30 Commits

Author SHA1 Message Date
904f6375be Consolidate per-operator trace lifting into GGraph.Embed + Trace.embed
Each graph-composition operator includes its operands via an index
translation preserving node payloads and edges. Capture that once as
GGraph.Embed (a structure, not a class: for g ; g both inclusions share
the type Embed g (g <~> g), so instance resolution could pick the wrong
copy) with five named witnesses, and replace the five structurally
identical trace-lifting inductions in Properties.lean with a single
generic Trace.embed plus one-line corollaries.

The same witnesses' nodes_eq fields will back the upcoming AST-id/CFG
label bijection, so the per-operator content is stated exactly once.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-02 15:06:40 -05:00
8cd053a242 Migrate Reaching.lean to projections via a generic Trace.steps
Finish the projection migration for reaching definitions by replacing the
accumulator-style runOfTrace*From definitions and their hand-rolled
re-association lemmas with a single analysis-agnostic projection:
Trace.steps / Traceₗ.steps, the chronological List of executed
(index, statement) pairs. Its four simp lemmas are one-line inductions,
with all re-association falling out of mathlib's List.append_assoc and
List.reverse_append.

Run is now an abbrev for List (State × BasicStmt) (latest-first, so
LastAssign keeps its first-match structure) and runOfTrace is just
steps.reverse.

Also hoist the generic reaches_final_post into Forward.lean, letting
analyze_correct' be stated directly about S.Post (prog.trace hrun).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-02 09:01:09 -05:00
0e6976f9b4 Migrate most of the codebase (sans Reaching.lean / LICM left) to projections 2026-07-01 22:56:29 -05:00
10b8fa97ca Add left-and-right open traces to help formalization
Co-Authored-By: OpenAI Codex <codex@openai.com>
2026-07-01 19:27:06 -05:00
8ed48cf444 Add non-state parameterized 'Reaches' relation 2026-07-01 13:02:39 -05:00
37d88f070a Remove 'prog.code s = some bs' argument to eval 2026-06-30 23:21:00 -05:00
6c05e401c1 Document Program.lean 2026-06-29 10:42:01 -05:00
fe5098095a Reorganize proofs to make 'Program' accessible to files in Language/ 2026-06-29 10:41:40 -05:00
59afbdaf71 Rename StateInterp to match the style of the rest of the codebase 2026-06-29 10:00:01 -05:00
490c472d22 Start documenting FiniteMap.lean 2026-06-29 08:59:51 -05:00
d1a11a9b2c Use alpha and beta for FiniteMap type variables 2026-06-29 08:59:37 -05:00
2598df690c Slightly tweak AboveBelow proofs 2026-06-29 08:16:55 -05:00
47d54f5b4b Further simplify proofs in AboveBelow
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 15:01:24 -05:00
8fa822b2e6 Improve performance by caching CFG building
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 14:39:14 -05:00
d66a7d0e3e Clean up and document AboveBelow 2026-06-28 14:38:12 -05:00
778e974dfb Prove that analysis results apply to all states, not just the final one
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 14:24:46 -05:00
319fa272ac Switch Reaching analysis to use Finset for more efficiency
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-28 09:46:54 -05:00
86bc33ee26 Register cases rules on lattice carriers for aesop automation
Tag the finite lattice carrier types with `@[aesop safe cases]`
(`AboveBelow`, `Sign`) so aesop performs the dominant proof step in this
framework -- case-splitting a lattice element -- automatically. Combined
with the existing `@[simp]` operation lemmas, this collapses the recurring
"case-split then reduce" proofs to a bare `aesop`:

  * AboveBelow's six lattice axioms drop their explicit `rcases`
  * Sign/Constant `plus_mono₂`/`minus_mono₂` become `by aesop`
  * Constant `plus_valid`/`minus_valid` shrink to a 2-line `rcases <;> simp_all`
  * `not_mk_lt_mk` is reexpressed via `le_cases`

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 20:01:01 -05:00
9e0702b5f5 Replace AboveBelow lattice-axiom case bashes with aesop
The six lattice axioms (sup/inf comm/assoc, absorption) all close with a
uniform `rcases <;> aesop`, removing the per-lemma simp-lemma lists that had
to be kept in sync with the Max/Min definitions.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 19:49:13 -05:00
445187837c Add Trace.concat notation and apply at call sites
Introduce `tr₁ ++< he >++ tr₂` scoped notation for `Trace.concat`
(precedence 65, right-associative, mirroring `++`) and use it
throughout Properties.lean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 19:46:19 -05:00
1a49689edc Apply aesop to reduce proofs
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 19:30:01 -05:00
b1b3b0d2fe Add more documentation
Signed-off-by: Danila Fedorin <danila.fedorin@gmail.com>
2026-06-27 19:20:23 -05:00
379438ec17 Add more documentation 2026-06-27 18:56:59 -05:00
1120e01605 Add some documentation 2026-06-27 18:56:59 -05:00
b6b30958aa Add proof of reaching definition analysis
This requires a few pieces:

* Make node tags use `Fin n` intead of natural numbers. This makes
  it possible to build a finite lattice over AST nodes, and also
  ensure automatic, total indexing from CFG nodes into the AST that
  created them. For this, use the elaborator to derive the ordering
  statements etc. where possible.
* Adjust the forward framework to enable proofs that don't just state
  correctness on the environment, but also on an arbitrary additional
  state accumulated from traversing the trace.
* State the reaching definition analysis's correctness in terms
  of this new framework.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 18:56:59 -05:00
5737805125 Remove maximal chain witness from FiniteHeightLattice
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 15:04:18 -05:00
e738eb4294 Usw OrderBot / OrderTop for lattice witnesses
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Co-Authored-By: OpenAI Codex <codex@openai.com>
2026-06-26 14:49:57 -05:00
6a6ed521ca Slightly tweak LICM implementation
Signed-off-by: Danila Fedorin <danila.fedorin@gmail.com>
2026-06-26 12:16:04 -05:00
c38c10fe9e Add a sketch of loop invariant code motion
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 12:16:04 -05:00
c367f130cf Add tagging machinery to assign unique IDs to AST nodes
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 12:16:04 -05:00
30 changed files with 2394 additions and 649 deletions

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@@ -1,5 +1,6 @@
import Spa.Analysis.Sign import Spa.Analysis.Sign
import Spa.Analysis.Constant import Spa.Analysis.Constant
import Spa.Analysis.Reaching
import Spa.Language.Notation import Spa.Language.Notation
namespace Spa namespace Spa
@@ -26,10 +27,11 @@ def testCodeCond₂ : Stmt := [obj_stmt|
if var { x := 1 } else { noop } if var { x := 1 } else { noop }
] ]
def testProgram : Program := testCode def testProgram : Program := { rootStmt := testCode }
end Spa end Spa
def main : IO Unit := def main : IO Unit :=
IO.println (Spa.ConstAnalysis.output Spa.testProgram ++ "\n" ++ IO.println (Spa.ConstAnalysis.output Spa.testProgram ++ "\n" ++
Spa.SignAnalysis.output Spa.testProgram) Spa.SignAnalysis.output Spa.testProgram ++ "\n" ++
Spa.ReachingAnalysis.output Spa.testProgram)

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@@ -19,3 +19,10 @@ import Spa.Showable
import Spa.Analysis.Utils import Spa.Analysis.Utils
import Spa.Analysis.Sign import Spa.Analysis.Sign
import Spa.Analysis.Constant import Spa.Analysis.Constant
import Spa.Language.Tagged.Id
import Spa.Language.Tagged.Derive
import Spa.Language.Tagged.Basic
import Spa.Language.Tagged.Properties
import Spa.Language.Tagged.Graphs
import Spa.Analysis.Reaching
import Spa.Transformation.Licm

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@@ -29,15 +29,13 @@ def minus : ConstLattice → ConstLattice → ConstLattice
lemma plus_mono₂ : Monotone₂ plus := lemma plus_mono₂ : Monotone₂ plus :=
AboveBelow.monotone₂_of_strict plus AboveBelow.monotone₂_of_strict plus
(fun y => by cases y <;> rfl) (fun x => by cases x <;> rfl) (fun y => by aesop) (fun x => by aesop)
(fun y hy => by cases y <;> first | exact absurd rfl hy | rfl) (fun y hy => by aesop) (fun x hx => by aesop)
(fun x hx => by cases x <;> first | exact absurd rfl hx | rfl)
lemma minus_mono₂ : Monotone₂ minus := lemma minus_mono₂ : Monotone₂ minus :=
AboveBelow.monotone₂_of_strict minus AboveBelow.monotone₂_of_strict minus
(fun y => by cases y <;> rfl) (fun x => by cases x <;> rfl) (fun y => by aesop) (fun x => by aesop)
(fun y hy => by cases y <;> first | exact absurd rfl hy | rfl) (fun y hy => by aesop) (fun x hx => by aesop)
(fun x hx => by cases x <;> first | exact absurd rfl hx | rfl)
def interpConst : ConstLattice Value Prop def interpConst : ConstLattice Value Prop
| .bot, _ => False | .bot, _ => False
@@ -96,36 +94,14 @@ def output : String :=
lemma plus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : } lemma plus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : }
(h₁ : g₁ (.int z₁)) (h₂ : g₂ (.int z₂)) : (h₁ : g₁ (.int z₁)) (h₂ : g₂ (.int z₂)) :
plus g₁ g₂ (.int (z₁ + z₂)) := by plus g₁ g₂ (.int (z₁ + z₂)) := by
rcases g₁ with _ | _ | c₁ rcases g₁ with _ | _ | c₁ <;> rcases g₂ with _ | _ | c₂ <;>
· exact h₁.elim simp_all [plus, constInterpretation, interpConst]
· rcases g₂ with _ | _ | c₂
· exact h₂.elim
· exact trivial
· exact trivial
· rcases g₂ with _ | _ | c₂
· exact h₂.elim
· exact trivial
· injection h₁ with hz₁
injection h₂ with hz₂
show Value.int (z₁ + z₂) = Value.int (c₁ + c₂)
rw [hz₁, hz₂]
lemma minus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : } lemma minus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : }
(h₁ : g₁ (.int z₁)) (h₂ : g₂ (.int z₂)) : (h₁ : g₁ (.int z₁)) (h₂ : g₂ (.int z₂)) :
minus g₁ g₂ (.int (z₁ - z₂)) := by minus g₁ g₂ (.int (z₁ - z₂)) := by
rcases g₁ with _ | _ | c₁ rcases g₁ with _ | _ | c₁ <;> rcases g₂ with _ | _ | c₂ <;>
· exact h₁.elim simp_all [minus, constInterpretation, interpConst]
· rcases g₂ with _ | _ | c₂
· exact h₂.elim
· exact trivial
· exact trivial
· rcases g₂ with _ | _ | c₂
· exact h₂.elim
· exact trivial
· injection h₁ with hz₁
injection h₂ with hz₂
show Value.int (z₁ - z₂) = Value.int (c₁ - c₂)
rw [hz₁, hz₂]
instance eval_valid : ValidExprEvaluator ConstLattice prog := by instance eval_valid : ValidExprEvaluator ConstLattice prog := by
constructor constructor
@@ -161,6 +137,13 @@ theorem analyze_correct {ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) :
variablesAt prog.finalState (result ConstLattice prog) ρ := variablesAt prog.finalState (result ConstLattice prog) ρ :=
Forward.analyze_correct ConstLattice prog hrun Forward.analyze_correct ConstLattice prog hrun
theorem analyze_correct_at {ρf : Env} (hrun : EvalStmt [] prog.rootStmt ρf)
{s : prog.State} {ρin ρout : Env}
(hr : Reaches (prog.trace hrun) s ρin ρout) :
joinForKey s (result ConstLattice prog) ρin
variablesAt s (result ConstLattice prog) ρout :=
Forward.analyze_correct_at ConstLattice prog hrun hr
end ConstAnalysis end ConstAnalysis
end Spa end Spa

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@@ -10,12 +10,11 @@ namespace Forward
variable {L : Type} [FiniteHeightLattice L] {prog : Program} [E : StmtEvaluator L prog] variable {L : Type} [FiniteHeightLattice L] {prog : Program} [E : StmtEvaluator L prog]
def updateVariablesForState (s : prog.State) (sv : StateVariables L prog) : def updateVariablesForState (s : prog.State) (sv : StateVariables L prog) :
VariableValues L prog := VariableValues L prog := E.eval s (variablesAt s sv)
(prog.code s).foldl (fun vs bs => E.eval s bs vs) (variablesAt s sv)
lemma updateVariablesForState_mono (s : prog.State) : lemma updateVariablesForState_mono (s : prog.State) :
Monotone (updateVariablesForState (L := L) s) := fun _ _ hle => Monotone (updateVariablesForState (L := L) s) := fun _ _ hle =>
foldl_mono' (prog.code s) _ (E.eval_mono s ·) (variablesAt_le hle s) E.eval_mono s (variablesAt_le hle s)
def updateAll (sv : StateVariables L prog) : StateVariables L prog := def updateAll (sv : StateVariables L prog) : StateVariables L prog :=
FiniteMap.generalizedUpdate id updateVariablesForState FiniteMap.generalizedUpdate id updateVariablesForState
@@ -54,67 +53,121 @@ lemma joinForKey_initialState :
rw [joinForKey, prog.incoming_initialState_eq_nil] rw [joinForKey, prog.incoming_initialState_eq_nil]
rfl rfl
variable [I : LatticeInterpretation L] [V : ValidStmtEvaluator L prog] class ValidStateEvaluator (L : Type) [FiniteHeightLattice L] (prog : Program)
[E : StmtEvaluator L prog] [S : StateInterpretation L prog] where
valid : (s₁ s₂ : prog.State) {ρ₁ ρ₂ ρ₃: Env}
{vs : VariableValues L prog},
(tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂)
(hbs : EvalBasicStmtOpt ρ₂ (prog.cfg.nodes s₂) ρ₃) vs (S.Pre tr)
E.eval s₂ vs (S.Post (tr ++ hbs))
botV_init : botV L prog (S.Pre (Traceₗ.single prog.cfg prog.initialState []))
instance [LatticeInterpretation L] [ValidStmtEvaluator L prog] :
ValidStateEvaluator L prog where
valid := by intro _ _ _ _ _ _ tr hbs hvs; exact ValidStmtEvaluator.valid hbs hvs
botV_init := by intro k l _ v hmem; cases hmem
section
variable [S : StateInterpretation L prog] [V : ValidStateEvaluator L prog]
omit [DecidableEq L] in omit [DecidableEq L] in
lemma eval_fold_valid {s : prog.State} {bss : List BasicStmt} lemma updateAll_matches {s s₂ : prog.State} {sv : StateVariables L prog}
{vs : VariableValues L prog} {ρ₁ ρ : Env} {ρ₁ ρ₂ ρ : Env}
(hbss : EvalBasicStmts ρ₁ bss ρ₂) (hvs : vs ρ) : (tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ)
bss.foldl (fun vs bs => E.eval s bs vs) vs ρ₂ := by (hnode : EvalBasicStmtOpt ρ₂ (prog.code s) ρ₃)
induction hbss generalizing vs with (hvs : variablesAt s₂ sv (S.Pre tr)) :
| nil => exact hvs variablesAt s₂ (updateAll sv) (S.Post (tr ++ hnode)) := by
| cons hbs _ ih => exact ih (ValidStmtEvaluator.valid hbs hvs)
omit [DecidableEq L] in
lemma updateVariablesForState_matches {s : prog.State}
{sv : StateVariables L prog} {ρ₁ ρ₂ : Env}
(hbss : EvalBasicStmts ρ₁ (prog.code s) ρ₂)
(hvs : variablesAt s sv ρ₁) :
updateVariablesForState s sv ρ₂ :=
eval_fold_valid hbss hvs
omit [DecidableEq L] in
lemma updateAll_matches {s : prog.State} {sv : StateVariables L prog}
{ρ₁ ρ₂ : Env} (hbss : EvalBasicStmts ρ₁ (prog.code s) ρ₂)
(hvs : variablesAt s sv ρ₁) :
variablesAt s (updateAll sv) ρ₂ := by
rw [variablesAt_updateAll] rw [variablesAt_updateAll]
exact updateVariablesForState_matches hbss hvs exact V.valid s₁ s₂ tr hnode hvs
lemma stepTrace {s₁ : prog.State} {ρ₁ ρ₂ : Env} lemma stepTrace {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
(hjoin : joinForKey s₁ (result L prog) ρ) (tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ)
(hbss : EvalBasicStmts ρ₁ (prog.code s₁) ρ₂) : (hjoin : joinForKey s₂ (result L prog) (S.Pre tr))
variablesAt s₁ (result L prog) ρ₂ := by (hnode : EvalBasicStmtOpt ρ₂ (prog.code s₂) ρ₃) :
variablesAt s₂ (result L prog) (S.Post (tr ++ hnode)) := by
rw [result_eq L prog] rw [result_eq L prog]
refine updateAll_matches hbss ?_ refine updateAll_matches tr hnode ?_
rw [variablesAt_joinAll] rw [variablesAt_joinAll]
exact hjoin exact hjoin
lemma walkTrace {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env} /-- Soundness at *every* visited node: if the analysis result over-approximates the
(hjoin : joinForKey s₁ (result L prog) ρ₁) incoming environment at the start of the trace, then at each node reached along the
(tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) : way it over-approximates both the environment entering that node (via `joinForKey`)
variablesAt s₂ (result L prog) ρ₂ := by and the environment leaving it (via `variablesAt`). The intermediate `variablesAt`
induction tr with evidence used to be computed and discarded inside `walkTrace`; here it is returned. -/
| single hbss => exact stepTrace hjoin hbss lemma walkTrace_reaches {s₁ s₂ s₃: prog.State} {ρ₁ ρ₂ ρ₃: Env}
| @edge _ ρ' _ i₁ i₂ _ hbss hedge _ ih => {s : prog.State} {ρin ρout : Env}
have hstep : variablesAt i₁ (result L prog) ρ' := {tr : Trace prog.cfg s₂ s₃ ρ₂ ρ}
stepTrace hjoin hbss (hr : Reaches tr s ρin ρout)
have hmem : variablesAt i (result L prog) (trₗ : Traceₗ prog.cfg s s₂ ρ₁ ρ₂)
(result L prog).valuesAt (prog.incoming i₂) := (hjoin : joinForKey s₂ (result L prog) (S.Pre trₗ)) :
FiniteMap.mem_valuesAt prog.states_nodup joinForKey s (result L prog) (S.Pre (trₗ ++ hr.pre))
(prog.mem_incoming_of_edge hedge) (variablesAt_mem i₁ (result L prog)) variablesAt s (result L prog) (S.Post (trₗ ++ hr.post)) := by
exact ih (interp_foldr hstep hmem) induction hr with
| single_here hnode =>
simp [Reaches.pre, Reaches.post]
refine ?_, ?_ <;> try simpa [HAppend.hAppend]
exact stepTrace trₗ hjoin hnode
| edge_here hnode hedge rest =>
simp [Reaches.pre, Reaches.post]
refine ?_, ?_ <;> try simpa [HAppend.hAppend]
exact stepTrace trₗ hjoin hnode
| edge_there hnode hedge rest hr' ih =>
have hstep := stepTrace trₗ hjoin hnode
have hmem := FiniteMap.mem_valuesAt prog.states_nodup
(prog.mem_incoming_of_edge hedge) (variablesAt_mem _ (result L prog))
simpa [Reaches.pre, Reaches.post, HAppend.hAppend] using
ih ((trₗ ++ hnode).addEdge hedge)
(interp_foldr (S.post_pre (trₗ ++ hnode) hedge hstep) hmem)
omit V in omit [DecidableEq L] in
lemma interp_joinForKey_initialState : /-- The final node of a trace is always reached, with the environment/state the trace
joinForKey prog.initialState (result L prog) [] := by ends in. Used to recover the final-state soundness theorem from `walkTrace_reaches`. -/
rw [joinForKey_initialState] def reaches_final {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
exact interp_botV_nil (tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) :
Σ ρin, Reaches tr s₂ ρin ρ₂ :=
match tr with
| .single hnode => _, .single_here hnode
| .edge hnode hedge rest =>
let ρin, r' := reaches_final rest; ρin, .edge_there hnode hedge _ r'
omit [DecidableEq L] in
/-- Reaching the final node covers the whole trace. -/
@[simp] lemma reaches_final_post {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
(tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) :
(reaches_final tr).2.post = tr := by
induction tr with
| single hnode => rfl
| edge hnode hedge rest ih => simp [reaches_final, Reaches.post, ih]
variable (L prog) in variable (L prog) in
theorem analyze_correct {ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) : /-- Soundness at every program point reached during execution: for any node `s` visited
by the run `hrun` (witnessed by `hr`), the analysis result over-approximates both the
environment entering `s` and the one leaving it. The final-state theorem
`analyze_correct_state` is the special case where `s` is `prog.finalState`. -/
theorem analyze_correct_at {ρf : Env} (hrun : EvalStmt [] prog.rootStmt ρf)
{s : prog.State} {ρin ρout : Env}
(hr : Reaches (prog.trace hrun) s ρin ρout) :
joinForKey s (result L prog) (S.Pre hr.pre)
variablesAt s (result L prog) (S.Post hr.post) := by
refine walkTrace_reaches hr (Traceₗ.single _ _ []) ?_
rw [joinForKey_initialState]
exact ValidStateEvaluator.botV_init
variable (L prog) in
theorem analyze_correct'
{ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) :
variablesAt prog.finalState (result L prog) (S.Post (prog.trace hrun)) := by
have h := (analyze_correct_at L prog hrun (reaches_final (prog.trace hrun)).2).2
rwa [reaches_final_post] at h
end
variable (L prog) in
theorem analyze_correct [LatticeInterpretation L] [ValidStmtEvaluator L prog]
{ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) :
variablesAt prog.finalState (result L prog) ρ := variablesAt prog.finalState (result L prog) ρ :=
walkTrace interp_joinForKey_initialState (prog.trace hrun) analyze_correct' L prog hrun
end Forward end Forward

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@@ -14,44 +14,50 @@ lemma updateVariablesFromExpression_mono (k : String) (e : Expr) :
Monotone (updateVariablesFromExpression (L := L) (prog := prog) k e) := Monotone (updateVariablesFromExpression (L := L) (prog := prog) k e) :=
FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => E.eval_mono e) FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => E.eval_mono e)
def evalBasicStmt (_ : prog.State) (bs : BasicStmt) def evalBasicStmt (bs : BasicStmt)
(vs : VariableValues L prog) : VariableValues L prog := (vs : VariableValues L prog) : VariableValues L prog :=
match bs with match bs with
| .assign k e => updateVariablesFromExpression k e vs | .assign k e => updateVariablesFromExpression k e vs
| .noop => vs | .noop => vs
lemma evalBasicStmt_mono (s : prog.State) (bs : BasicStmt) : lemma evalBasicStmt_mono (bs : BasicStmt) :
Monotone (evalBasicStmt (L := L) (prog := prog) s bs) := by Monotone (evalBasicStmt (L := L) (prog := prog) bs) := by
cases bs with cases bs with
| assign k e => exact updateVariablesFromExpression_mono k e | assign k e => exact updateVariablesFromExpression_mono k e
| noop => exact monotone_id | noop => exact monotone_id
def evalBasicStmtOpt (obs : Option BasicStmt)
(vs : VariableValues L prog) : VariableValues L prog :=
match obs with
| none => vs
| some bs => evalBasicStmt bs vs
lemma evalBasicStmtOpt_mono (obs : Option BasicStmt) :
Monotone (evalBasicStmtOpt (L := L) (prog := prog) obs) := by
cases obs <;> unfold evalBasicStmtOpt
· exact monotone_id
· apply evalBasicStmt_mono
instance ExprEvaluator.toStmtEvaluator : StmtEvaluator L prog := instance ExprEvaluator.toStmtEvaluator : StmtEvaluator L prog :=
evalBasicStmt, evalBasicStmt_mono evalBasicStmtOpt prog.code,
by intro s; simp; exact (evalBasicStmtOpt_mono (prog.code s))
instance ExprEvaluator.toStmtEvaluator_valid [LatticeInterpretation L] instance ExprEvaluator.toStmtEvaluator_valid [LatticeInterpretation L]
[ValidExprEvaluator L prog] : ValidStmtEvaluator L prog := by [ValidExprEvaluator L prog] : ValidStmtEvaluator L prog := by
constructor constructor
intro s vs ρ₁ ρ₂ bs hbs hvs simp [StmtEvaluator.eval, evalBasicStmtOpt]
cases hbs with intro s vs ρ₁ ρ₂; generalize prog.code s = obs; intro hev hvs
| noop => exact hvs rcases hev with _ | @_,bs,hev <;> try simpa
| assign k e v hev => rcases hev with _ | @k, e, v, hev <;> try simpa
intro k' l hk'l v' hv' intros k' l' hkl' v' hρ
cases hv' with rcases hρ with _ | _,_,_,_,_,hne,hmem <;> simp [evalBasicStmt] at hkl'
| here => · have hl := FiniteMap.generalizedUpdate_mem_eq (f := id)
have hk'l₀ : (k, l) FiniteMap.generalizedUpdate (ks := prog.vars) id (g := fun _ vs => E.eval e vs) (List.mem_singleton_self k) hkl'
(fun _ vs => E.eval e vs) [k] vs := hk'l rewrite [hl]; simp
have hl := FiniteMap.generalizedUpdate_mem_eq (f := id) exact ValidExprEvaluator.valid hev hvs
(g := fun _ vs => E.eval e vs) (List.mem_singleton_self k) hk'l₀ · have hl := FiniteMap.generalizedUpdate_not_mem_backward
rw [hl] (fun hmem => hne (List.mem_singleton.mp hmem)) hkl'
exact ValidExprEvaluator.valid hev hvs apply hvs _ _ hl _ hmem
| there _ _ _ _ _ hne hmem' =>
have hk'l₀ : (k', l) FiniteMap.generalizedUpdate (ks := prog.vars) id
(fun _ vs => E.eval e vs) [k] vs := hk'l
have hk'l' : (k', l) (id vs : VariableValues L prog) :=
FiniteMap.generalizedUpdate_not_mem_backward
(fun hmem => hne (List.mem_singleton.mp hmem)) hk'l₀
exact hvs _ _ hk'l' _ hmem'
end Forward end Forward

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@@ -7,8 +7,8 @@ namespace Forward
variable (L : Type) [Lattice L] (prog : Program) variable (L : Type) [Lattice L] (prog : Program)
class StmtEvaluator where class StmtEvaluator where
eval : prog.State BasicStmt VariableValues L prog VariableValues L prog eval : prog.State VariableValues L prog VariableValues L prog
eval_mono : s bs, Monotone (eval s bs) eval_mono : s, Monotone (eval s)
class ExprEvaluator where class ExprEvaluator where
eval : Expr VariableValues L prog L eval : Expr VariableValues L prog L
@@ -21,9 +21,8 @@ class ValidExprEvaluator [ExprEvaluator L prog] [I : LatticeInterpretation L] :
class ValidStmtEvaluator [E : StmtEvaluator L prog] [LatticeInterpretation L] : class ValidStmtEvaluator [E : StmtEvaluator L prog] [LatticeInterpretation L] :
Prop where Prop where
valid : {s : prog.State} {vs : VariableValues L prog} {ρ₁ ρ₂ : Env} valid : {s : prog.State} {vs : VariableValues L prog} {ρ₁ ρ₂ : Env},
{bs : BasicStmt}, EvalBasicStmtOpt ρ₁ (prog.code s) ρ₂ vs ρ₁ E.eval s vs ρ₂
EvalBasicStmt ρ₁ bs ρ₂ vs ρ₁ E.eval s bs vs ρ₂
end Forward end Forward

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@@ -64,39 +64,57 @@ lemma variablesAt_joinAll (s : prog.State) (sv : StateVariables L prog) :
variablesAt s (joinAll sv) = joinForKey s sv := variablesAt s (joinAll sv) = joinForKey s sv :=
joinAll_mem_eq (variablesAt_mem s (joinAll sv)) joinAll_mem_eq (variablesAt_mem s (joinAll sv))
/-! ### Lifting an interpretation to variable maps -/ class StateInterpretation (L : Type) [Lattice L] (prog : Program) where
Proj : Type
Pre : {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}, Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂ Proj
Post : {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}, Trace prog.cfg s₁ s₂ ρ₁ ρ₂ Proj
variable [I : LatticeInterpretation L] interp : VariableValues L prog (p : Proj) Prop
interp_sup : {vs₁ vs₂ : VariableValues L prog} {p : Proj},
interp vs₁ p interp vs₂ p interp (vs₁ vs₂) p
interp_inf : {vs₁ vs₂ : VariableValues L prog} {p : Proj},
interp vs₁ p interp vs₂ p interp (vs₁ vs₂) p
omit [FiniteHeightLattice L] in post_pre : {vs} {s₁ s₂ s₃: prog.State} {ρ₁ ρ₂ : Env}
instance : Interp (VariableValues L prog) (Env Prop) where (tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) (hedge : (s₂, s₃) prog.cfg.edges),
interp (vs : VariableValues L prog) (ρ : Env) : Prop := interp vs (Post tr) interp vs (Pre (tr.addEdge hedge))
(k : String) (l : L), (k, l) vs
(v : Value), Env.Mem (k, v) ρ I.interp l v
lemma interp_botV_nil : botV L prog [] := by instance [S : StateInterpretation L prog] :
intro k l _ v hmem Interp (VariableValues L prog) (S.Proj Prop) :=
cases hmem S.interp
omit [FiniteHeightLattice L] in lemma interp_foldr [S : StateInterpretation L prog]
lemma interp_sup {vs₁ vs₂ : VariableValues L prog} {ρ : Env} {vs : VariableValues L prog} {vss : List (VariableValues L prog)}
(h : vs₁ ρ vs ρ) : vs vs ρ := by {p : S.Proj} (hvs : vs p) (hmem : vs vss) :
intro k l hmem v hv vss.foldr (· ·) (botV L prog) p := by
obtain l₁, l₂, rfl, h₁, h₂ := FiniteMap.mem_sup hmem
rcases h with h | h
· exact I.interp_sup v (Or.inl (h _ _ h₁ _ hv))
· exact I.interp_sup v (Or.inr (h _ _ h₂ _ hv))
lemma interp_foldr {vs : VariableValues L prog}
{vss : List (VariableValues L prog)} {ρ : Env}
(hvs : vs ρ) (hmem : vs vss) :
vss.foldr (· ·) (botV L prog) ρ := by
induction vss with induction vss with
| nil => cases hmem | nil => cases hmem
| cons vs' vss' ih => | cons vs' vss' ih =>
rcases List.mem_cons.mp hmem with rfl | hmem' rcases List.mem_cons.mp hmem with rfl | hmem'
· exact interp_sup (Or.inl hvs) · exact S.interp_sup (Or.inl hvs)
· exact interp_sup (Or.inr (ih hmem')) · exact S.interp_sup (Or.inr (ih hmem'))
variable [I : LatticeInterpretation L]
instance : StateInterpretation L prog where
Proj := Env
Pre := fun {_ _ _ ρ₂} _ => ρ₂
Post := fun {_ _ _ ρ₂} _ => ρ₂
interp vs ρ := (k : String) (l : L), (k, l) vs
(v : Value), Env.Mem (k, v) ρ I.interp l v
interp_sup := by
intro vs₁ vs₂ ρ h k l hmem v hv
obtain l₁, l₂, rfl, h₁, h₂ := FiniteMap.mem_sup hmem
rcases h with h | h
· exact I.interp_sup v (Or.inl (h _ _ h₁ _ hv))
· exact I.interp_sup v (Or.inr (h _ _ h₂ _ hv))
interp_inf := by
intro vs₁ vs₂ ρ h k l hmem v hv
obtain l₁, l₂, rfl, h₁, h₂ := FiniteMap.mem_inf hmem
exact I.interp_inf v h.1 _ _ h₁ _ hv, h.2 _ _ h₂ _ hv
post_pre := by simp
end Forward end Forward

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@@ -1,34 +1,41 @@
import Spa.Analysis.Forward import Spa.Analysis.Forward
import Spa.Lattice.Bool import Spa.Lattice.Finset
import Spa.Language.Tagged.Graphs
import Spa.Showable import Spa.Showable
namespace Spa namespace Spa
open Forward open Forward
instance : Showable Bool := fun b => if b then "true" else "false" instance {n : } : Showable (Finset (Fin n)) :=
fun s =>
"{" ++ (List.finRange n).foldr
(fun i rest => if i s then show' i ++ ", " ++ rest else rest) ""
++ "}"
abbrev DefSet (prog : Program) : Type := FiniteMap prog.State Bool prog.states abbrev DefSet (prog : Program) : Type := Finset prog.NodeId
namespace ReachingAnalysis namespace ReachingAnalysis
variable (prog : Program) variable (prog : Program)
def genSet (s : prog.State) : DefSet prog := def genSet (s : prog.State) : DefSet prog := (prog.nodeIdOf s).elim {} (fun x => {x})
FiniteMap.updating ( : DefSet prog) [s] (fun _ => true)
def eval (s : prog.State) : def eval (s : prog.State) (vs : VariableValues (DefSet prog) prog) : VariableValues (DefSet prog) prog :=
BasicStmt VariableValues (DefSet prog) prog VariableValues (DefSet prog) prog match prog.code s with
| .assign k _, vs => | none => vs
FiniteMap.generalizedUpdate id (fun _ _ => genSet prog s) [k] vs | some bs =>
| .noop, vs => vs match bs with
| .assign k _ => FiniteMap.generalizedUpdate id (fun _ _ => genSet prog s) [k] vs
| .noop => vs
lemma eval_mono (s : prog.State) (bs : BasicStmt) : lemma eval_mono (s : prog.State) :
Monotone (eval prog s bs) := by Monotone (eval prog s) := by
cases bs with intros vs₁ vs₂ hle
| assign k e => unfold eval; split <;> try simpa
exact FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => monotone_const) split <;> try simpa
| noop => exact monotone_id apply FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => monotone_const)
assumption
instance stmtEvaluator : StmtEvaluator (DefSet prog) prog := instance stmtEvaluator : StmtEvaluator (DefSet prog) prog :=
eval prog, eval_mono prog eval prog, eval_mono prog
@@ -36,6 +43,93 @@ instance stmtEvaluator : StmtEvaluator (DefSet prog) prog :=
def output : String := def output : String :=
show' (result (DefSet prog) prog) show' (result (DefSet prog) prog)
/-- The statements a trace executed, paired with the state each executed at,
most recent first (matching `LastAssign`, which scans for the most recent
assignment). This is `Trace.steps` (chronological) reversed, so facts about
concatenating traces reduce to mathlib's `List.append`/`List.reverse` lemmas. -/
abbrev Run (prog : Program) : Type := List (prog.State × BasicStmt)
@[aesop unsafe cases]
inductive LastAssign (prog : Program) (x : String) : Run prog prog.NodeId Prop
| here (s : prog.State) (e : Expr) (hc : prog.code s = some (.assign x e))
(rest : Run prog) :
LastAssign prog x ((s, .assign x e) :: rest) (prog.nodeIdOfNonempty s hc)
| there (s : prog.State) (bs : BasicStmt) (hc : prog.code s = some bs)
(rest : Run prog) {n : prog.NodeId} :
( e, bs .assign x e) LastAssign prog x rest n
LastAssign prog x ((s, bs) :: rest) n
def runOfTraceₗ {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
(tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂) : Run prog :=
tr.steps.reverse
def runOfTrace {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
(tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) : Run prog :=
tr.steps.reverse
instance stateInterp : StateInterpretation (DefSet prog) prog where
Proj := Run prog
Pre := @runOfTraceₗ prog
Post := @runOfTrace prog
interp vs run := (x : String) (assigners : DefSet prog), (x, assigners) vs
(n : prog.NodeId), LastAssign prog x run n n assigners
interp_sup := by
intro vs₁ vs₂ run h x assigners hmem n hla
obtain a₁, a₂, rfl, h₁, h₂ := FiniteMap.mem_sup hmem
aesop (add simp Finset.mem_union)
interp_inf := by
intro vs₁ vs₂ run h x assigners hmem n hla
obtain a₁, a₂, rfl, h₁, h₂ := FiniteMap.mem_inf hmem
aesop (add simp Finset.mem_inter)
post_pre := by
intro vs s₁ s₂ s₃ ρ₁ ρ₂ tr hedge hvs
simpa [runOfTrace, runOfTraceₗ] using hvs
private lemma valid_step (s : prog.State) {ρ₁ ρ₂ : Env}
{obs : Option BasicStmt} (hcode : prog.code s = obs)
(hbs : EvalBasicStmtOpt ρ₁ obs ρ₂)
{vs : VariableValues (DefSet prog) prog} {run : Run prog}
(hvs : vs run) :
eval prog s vs ((hbs.steps s).reverse ++ run) := by
cases hbs with
| none => simpa [eval, hcode, EvalBasicStmtOpt.steps] using hvs
| some hbs =>
cases hbs with
| noop =>
simp [eval, hcode, EvalBasicStmtOpt.steps]
intro x assigners hmem n hla; aesop
| assign x e v hev =>
simp [eval, hcode, EvalBasicStmtOpt.steps]; intro k assigners hmem n hla
by_cases hx : k = x
· subst hx
have hd := FiniteMap.generalizedUpdate_mem_eq (List.mem_singleton.mpr rfl) hmem
rcases hla
<;> simp [Program.nodeIdOfNonempty, hd, genSet, Option.get] <;> aesop
· have hmem' := FiniteMap.generalizedUpdate_not_mem_backward
(fun hc => hx (List.mem_singleton.mp hc)) hmem
aesop
instance validStateEvaluator : ValidStateEvaluator (DefSet prog) prog where
valid := by
intro s₁ s₂ ρ₁ ρ₂ ρ₃ vs tr hbs hvs
show eval prog s₂ vs (runOfTrace prog (tr ++ hbs))
simpa [runOfTrace, runOfTraceₗ] using valid_step prog s₂ rfl hbs hvs
botV_init := by intro x assigners _ n hla; cases hla
theorem analyze_correct {ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) :
variablesAt prog.finalState (result (DefSet prog) prog)
(runOfTrace prog (prog.trace hrun)) :=
Forward.analyze_correct' (DefSet prog) prog hrun
theorem analyze_correct_at {ρf : Env} (hrun : EvalStmt [] prog.rootStmt ρf)
{s : prog.State} {ρin ρout : Env}
(hr : Reaches (prog.trace hrun) s ρin ρout) :
joinForKey s (result (DefSet prog) prog) (runOfTraceₗ prog hr.pre)
variablesAt s (result (DefSet prog) prog) (runOfTrace prog hr.post) :=
Forward.analyze_correct_at (DefSet prog) prog hrun hr
end ReachingAnalysis end ReachingAnalysis
end Spa end Spa

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@@ -13,6 +13,8 @@ inductive Sign where
| zero | zero
deriving DecidableEq deriving DecidableEq
attribute [aesop safe cases] Sign
instance : Showable Sign := instance : Showable Sign :=
fun fun
| .plus => "+" | .plus => "+"
@@ -57,21 +59,13 @@ def minus : SignLattice → SignLattice → SignLattice
lemma plus_mono₂ : Monotone₂ plus := lemma plus_mono₂ : Monotone₂ plus :=
AboveBelow.monotone₂_of_strict plus AboveBelow.monotone₂_of_strict plus
(fun y => by cases y <;> rfl) (fun y => by aesop) (fun x => by aesop)
(fun x => by rcases x with _ | _ | s <;> first | rfl | (cases s <;> rfl)) (fun y hy => by aesop) (fun x hx => by aesop)
(fun y hy => by cases y <;> first | exact absurd rfl hy | rfl)
(fun x hx => by
rcases x with _ | _ | s <;>
first | exact absurd rfl hx | rfl | (cases s <;> rfl))
lemma minus_mono₂ : Monotone₂ minus := lemma minus_mono₂ : Monotone₂ minus :=
AboveBelow.monotone₂_of_strict minus AboveBelow.monotone₂_of_strict minus
(fun y => by cases y <;> rfl) (fun y => by aesop) (fun x => by aesop)
(fun x => by rcases x with _ | _ | s <;> first | rfl | (cases s <;> rfl)) (fun y hy => by aesop) (fun x hx => by aesop)
(fun y hy => by cases y <;> first | exact absurd rfl hy | rfl)
(fun x hx => by
rcases x with _ | _ | s <;>
first | exact absurd rfl hx | rfl | (cases s <;> rfl))
def interpSign : SignLattice Value Prop def interpSign : SignLattice Value Prop
| .bot, _ => False | .bot, _ => False
@@ -219,6 +213,13 @@ theorem analyze_correct {ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) :
variablesAt prog.finalState (result SignLattice prog) ρ := variablesAt prog.finalState (result SignLattice prog) ρ :=
Forward.analyze_correct SignLattice prog hrun Forward.analyze_correct SignLattice prog hrun
theorem analyze_correct_at {ρf : Env} (hrun : EvalStmt [] prog.rootStmt ρf)
{s : prog.State} {ρin ρout : Env}
(hr : Reaches (prog.trace hrun) s ρin ρout) :
joinForKey s (result SignLattice prog) ρin
variablesAt s (result SignLattice prog) ρout :=
Forward.analyze_correct_at SignLattice prog hrun hr
end SignAnalysis end SignAnalysis
end Spa end Spa

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@@ -12,7 +12,7 @@ def doStep (f : αα) (hf : Monotone f) :
(g : ) (c : LTSeries α), c.length + g = height (α := α) + 1 (g : ) (c : LTSeries α), c.length + g = height (α := α) + 1
c.last f c.last {a : α // a = f a} c.last f c.last {a : α // a = f a}
| 0, c, hlen, _ => | 0, c, hlen, _ =>
absurd (FiniteHeightLattice.chains_bounded c) (by simp only [height] at hlen; omega) absurd (FiniteHeightLattice.chains_bounded c) (by omega)
| g + 1, c, hlen, hle => | g + 1, c, hlen, hle =>
if heq : c.last = f c.last then if heq : c.last = f c.last then
c.last, heq c.last, heq
@@ -24,8 +24,7 @@ def doStep (f : αα) (hf : Monotone f) :
def fix (f : α α) (hf : Monotone f) : {a : α // a = f a} := def fix (f : α α) (hf : Monotone f) : {a : α // a = f a} :=
doStep f hf (height (α := α) + 1) (RelSeries.singleton _ ) doStep f hf (height (α := α) + 1) (RelSeries.singleton _ )
(by simp) (by simp)
(by simpa [RelSeries.last_singleton] (by simp)
using FiniteHeightLattice.bot_le α (f ))
def aFix (f : α α) (hf : Monotone f) : α := def aFix (f : α α) (hf : Monotone f) : α :=
(fix f hf).1 (fix f hf).1
@@ -40,7 +39,7 @@ lemma doStep_le (f : αα) (hf : Monotone f)
(hle : c.last f c.last), c.last b (hle : c.last f c.last), c.last b
(doStep f hf g c hlen hle : α) b (doStep f hf g c hlen hle : α) b
| 0, c, hlen, _ => fun _ => | 0, c, hlen, _ => fun _ =>
absurd (FiniteHeightLattice.chains_bounded c) (by simp only [height] at hlen; omega) absurd (FiniteHeightLattice.chains_bounded c) (by omega)
| g + 1, c, hlen, hle => fun hcb => by | g + 1, c, hlen, hle => fun hcb => by
rw [doStep] rw [doStep]
split split
@@ -50,7 +49,7 @@ lemma doStep_le (f : αα) (hf : Monotone f)
theorem aFix_le (f : α α) (hf : Monotone f) theorem aFix_le (f : α α) (hf : Monotone f)
{a : α} (ha : a = f a) : aFix f hf a := {a : α} (ha : a = f a) : aFix f hf a :=
doStep_le f hf ha _ _ _ _ (by simpa using FiniteHeightLattice.bot_le α a) doStep_le f hf ha _ _ _ _ (by simp)
end Fixedpoint end Fixedpoint

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@@ -3,56 +3,4 @@ import Spa.Language.Semantics
import Spa.Language.Graphs import Spa.Language.Graphs
import Spa.Language.Traces import Spa.Language.Traces
import Spa.Language.Properties import Spa.Language.Properties
import Mathlib.Data.Finset.Sort import Spa.Language.Program
import Mathlib.Data.String.Basic
namespace Spa
structure Program where
rootStmt : Stmt
namespace Program
variable (p : Program)
def cfg : Graph := Graph.wrap p.rootStmt.cfg
abbrev State : Type := p.cfg.Index
def initialState : p.State := p.rootStmt.cfg.wrapInput
def finalState : p.State := p.rootStmt.cfg.wrapOutput
theorem trace {ρ : Env} (h : EvalStmt [] p.rootStmt ρ) :
Trace p.cfg p.initialState p.finalState [] ρ := by
obtain i₁, h₁, i₂, h₂, tr := EndToEndTrace.wrap (Stmt.cfg_sufficient h)
rw [Graph.wrap_inputs, List.mem_singleton] at h₁
rw [Graph.wrap_outputs, List.mem_singleton] at h₂
subst h₁; subst h₂
exact tr
def vars : List String := p.rootStmt.vars.sort (· ·)
lemma vars_nodup : p.vars.Nodup := Finset.sort_nodup _ _
def states : List p.State := p.cfg.indices
lemma states_complete (s : p.State) : s p.states := p.cfg.mem_indices s
lemma states_nodup : p.states.Nodup := p.cfg.nodup_indices
def code (st : p.State) : List BasicStmt := p.cfg.nodes st
def incoming (s : p.State) : List p.State := p.cfg.predecessors s
lemma incoming_initialState_eq_nil : p.incoming p.initialState = [] :=
Graph.wrap_predecessors_eq_nil p.rootStmt.cfg p.initialState
(by rw [Graph.wrap_inputs]; exact List.mem_singleton_self _)
lemma mem_incoming_of_edge {s₁ s₂ : p.State}
(h : (s₁, s₂) p.cfg.edges) : s₁ p.incoming s₂ :=
p.cfg.mem_predecessors_of_edge h
end Program
end Spa

View File

@@ -25,6 +25,15 @@ indexing into a list.
-/ -/
/-- Logically, when combining `Fin`s from two distinct pools,
the combination is disjoint. -/
lemma Fin.castAdd_ne_natAdd {n m : } (i : Fin n) (j : Fin m) :
Fin.castAdd m i Fin.natAdd n j := by
intro h
have := congrArg Fin.val h
simp only [Fin.coe_castAdd, Fin.coe_natAdd] at this
omega
/-- Bump the upper bound of a list of `Fin`s without changing their value. -/ /-- Bump the upper bound of a list of `Fin`s without changing their value. -/
def List.finCastAdd {n : } (l : List (Fin n)) (m : ) : List (Fin (n + m)) := def List.finCastAdd {n : } (l : List (Fin n)) (m : ) : List (Fin (n + m)) :=
l.map (Fin.castAdd m) l.map (Fin.castAdd m)
@@ -130,9 +139,9 @@ def loopOut (g : GGraph α) : Fin (2 + g.size) := (1 : Fin 2).castAdd g.size
This is technically sloppy (see module comment), but it's simple. This is technically sloppy (see module comment), but it's simple.
-/ -/
def loop (g : GGraph (List β)) : GGraph (List β) where def loop (g : GGraph (Option β)) : GGraph (Option β) where
size := 2 + g.size size := 2 + g.size
nodes := Fin.append (fun _ : Fin 2 => []) g.nodes nodes := Fin.append (fun _ : Fin 2 => none) g.nodes
edges := g.edges.finNatAddProd 2 ++ edges := g.edges.finNatAddProd 2 ++
((g.loopIn, ·) <$> g.inputs.finNatAdd 2) ++ ((g.loopIn, ·) <$> g.inputs.finNatAdd 2) ++
((·, g.loopOut) <$> g.outputs.finNatAdd 2) ++ ((·, g.loopOut) <$> g.outputs.finNatAdd 2) ++
@@ -140,9 +149,9 @@ def loop (g : GGraph (List β)) : GGraph (List β) where
inputs := [g.loopIn] inputs := [g.loopIn]
outputs := [g.loopOut] outputs := [g.loopOut]
@[simp] lemma loop_inputs (g : GGraph (List β)) : (loop g).inputs = [g.loopIn] := rfl @[simp] lemma loop_inputs (g : GGraph (Option β)) : (loop g).inputs = [g.loopIn] := rfl
@[simp] lemma loop_outputs (g : GGraph (List β)) : (loop g).outputs = [g.loopOut] := rfl @[simp] lemma loop_outputs (g : GGraph (Option β)) : (loop g).outputs = [g.loopOut] := rfl
/-- Creates a single-node graph whose node contains the given value. -/ /-- Creates a single-node graph whose node contains the given value. -/
def singleton (a : α) : GGraph α where def singleton (a : α) : GGraph α where
@@ -154,8 +163,24 @@ def singleton (a : α) : GGraph α where
/-- Creates a new graph with a single input and single output node. Useful to ensure there's /-- Creates a new graph with a single input and single output node. Useful to ensure there's
a single point of entry and single point of exit. -/ a single point of entry and single point of exit. -/
def wrap (g : GGraph (List β)) : GGraph (List β) := def wrap (g : GGraph (Option β)) : GGraph (Option β) :=
singleton [] g singleton [] singleton none g singleton none
/-- The input / entry node generated by `GGraph.wrap`. -/
def wrapInput (g : GGraph (Option β)) : (wrap g).Index :=
(0 : Fin 1).castAdd ((g singleton none).size)
/-- The output / exit node generated by `GGraph.wrap`. -/
def wrapOutput (g : GGraph (Option β)) : (wrap g).Index :=
Fin.natAdd 1 ((Fin.natAdd g.size (0 : Fin 1)))
/-- The `wrapInput` is, indeed, the graph's only input after `wrap`. -/
lemma wrap_inputs (g : GGraph (Option β)) :
(wrap g).inputs = [g.wrapInput] := rfl
/-- The `wrapInput` is, indeed, the graph's only output after `wrap`. -/
lemma wrap_outputs (g : GGraph (Option β)) :
(wrap g).outputs = [g.wrapOutput] := rfl
@[simp] lemma map_singleton (f : α β) (a : α) : @[simp] lemma map_singleton (f : α β) (a : α) :
f <$> singleton a = singleton (f a) := rfl f <$> singleton a = singleton (f a) := rfl
@@ -176,18 +201,77 @@ def wrap (g : GGraph (List β)) : GGraph (List β) :=
funext i funext i
refine Fin.addCases ?_ ?_ i <;> intro j <;> simp [Fin.append_left, Fin.append_right] refine Fin.addCases ?_ ?_ i <;> intro j <;> simp [Fin.append_left, Fin.append_right]
@[simp] lemma map_loop (h : β γ) (g : GGraph (List β)) : @[simp] lemma map_loop (h : β γ) (g : GGraph (Option β)) :
(List.map h) <$> (loop g) = loop (List.map h <$> g) := by (Option.map h) <$> (loop g) = loop (Option.map h <$> g) := by
rcases g with n, nd, e, i, o rcases g with n, nd, e, i, o
simp only [Functor.map, GGraph.loop] simp only [Functor.map, GGraph.loop]
congr 1 congr 1
funext i funext i
refine Fin.addCases ?_ ?_ i <;> intro j <;> simp [Fin.append_left, Fin.append_right] refine Fin.addCases ?_ ?_ i <;> intro j <;> simp [Fin.append_left, Fin.append_right]
@[simp] lemma map_wrap (h : β γ) (g : GGraph (List β)) : @[simp] lemma map_wrap (h : β γ) (g : GGraph (Option β)) :
(List.map h) <$> wrap g = wrap (List.map h <$> g) := by (Option.map h) <$> wrap g = wrap (Option.map h <$> g) := by
simp [GGraph.wrap, GGraph.map_sequence, GGraph.map_singleton] simp [GGraph.wrap, GGraph.map_sequence, GGraph.map_singleton]
/-! ### Embeddings
Each composition operator includes its operands into the result via an index
translation that preserves node payloads and edges. `Embed` captures exactly
those two facts, so anything defined from `nodes` and `edges` (traces, node
labels, …) can be transported along an embedding once, instead of once per
operator.
`Embed` is deliberately a structure rather than a class: for `g ⤳ g`, both the
left and the right inclusion inhabit the same type `Embed g (g ⤳ g)`, so
instance resolution could silently pick the wrong copy. Embeddings into a
composed graph are non-canonical by design; a named witness says which
inclusion is meant. -/
/-- An embedding of graph `g` into graph `h`: an index translation that
preserves node payloads and edges. -/
structure Embed (g h : GGraph α) where
f : g.Index h.Index
nodes_eq : i, h.nodes (f i) = g.nodes i
edges_mem : {e : g.Edge}, e g.edges (f e.1, f e.2) h.edges
/-- Embeddings compose. -/
def Embed.trans {g₁ g₂ g₃ : GGraph α} (e₁ : Embed g₁ g₂) (e₂ : Embed g₂ g₃) :
Embed g₁ g₃ where
f := e₂.f e₁.f
nodes_eq i := (e₂.nodes_eq (e₁.f i)).trans (e₁.nodes_eq i)
edges_mem he := e₂.edges_mem (e₁.edges_mem he)
/-- The left operand's inclusion into a sequenced graph. -/
def Embed.sequenceLeft (g₁ g₂ : GGraph α) : Embed g₁ (g₁ g₂) where
f i := i.castAdd g₂.size
nodes_eq i := Fin.append_left g₁.nodes g₂.nodes i
edges_mem he := List.mem_append_left _ (List.mem_append_left _ (List.mem_map_of_mem _ he))
/-- The right operand's inclusion into a sequenced graph. -/
def Embed.sequenceRight (g₁ g₂ : GGraph α) : Embed g₂ (g₁ g₂) where
f i := i.natAdd g₁.size
nodes_eq i := Fin.append_right g₁.nodes g₂.nodes i
edges_mem he := List.mem_append_left _ (List.mem_append_right _ (List.mem_map_of_mem _ he))
/-- The left operand's inclusion into an overlaid graph. -/
def Embed.overlayLeft (g₁ g₂ : GGraph α) : Embed g₁ (g₁ g₂) where
f i := i.castAdd g₂.size
nodes_eq i := Fin.append_left g₁.nodes g₂.nodes i
edges_mem he := List.mem_append_left _ (List.mem_map_of_mem _ he)
/-- The right operand's inclusion into an overlaid graph. -/
def Embed.overlayRight (g₁ g₂ : GGraph α) : Embed g₂ (g₁ g₂) where
f i := i.natAdd g₁.size
nodes_eq i := Fin.append_right g₁.nodes g₂.nodes i
edges_mem he := List.mem_append_right _ (List.mem_map_of_mem _ he)
/-- The body's inclusion into a `loop` graph. -/
def Embed.loop (g : GGraph (Option β)) : Embed g (loop g) where
f i := i.natAdd 2
nodes_eq i := Fin.append_right (fun _ : Fin 2 => none) g.nodes i
edges_mem he := List.mem_append_left _ (List.mem_append_left _
(List.mem_append_left _ (List.mem_map_of_mem _ he)))
variable (g : GGraph α) variable (g : GGraph α)
/-- All the nodes in the graph. -/ /-- All the nodes in the graph. -/
@@ -205,6 +289,35 @@ lemma nodup_indices : g.indices.Nodup :=
def predecessors (idx : g.Index) : List g.Index := def predecessors (idx : g.Index) : List g.Index :=
g.indices.filter (fun idx' => (idx', idx) g.edges) g.indices.filter (fun idx' => (idx', idx) g.edges)
/-- When sequencing (proven here with `Graph.singleton` on the left), no edges
exist from the right-hand graph back to the left. -/
private lemma not_mem_edges_castAdd_sequence {g₂ : GGraph (Option β)} (i : Fin 1)
(idx : (singleton none g₂).Index) :
((idx, i.castAdd g₂.size) : (singleton none g₂).Edge)
(singleton none g₂).edges := by
intro h
rcases List.mem_append.mp h with h' | h'
· rcases List.mem_append.mp h' with h'' | h''
· -- lifted edges of `singleton []`: there are none
simp [singleton, List.finCastAddProd] at h''
· -- lifted edges of g₂: targets are natAdd
obtain e, _, heq := List.mem_map.mp h''
exact Fin.castAdd_ne_natAdd i e.2 (congrArg Prod.snd heq).symm
· -- product edges: targets are natAdd'd inputs of g₂
obtain -, hb := List.mem_product.mp h'
obtain j, -, heq := List.mem_map.mp hb
exact Fin.castAdd_ne_natAdd i j heq.symm
/-- The input node of a graph after `Graph.wrap` has no predecessors. -/
lemma wrap_predecessors_eq_nil (g : GGraph (Option β)) (idx : (wrap g).Index)
(h : idx (wrap g).inputs) :
(wrap g).predecessors idx = [] := by
rw [wrap_inputs, List.mem_singleton] at h
subst h
rw [GGraph.predecessors, List.filter_eq_nil_iff]
intro idx' _
simpa using not_mem_edges_castAdd_sequence (g₂ := g singleton none) 0 idx'
/-- There's there's an edge between two nodes `idx₁` and `idx₂`, /-- There's there's an edge between two nodes `idx₁` and `idx₂`,
then `idx₁` is the predecessor of `idx₂`. -/ then `idx₁` is the predecessor of `idx₂`. -/
lemma mem_predecessors_of_edge {idx₁ idx₂ : g.Index} lemma mem_predecessors_of_edge {idx₁ idx₂ : g.Index}
@@ -220,12 +333,12 @@ lemma edge_of_mem_predecessors {idx₁ idx₂ : g.Index}
end GGraph end GGraph
/-- "Normal" graphs, for the purposes of the analyses in this /-- "Normal" graphs, for the purposes of the analyses in this
framework, have basic blocks in their nodes, and nothing else. -/ framework, have basic statements in their nodes, and nothing else. -/
abbrev Graph : Type := GGraph (List BasicStmt) abbrev Graph : Type := GGraph (Option BasicStmt)
namespace Graph namespace Graph
export GGraph (overlay sequence loop singleton wrap loop_inputs loop_outputs) export GGraph (overlay sequence loop singleton wrap loop_inputs loop_outputs wrapInput wrapOutput wrap_inputs wrap_outputs)
@[inherit_doc] scoped infixr:70 "" => GGraph.overlay @[inherit_doc] scoped infixr:70 "" => GGraph.overlay
@[inherit_doc] scoped infixr:70 "" => GGraph.sequence @[inherit_doc] scoped infixr:70 "" => GGraph.sequence
@@ -235,7 +348,7 @@ end Graph
open Graph in open Graph in
def Stmt.cfg : Stmt Graph def Stmt.cfg : Stmt Graph
-- A basic statement goes into a single basic block -- A basic statement goes into a single basic block
| .basic bs => singleton [bs] | .basic bs => singleton (some bs)
-- Sequencing of statements corresponds naturally to CFG sequencing -- Sequencing of statements corresponds naturally to CFG sequencing
| .andThen s₁ s₂ => s₁.cfg s₂.cfg | .andThen s₁ s₂ => s₁.cfg s₂.cfg
-- An if can execute either one branch or the other; overlap them. -- An if can execute either one branch or the other; overlap them.

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@@ -0,0 +1,77 @@
import Spa.Language.Base
import Spa.Language.Semantics
import Spa.Language.Graphs
import Mathlib.Data.Finset.Sort
import Mathlib.Data.String.Basic
namespace Spa
/-- A self-contained program to be evaluated, analyzed, and transformed. -/
structure Program where
/-- The statement at the top level of the program. Since `Spa.Stmt` contains
sequencing via `Spa.Stmt.andThen`, this can encode any number of
statements. -/
rootStmt : Stmt
/-- A memoized copy of the control-flow graph. This field is an
implementation detail to avoid re-computing `Spa.GGraph.wrap` and `Spa.Stmt.cfg`
every time the program's control flow graph is needed -/
cfgCache : Thunk Graph := Thunk.mk fun _ => Graph.wrap rootStmt.cfg
namespace Program
variable (p : Program)
-- Runtime implementation of `cfg`: read the memoized graph.
private def cfgImpl : Graph := p.cfgCache.get
/-- The control flow graph corresponding to this graph. -/
@[implemented_by cfgImpl]
def cfg : Graph := Graph.wrap p.rootStmt.cfg
/-- A state in the control flow `Spa.Graph` of this program. -/
abbrev State : Type := p.cfg.Index
/-- Variables mentioned or defined in this program. -/
def vars : List String := p.rootStmt.vars.sort (· ·)
/-- `vars` has no duplicates. -/
lemma vars_nodup : p.vars.Nodup := Finset.sort_nodup _ _
/-- All the states in the program's control flow `Spa.Graph`. -/
def states : List p.State := p.cfg.indices
/-- All states in the CFG are contained in `states`. -/
lemma states_complete (s : p.State) : s p.states := p.cfg.mem_indices s
/-- `states` has no duplicates. -/
lemma states_nodup : p.states.Nodup := p.cfg.nodup_indices
/-- Given a node of the program's CFG, return the code at that node.
At this time, for convenience of proofs, the CFGs have at most
one basic statement, and multi-statement basic blocks are encoded
as chains of blocks. Thus, this returns at most one `Spa.BasicStmt`. -/
@[reducible]
def code (st : p.State) : Option BasicStmt := p.cfg.nodes st
/-- Get the predecessors of a particular CFG node / program state. -/
def incoming (s : p.State) : List p.State := p.cfg.predecessors s
/-- The entry point of the program's CFG. -/
def initialState : p.State := Graph.wrapInput p.rootStmt.cfg
/-- The exit point of the program's CFG. -/
def finalState : p.State := Graph.wrapOutput p.rootStmt.cfg
/-- `incoming` is a faithful representation of edges in the CFG. -/
lemma mem_incoming_of_edge {s₁ s₂ : p.State}
(h : (s₁, s₂) p.cfg.edges) : s₁ p.incoming s₂ :=
p.cfg.mem_predecessors_of_edge h
/-- The `initialState` has no incoming edges (it's the program start). -/
lemma incoming_initialState_eq_nil : p.incoming p.initialState = [] :=
GGraph.wrap_predecessors_eq_nil p.rootStmt.cfg p.initialState
(by rw [Graph.wrap_inputs]; exact List.mem_singleton_self _)
end Program
end Spa

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@@ -1,126 +1,126 @@
import Spa.Language.Traces import Spa.Language.Traces
/-!
# Properties of the Object Language, CFGs, and Traces
This module encodes some properties of the language, mostly those having to do
with connecting the computational view (the `Spa.Graph`s, on which static
analyses are executed) to the semantic view (such as `EvalStmt`, which
encodes the expected formal behavior of the language). In particular,
to prove that our computationally-implemented static analyses are correct,
we need to show that our computational model of their execution (the CFG)
matches the formal description. Thus, the key result `cfg_sufficient`.
Many lemmas and definitions here aim are used to prove that result,
by allowing inductive proofs on the construction of the CFG:
the bits where we _build up_ the trace corresponding to each
proof tree are exactly those when we have two graphs (through
which traces exist) and we want to combine these graphs, while
showing also that a combined trace exists as well. -/
namespace Spa namespace Spa
open Graph open Graph
lemma Fin.castAdd_ne_natAdd {n m : } (i : Fin n) (j : Fin m) :
Fin.castAdd m i Fin.natAdd n j := by
intro h
have := congrArg Fin.val h
simp only [Fin.coe_castAdd, Fin.coe_natAdd] at this
omega
/-! ### Trace embeddings -/
section Embeddings section Embeddings
variable {g₁ g₂ : Graph} {ρ₁ ρ₂ : Env} variable {g₁ g₂ : Graph} {ρ₁ ρ₂ : Env}
lemma Trace.overlay_left {idx₁ idx₂ : g₁.Index} /-- Transport a trace along a graph embedding: an embedding preserves node
payloads and edges, which is everything a trace is made of. This is the
single induction behind all the per-operator lifting corollaries below. -/
noncomputable def Trace.embed {g h : Graph} (e : GGraph.Embed g h)
{idx₁ idx₂ : g.Index} (tr : Trace g idx₁ idx₂ ρ₁ ρ₂) :
Trace h (e.f idx₁) (e.f idx₂) ρ₁ ρ₂ := by
induction tr with
| single hbs => exact Trace.single (by rwa [e.nodes_eq])
| edge hbs he _ ih => exact Trace.edge (by rwa [e.nodes_eq]) (e.edges_mem he) ih
/-- When two graphs are overlaid, for each trace in the left graph,
a corresponding trace exists in the combined graph. -/
noncomputable def Trace.overlay_left {idx₁ idx₂ : g₁.Index}
(tr : Trace g₁ idx₁ idx₂ ρ₁ ρ₂) : (tr : Trace g₁ idx₁ idx₂ ρ₁ ρ₂) :
Trace (g₁ g₂) (idx₁.castAdd g₂.size) (idx₂.castAdd g₂.size) ρ₁ ρ₂ := by Trace (g₁ g₂) (idx₁.castAdd g₂.size) (idx₂.castAdd g₂.size) ρ₁ ρ₂ :=
induction tr with tr.embed (GGraph.Embed.overlayLeft g₁ g₂)
| single hbs =>
exact Trace.single (by rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl,
Fin.append_left])
| edge hbs he _ ih =>
refine Trace.edge ?_ ?_ ih
· rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl, Fin.append_left]
· exact List.mem_append_left _ (List.mem_map_of_mem _ he)
lemma Trace.overlay_right {idx₁ idx₂ : g₂.Index} /-- When two graphs are overlaid, for each trace in the right graph,
a corresponding trace exists in the combined graph. -/
noncomputable def Trace.overlay_right {idx₁ idx₂ : g₂.Index}
(tr : Trace g₂ idx₁ idx₂ ρ₁ ρ₂) : (tr : Trace g₂ idx₁ idx₂ ρ₁ ρ₂) :
Trace (g₁ g₂) (idx₁.natAdd g₁.size) (idx₂.natAdd g₁.size) ρ₁ ρ₂ := by Trace (g₁ g₂) (idx₁.natAdd g₁.size) (idx₂.natAdd g₁.size) ρ₁ ρ₂ :=
induction tr with tr.embed (GGraph.Embed.overlayRight g₁ g₂)
| single hbs =>
exact Trace.single (by rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl,
Fin.append_right])
| edge hbs he _ ih =>
refine Trace.edge ?_ ?_ ih
· rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl, Fin.append_right]
· exact List.mem_append_right _ (List.mem_map_of_mem _ he)
lemma Trace.sequence_left {idx₁ idx₂ : g₁.Index} /-- When two graphs are sequenced, for each trace in the first graph,
a corresponding trace exists in the combined graph. -/
noncomputable def Trace.sequence_left {idx₁ idx₂ : g₁.Index}
(tr : Trace g₁ idx₁ idx₂ ρ₁ ρ₂) : (tr : Trace g₁ idx₁ idx₂ ρ₁ ρ₂) :
Trace (g₁ g₂) (idx₁.castAdd g₂.size) (idx₂.castAdd g₂.size) ρ₁ ρ₂ := by Trace (g₁ g₂) (idx₁.castAdd g₂.size) (idx₂.castAdd g₂.size) ρ₁ ρ₂ :=
induction tr with tr.embed (GGraph.Embed.sequenceLeft g₁ g₂)
| single hbs =>
exact Trace.single (by rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl,
Fin.append_left])
| edge hbs he _ ih =>
refine Trace.edge ?_ ?_ ih
· rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl, Fin.append_left]
· exact List.mem_append_left _ (List.mem_append_left _ (List.mem_map_of_mem _ he))
lemma Trace.sequence_right {idx₁ idx₂ : g₂.Index} /-- When two graphs are sequenced, for each trace in the second graph,
a corresponding trace exists in the combined graph. -/
noncomputable def Trace.sequence_right {idx₁ idx₂ : g₂.Index}
(tr : Trace g₂ idx₁ idx₂ ρ₁ ρ₂) : (tr : Trace g₂ idx₁ idx₂ ρ₁ ρ₂) :
Trace (g₁ g₂) (idx₁.natAdd g₁.size) (idx₂.natAdd g₁.size) ρ₁ ρ₂ := by Trace (g₁ g₂) (idx₁.natAdd g₁.size) (idx₂.natAdd g₁.size) ρ₁ ρ₂ :=
induction tr with tr.embed (GGraph.Embed.sequenceRight g₁ g₂)
| single hbs =>
exact Trace.single (by rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl,
Fin.append_right])
| edge hbs he _ ih =>
refine Trace.edge ?_ ?_ ih
· rwa [show (g₁ g₂).nodes = Fin.append g₁.nodes g₂.nodes from rfl, Fin.append_right]
· exact List.mem_append_left _
(List.mem_append_right _ (List.mem_map_of_mem _ he))
lemma EndToEndTrace.overlay_left (etr : EndToEndTrace g₁ ρ₁ ρ₂) : /-- Equivalent of `Trace.overlay_left` for end-to-end traces. -/
noncomputable def EndToEndTrace.overlay_left (etr : EndToEndTrace g₁ ρ₁ ρ₂) :
EndToEndTrace (g₁ g₂) ρ₁ ρ₂ := by EndToEndTrace (g₁ g₂) ρ₁ ρ₂ := by
obtain i₁, h₁, i₂, h₂, tr := etr obtain i₁, h₁, i₂, h₂, tr := etr
exact i₁.castAdd g₂.size, List.mem_append_left _ (List.mem_map_of_mem _ h₁), exact i₁.castAdd g₂.size, List.mem_append_left _ (List.mem_map_of_mem _ h₁),
i₂.castAdd g₂.size, List.mem_append_left _ (List.mem_map_of_mem _ h₂), i₂.castAdd g₂.size, List.mem_append_left _ (List.mem_map_of_mem _ h₂),
tr.overlay_left tr.overlay_left
lemma EndToEndTrace.overlay_right (etr : EndToEndTrace g₂ ρ₁ ρ₂) : /-- Equivalent of `Trace.overlay_right` for end-to-end traces. -/
noncomputable def EndToEndTrace.overlay_right (etr : EndToEndTrace g₂ ρ₁ ρ₂) :
EndToEndTrace (g₁ g₂) ρ₁ ρ₂ := by EndToEndTrace (g₁ g₂) ρ₁ ρ₂ := by
obtain i₁, h₁, i₂, h₂, tr := etr obtain i₁, h₁, i₂, h₂, tr := etr
exact i₁.natAdd g₁.size, List.mem_append_right _ (List.mem_map_of_mem _ h₁), exact i₁.natAdd g₁.size, List.mem_append_right _ (List.mem_map_of_mem _ h₁),
i₂.natAdd g₁.size, List.mem_append_right _ (List.mem_map_of_mem _ h₂), i₂.natAdd g₁.size, List.mem_append_right _ (List.mem_map_of_mem _ h₂),
tr.overlay_right tr.overlay_right
lemma EndToEndTrace.concat {ρ₃ : Env} (etr₁ : EndToEndTrace g₁ ρ₁ ρ₂) /-- When two graphs are sequenced, two end-to-end traces through the respective
graphs can be sequenced to create an end-to-end trace in the combined
graph. This is only possible for end-to-end traces and not for general
`Trace`s, because sequencing only introduces edges from the output nodes
of one graph to the input nodes of another graph. A non-end-to-end trace
need to conclude at the output node, so it cannot necessarily be sequenced
with a trace in another graph. -/
noncomputable def EndToEndTrace.concat {ρ₃ : Env} (etr₁ : EndToEndTrace g₁ ρ₁ ρ₂)
(etr₂ : EndToEndTrace g₂ ρ₂ ρ₃) : EndToEndTrace (g₁ g₂) ρ₁ ρ₃ := by (etr₂ : EndToEndTrace g₂ ρ₂ ρ₃) : EndToEndTrace (g₁ g₂) ρ₁ ρ₃ := by
obtain i₁, h₁, i₂, h₂, tr₁ := etr₁ obtain i₁, h₁, i₂, h₂, tr₁ := etr₁
obtain j₁, k₁, j₂, k₂, tr₂ := etr₂ obtain j₁, k₁, j₂, k₂, tr₂ := etr₂
refine i₁.castAdd g₂.size, List.mem_map_of_mem _ h₁, refine i₁.castAdd g₂.size, List.mem_map_of_mem _ h₁,
j₂.natAdd g₁.size, List.mem_map_of_mem _ k₂, j₂.natAdd g₁.size, List.mem_map_of_mem _ k₂,
Trace.concat tr₁.sequence_left ?_ tr₂.sequence_right tr₁.sequence_left ++< ?_ >++ tr₂.sequence_right
exact List.mem_append_right _ exact List.mem_append_right _
(List.mem_product.mpr List.mem_map_of_mem _ h₂, List.mem_map_of_mem _ k₁) (List.mem_product.mpr List.mem_map_of_mem _ h₂, List.mem_map_of_mem _ k₁)
end Embeddings end Embeddings
/-! ### Loops -/
section Loop section Loop
variable {g : Graph} {ρ₁ ρ₂ ρ₃ : Env} variable {g : Graph} {ρ₁ ρ₂ ρ₃ : Env}
lemma Trace.loop {idx₁ idx₂ : g.Index} (tr : Trace g idx₁ idx₂ ρ₁ ρ₂) : /-- A trace through a body CFG still exists (up to reindexing) in a zero-or-more loop CFG. -/
Trace (Graph.loop g) (idx.natAdd 2) (idx₂.natAdd 2) ρ₁ ρ₂ := by noncomputable def Trace.loop {idx₁ idx : g.Index} (tr : Trace g idx₁ idx₂ ρ₁ ρ₂) :
induction tr with Trace (Graph.loop g) (idx₁.natAdd 2) (idx₂.natAdd 2) ρ₁ ρ₂ :=
| single hbs => tr.embed (GGraph.Embed.loop g)
exact Trace.single (by
rwa [show (Graph.loop g).nodes = Fin.append (fun _ : Fin 2 => []) g.nodes from rfl,
Fin.append_right])
| edge hbs he _ ih =>
refine Trace.edge ?_ ?_ ih
· rwa [show (Graph.loop g).nodes = Fin.append (fun _ : Fin 2 => []) g.nodes from rfl,
Fin.append_right]
· exact List.mem_append_left _ (List.mem_append_left _
(List.mem_append_left _ (List.mem_map_of_mem _ he)))
/-- The beginning node of a loop graph is empty. -/
private lemma loop_nodes_at_in : private lemma loop_nodes_at_in :
(Graph.loop g).nodes g.loopIn = [] := (Graph.loop g).nodes g.loopIn = none :=
Fin.append_left (fun _ : Fin 2 => []) g.nodes 0 Fin.append_left (fun _ : Fin 2 => none) g.nodes 0
/-- The ending node of a loop graph is empty. -/
private lemma loop_nodes_at_out : private lemma loop_nodes_at_out :
(Graph.loop g).nodes g.loopOut = [] := (Graph.loop g).nodes g.loopOut = none :=
Fin.append_left (fun _ : Fin 2 => []) g.nodes 1 Fin.append_left (fun _ : Fin 2 => none) g.nodes 1
lemma EndToEndTrace.loop (etr : EndToEndTrace g ρ₁ ρ₂) : /-- Equivlaent of `Trace.loop` for end-to-end traces. -/
noncomputable def EndToEndTrace.loop (etr : EndToEndTrace g ρ₁ ρ₂) :
EndToEndTrace (Graph.loop g) ρ₁ ρ₂ := by EndToEndTrace (Graph.loop g) ρ₁ ρ₂ := by
obtain i₁, h₁, i₂, h₂, tr := etr obtain i₁, h₁, i₂, h₂, tr := etr
-- the edge in → (2 ↑ʳ i₁), reached through the second edge group -- the edge in → (2 ↑ʳ i₁), reached through the second edge group
@@ -132,15 +132,17 @@ lemma EndToEndTrace.loop (etr : EndToEndTrace g ρ₁ ρ₂) :
refine List.mem_append_left _ (List.mem_append_right _ ?_) refine List.mem_append_left _ (List.mem_append_right _ ?_)
exact List.mem_map_of_mem _ (List.mem_map_of_mem _ h₂) exact List.mem_map_of_mem _ (List.mem_map_of_mem _ h₂)
refine g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _, ?_ refine g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _, ?_
exact Trace.concat (Trace.single (loop_nodes_at_in EvalBasicStmts.nil)) hin exact Trace.single (loop_nodes_at_in EvalBasicStmtOpt.none) ++< hin >++
(Trace.concat tr.loop hout (Trace.single (loop_nodes_at_out EvalBasicStmts.nil))) tr.loop ++< hout >++ Trace.single (loop_nodes_at_out EvalBasicStmtOpt.none)
/-- The zero-or-more times loop has an edge to return back to the top, to continue after an iteration. -/
private lemma loop_edge_out_in : private lemma loop_edge_out_in :
((g.loopOut, g.loopIn) : (Graph.loop g).Edge) (Graph.loop g).edges := by ((g.loopOut, g.loopIn) : (Graph.loop g).Edge) (Graph.loop g).edges := by
refine List.mem_append_right _ ?_ refine List.mem_append_right _ ?_
exact List.mem_cons_self _ _ exact List.mem_cons_self _ _
lemma EndToEndTrace.loop_concat (etr₁ : EndToEndTrace (Graph.loop g) ρ₁ ρ₂) /-- Two traces through a loop can be combined, since a loop can be executed any number of times. -/
noncomputable def EndToEndTrace.loop_concat (etr₁ : EndToEndTrace (Graph.loop g) ρ₁ ρ₂)
(etr₂ : EndToEndTrace (Graph.loop g) ρ₂ ρ₃) : (etr₂ : EndToEndTrace (Graph.loop g) ρ₂ ρ₃) :
EndToEndTrace (Graph.loop g) ρ₁ ρ₃ := by EndToEndTrace (Graph.loop g) ρ₁ ρ₃ := by
obtain i₁, h₁, i₂, h₂, tr₁ := etr₁ obtain i₁, h₁, i₂, h₂, tr₁ := etr₁
@@ -148,37 +150,55 @@ lemma EndToEndTrace.loop_concat (etr₁ : EndToEndTrace (Graph.loop g) ρ₁ ρ
simp only [Graph.loop_inputs, Graph.loop_outputs, List.mem_singleton] at h₁ h₂ k₁ k₂ simp only [Graph.loop_inputs, Graph.loop_outputs, List.mem_singleton] at h₁ h₂ k₁ k₂
subst h₁; subst h₂; subst k₁; subst k₂ subst h₁; subst h₂; subst k₁; subst k₂
exact g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _, exact g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _,
Trace.concat tr₁ loop_edge_out_in tr₂ tr₁ ++< loop_edge_out_in >++ tr₂
lemma EndToEndTrace.loop_empty {ρ : Env} : EndToEndTrace (Graph.loop g) ρ ρ := by /-- A loop can be executed zero times. -/
noncomputable def EndToEndTrace.loop_empty {ρ : Env} : EndToEndTrace (Graph.loop g) ρ ρ := by
have hedge : ((g.loopIn, g.loopOut) : (Graph.loop g).Edge) (Graph.loop g).edges := have hedge : ((g.loopIn, g.loopOut) : (Graph.loop g).Edge) (Graph.loop g).edges :=
List.mem_append_right _ (List.mem_cons_of_mem _ (List.mem_cons_self _ _)) List.mem_append_right _ (List.mem_cons_of_mem _ (List.mem_cons_self _ _))
exact g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _, exact g.loopIn, List.mem_singleton_self _, g.loopOut, List.mem_singleton_self _,
Trace.concat (Trace.single (loop_nodes_at_in EvalBasicStmts.nil)) hedge Trace.single (loop_nodes_at_in EvalBasicStmtOpt.none) ++< hedge >++
(Trace.single (loop_nodes_at_out EvalBasicStmts.nil)) Trace.single (loop_nodes_at_out EvalBasicStmtOpt.none)
end Loop end Loop
/-! ### Singletons, wrap, and the main result -/ /-- A CFG consisting of only a single node has a trace through it corresponding to that node. -/
noncomputable def EndToEndTrace.singleton {o : Option BasicStmt} {ρ₁ ρ₂ : Env}
lemma EndToEndTrace.singleton {bss : List BasicStmt} {ρ₁ ρ₂ : Env} (h : EvalBasicStmtOpt ρ₁ o ρ₂) : EndToEndTrace (Graph.singleton o) ρ₁ ρ₂ :=
(h : EvalBasicStmts ρ₁ bss ρ₂) : EndToEndTrace (Graph.singleton bss) ρ₁ ρ₂ :=
(0 : Fin 1), List.mem_singleton_self _, (0 : Fin 1), List.mem_singleton_self _, (0 : Fin 1), List.mem_singleton_self _, (0 : Fin 1), List.mem_singleton_self _,
Trace.single h Trace.single h
lemma EndToEndTrace.singleton_nil (ρ : Env) : /-- If a CFG's only node is empty, the no-op trace exists through it. -/
EndToEndTrace (Graph.singleton []) ρ ρ := noncomputable def EndToEndTrace.singleton_nil (ρ : Env) :
EndToEndTrace.singleton EvalBasicStmts.nil EndToEndTrace (Graph.singleton none) ρ ρ :=
EndToEndTrace.singleton EvalBasicStmtOpt.none
lemma EndToEndTrace.wrap {g : Graph} {ρ₁ ρ₂ : Env} /-- Invoking 'Graph.wrap` (which ensures a single entry and exit node for a CFG)
does not invalidate traces in the original graph. -/
noncomputable def EndToEndTrace.wrap {g : Graph} {ρ₁ ρ₂ : Env}
(etr : EndToEndTrace g ρ₁ ρ₂) : EndToEndTrace (Graph.wrap g) ρ₁ ρ₂ := (etr : EndToEndTrace g ρ₁ ρ₂) : EndToEndTrace (Graph.wrap g) ρ₁ ρ₂ :=
(EndToEndTrace.singleton_nil ρ₁).concat (etr.concat (EndToEndTrace.singleton_nil ρ₂)) (EndToEndTrace.singleton_nil ρ₁).concat (etr.concat (EndToEndTrace.singleton_nil ρ₂))
theorem Stmt.cfg_sufficient {s : Stmt} {ρ₁ ρ₂ : Env} /-- Key result: the control flow graph admits every execution that's made
possible by a language's semantics. Thus, the CFG encodes _at least_ all
semantically-possible executions. Informally, we can conclude from this
that if we compute a result that using the graph's edges to determine
what's possible, this result will not disagree with the semantics.
Note that a CFG like $K_4$ (where the nodes are basic blocks) is
technically also a sufficient graph, but is very likely meaningless in that
it grossly overestimates the possible execution paths in the language, and
thus is bound to produce less-than-specific results. There is as yet no
result in this framework that the CFG we produce is _minimal_: loosely,
posessing only edges for things that are admitted by the semantics.
This is difficult to state (in its strongest form, this would
require the CFG to be able to detect something like `while (alwaysFalse)`,
and so remains a TODO. -/
noncomputable def Stmt.cfg_sufficient {s : Stmt} {ρ₁ ρ₂ : Env}
(h : EvalStmt ρ₁ s ρ₂) : EndToEndTrace s.cfg ρ₁ ρ₂ := by (h : EvalStmt ρ₁ s ρ₂) : EndToEndTrace s.cfg ρ₁ ρ₂ := by
induction h with induction h with
| basic ρ₁ ρ₂ bs hbs => | basic ρ₁ ρ₂ bs hbs =>
exact EndToEndTrace.singleton (EvalBasicStmts.cons hbs EvalBasicStmts.nil) exact EndToEndTrace.singleton (EvalBasicStmtOpt.some hbs)
| andThen ρ₁ ρ₂ ρ₃ s₁ s₂ _ _ ih₁ ih₂ => | andThen ρ₁ ρ₂ ρ₃ s₁ s₂ _ _ ih₁ ih₂ =>
exact ih₁.concat ih₂ exact ih₁.concat ih₂
| ifTrue ρ₁ ρ₂ e z s₁ s₂ _ _ _ ih => | ifTrue ρ₁ ρ₂ e z s₁ s₂ _ _ _ ih =>
@@ -190,44 +210,17 @@ theorem Stmt.cfg_sufficient {s : Stmt} {ρ₁ ρ₂ : Env}
| whileFalse ρ e s _ => | whileFalse ρ e s _ =>
exact EndToEndTrace.loop_empty exact EndToEndTrace.loop_empty
/-! ### The wrapped graph's entry has no predecessors (Agda's "ugly" block) -/ namespace Program
def Graph.wrapInput (g : Graph) : (Graph.wrap g).Index := noncomputable def trace (p : Program) {ρ : Env} (h : EvalStmt [] p.rootStmt ρ) :
(0 : Fin 1).castAdd ((g Graph.singleton []).size) Trace p.cfg p.initialState p.finalState [] ρ := by
obtain i₁, h₁, i₂, h₂, tr := EndToEndTrace.wrap (Stmt.cfg_sufficient h)
rw [Graph.wrap_inputs, List.mem_singleton] at h₁
rw [Graph.wrap_outputs, List.mem_singleton] at h₂
subst h₁; subst h₂
exact tr
def Graph.wrapOutput (g : Graph) : (Graph.wrap g).Index := end Program
Fin.natAdd 1 ((Fin.natAdd g.size (0 : Fin 1)))
lemma Graph.wrap_inputs (g : Graph) :
(Graph.wrap g).inputs = [g.wrapInput] := rfl
lemma Graph.wrap_outputs (g : Graph) :
(Graph.wrap g).outputs = [g.wrapOutput] := rfl
private lemma not_mem_edges_castAdd_sequence {g₂ : Graph} (i : Fin 1)
(idx : (Graph.singleton [] g₂).Index) :
((idx, i.castAdd g₂.size) : (Graph.singleton [] g₂).Edge)
(Graph.singleton [] g₂).edges := by
intro h
rcases List.mem_append.mp h with h' | h'
· rcases List.mem_append.mp h' with h'' | h''
· -- lifted edges of `singleton []`: there are none
simp [Graph.singleton, List.finCastAddProd] at h''
· -- lifted edges of g₂: targets are natAdd
obtain e, _, heq := List.mem_map.mp h''
exact Fin.castAdd_ne_natAdd i e.2 (congrArg Prod.snd heq).symm
· -- product edges: targets are natAdd'd inputs of g₂
obtain -, hb := List.mem_product.mp h'
obtain j, -, heq := List.mem_map.mp hb
exact Fin.castAdd_ne_natAdd i j heq.symm
lemma Graph.wrap_predecessors_eq_nil (g : Graph) (idx : (Graph.wrap g).Index)
(h : idx (Graph.wrap g).inputs) :
(Graph.wrap g).predecessors idx = [] := by
rw [Graph.wrap_inputs, List.mem_singleton] at h
subst h
rw [GGraph.predecessors, List.filter_eq_nil_iff]
intro idx' _
simpa using not_mem_edges_castAdd_sequence (g₂ := g Graph.singleton []) 0 idx'
end Spa end Spa

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@@ -46,22 +46,22 @@ inductive EvalExpr : Env → Expr → Value → Prop
/-- Inference rules for evaluating a basic statement (`Spa.BasicStmt`) in /-- Inference rules for evaluating a basic statement (`Spa.BasicStmt`) in
a given environment, potentially changing the environment. a given environment, potentially changing the environment.
Pretty standard big-step evaluation. -/ Pretty standard big-step evaluation. -/
inductive EvalBasicStmt : Env BasicStmt Env Prop inductive EvalBasicStmt : Env BasicStmt Env Type
| noop (ρ : Env) : EvalBasicStmt ρ .noop ρ | noop (ρ : Env) : EvalBasicStmt ρ .noop ρ
| assign (ρ : Env) (x : String) (e : Expr) (v : Value) : | assign (ρ : Env) (x : String) (e : Expr) (v : Value) :
EvalExpr ρ e v EvalBasicStmt ρ (.assign x e) ((x, v) :: ρ) EvalExpr ρ e v EvalBasicStmt ρ (.assign x e) ((x, v) :: ρ)
/-- Inference rules for evaluating a sequence of basic statements. -/ /-- Inference rules for evaluating a basic-statement-or-nothing,
inductive EvalBasicStmts : Env List BasicStmt Env Prop which is the current representation of CFGs nodes. -/
| nil {ρ : Env} : EvalBasicStmts ρ [] ρ inductive EvalBasicStmtOpt : Env Option BasicStmt Env Type
| cons {ρ ρ₂ ρ₃ : Env} {bs : BasicStmt} {bss : List BasicStmt} : | none {ρ : Env} : EvalBasicStmtOpt ρ Option.none ρ
EvalBasicStmt ρ₁ bs ρ₂ EvalBasicStmts ρ₂ bss ρ₃ | some {ρ₁ ρ₂ : Env} {bs : BasicStmt} :
EvalBasicStmts ρ₁ (bs :: bss) ρ EvalBasicStmt ρ₁ bs ρ₂ EvalBasicStmtOpt ρ₁ (Option.some bs) ρ
/-- Inference rules for evaluating statements (`Spa.Stmt`) in a given /-- Inference rules for evaluating statements (`Spa.Stmt`) in a given
environment, potentially changing the environment. environment, potentially changing the environment.
Pretty standard big-step evaluation. -/ Pretty standard big-step evaluation. -/
inductive EvalStmt : Env Stmt Env Prop inductive EvalStmt : Env Stmt Env Type
| basic (ρ₁ ρ₂ : Env) (bs : BasicStmt) : | basic (ρ₁ ρ₂ : Env) (bs : BasicStmt) :
EvalBasicStmt ρ₁ bs ρ₂ EvalStmt ρ₁ (.basic bs) ρ₂ EvalBasicStmt ρ₁ bs ρ₂ EvalStmt ρ₁ (.basic bs) ρ₂
| andThen (ρ₁ ρ₂ ρ₃ : Env) (s₁ s₂ : Stmt) : | andThen (ρ₁ ρ₂ ρ₃ : Env) (s₁ s₂ : Stmt) :

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@@ -0,0 +1,18 @@
import Spa.Language.Base
import Spa.Language.Tagged.Id
import Spa.Language.Tagged.Derive
derive_tagged Spa.Expr Spa.BasicStmt Spa.Stmt
namespace Spa
def tagStmt (s : Stmt) : Stmt.Tagged RawId := (s.tag 0).1
def Stmt.Tagged.subtreeIds {τ : Type} (s : Stmt.Tagged τ) : List τ :=
s.foldTags (· :: ·) []
def Stmt.Tagged.isInLoopBody {τ : Type} [DecidableEq τ]
(body : Stmt.Tagged τ) (id : τ) : Bool :=
decide (id body.subtreeIds)
end Spa

View File

@@ -0,0 +1,417 @@
# Descendant tracking (parked)
This is the formally-verified **interval-labeling / descendant** machinery that
used to live in `Id.lean` and `Properties.lean`. It let you decide "is node `a`
a descendant of node `b`?" with two integer comparisons on their identifiers,
and *proved* that numeric test equivalent to structural subtree containment.
It was removed because the descendant test is a *computational optimization*:
the same question can be answered by walking the AST, and nothing in the current
pipeline needs the fast test yet. The proofs (a rose-tree flattening + a
postorder `Good` invariant) are a real mechanization cost to carry. Parked here
so it can be restored verbatim when LICM actually wants it.
## What stays in the live code
- `NodeId` collapses to a single unique index (`{ post : }`); `tag` still
assigns each node a distinct postorder number.
- The bidirectional mapping (`erase`/`tag` + `erase_tagStmt`) stays in
`Properties.lean`.
- The labelled-CFG id↔state mapping (`Cfg.lean`) is independent of this and is
unaffected.
## Revival checklist
1. In `Id.lean`, give `NodeId` back its descendant-count field and the test:
```lean
structure NodeId where
post :
desc : -- number of proper descendants (subtree size 1); leaf = 0
deriving DecidableEq, Repr
namespace NodeId
/-- Left endpoint of the node's postorder interval `[lo, post]`. -/
def lo (a : NodeId) : := a.post - a.desc
/-- `a` is a descendant-or-self of `b`: `a.post` lies in `b`'s interval. -/
def DescendantOf (a b : NodeId) : Prop := b.lo ≤ a.post ∧ a.post ≤ b.post
instance (a b : NodeId) : Decidable (DescendantOf a b) := by
unfold DescendantOf; infer_instance
end NodeId
```
2. In `Derive.lean`, make the generated `tag` store the descendant count again:
change the emitted identifier in `mkTag` from `(⟨$last⟩ : $nId)` back to
`(⟨$last, $last - n⟩ : $nId)`.
3. Paste the Lean block below back into `Properties.lean` (after the round-trip
theorems). It builds against the `id.lo = lo`-premise form of `Good` and the
childcount (`desc`) identifier. The headline result is
`descendant_iff_tagStmt`; everything else is supporting machinery.
## The parked proofs
```lean
/-- A rose tree of identifiers: the uniform shape underlying all three tagged
AST types, used to reason about the postorder labeling generically. -/
inductive IdTree where
| node (id : NodeId) (children : List IdTree)
namespace IdTree
def rootId : IdTree → NodeId
| .node id _ => id
@[simp] theorem rootId_node (id : NodeId) (cs : List IdTree) :
(IdTree.node id cs).rootId = id := rfl
mutual
def subtrees : IdTree → List IdTree
| .node id cs => .node id cs :: subtreesList cs
def subtreesList : List IdTree → List IdTree
| [] => []
| c :: cs => subtrees c ++ subtreesList cs
end
@[simp] theorem subtrees_node (id : NodeId) (cs : List IdTree) :
subtrees (.node id cs) = .node id cs :: subtreesList cs := rfl
@[simp] theorem subtreesList_nil : subtreesList [] = [] := rfl
@[simp] theorem subtreesList_cons (c : IdTree) (cs : List IdTree) :
subtreesList (c :: cs) = subtrees c ++ subtreesList cs := rfl
def posts (t : IdTree) : List := (subtrees t).map (fun s => s.rootId.post)
def postsList (cs : List IdTree) : List := (subtreesList cs).map (fun s => s.rootId.post)
@[simp] theorem posts_node (id : NodeId) (cs : List IdTree) :
posts (.node id cs) = id.post :: postsList cs := rfl
@[simp] theorem postsList_nil : postsList [] = [] := rfl
@[simp] theorem postsList_cons (c : IdTree) (cs : List IdTree) :
postsList (c :: cs) = posts c ++ postsList cs := by
simp [posts, postsList]
end IdTree
def Expr.Tagged.toIdTree : Expr.Tagged NodeId → IdTree
| .add t a b => .node t [a.toIdTree, b.toIdTree]
| .sub t a b => .node t [a.toIdTree, b.toIdTree]
| .var t _ => .node t []
| .num t _ => .node t []
def BasicStmt.Tagged.toIdTree : BasicStmt.Tagged NodeId → IdTree
| .assign t _ e => .node t [e.toIdTree]
| .noop t => .node t []
def Stmt.Tagged.toIdTree : Stmt.Tagged NodeId → IdTree
| .basic t bs => .node t [bs.toIdTree]
| .andThen t a b => .node t [a.toIdTree, b.toIdTree]
| .ifElse t e a b => .node t [e.toIdTree, a.toIdTree, b.toIdTree]
| .whileLoop t e s => .node t [e.toIdTree, s.toIdTree]
mutual
inductive Good : → IdTree → Prop
| mk {lo : } {id : NodeId} {cs : List IdTree} :
id.lo = lo → GoodChildren lo cs id.post →
Good lo (.node id cs)
inductive GoodChildren : → List IdTree → → Prop
| nil {pos : } : GoodChildren pos [] pos
| cons {cur : } {c : IdTree} {cs : List IdTree} {pos : } :
Good cur c → GoodChildren (c.rootId.post + 1) cs pos →
GoodChildren cur (c :: cs) pos
end
theorem Good.lo_le_post {lo : } {t : IdTree} (h : Good lo t) : lo ≤ t.rootId.post := by
cases h with
| mk hlo _ => simp only [NodeId.lo] at hlo; simp only [IdTree.rootId_node]; omega
theorem GoodChildren.cur_le_pos : ∀ {cur : } (cs : List IdTree) {pos : },
GoodChildren cur cs pos → cur ≤ pos
| _, [], _, h => by cases h; exact le_rfl
| _, c :: cs, _, h => by
cases h with
| cons hc hcs =>
have := hc.lo_le_post
have := GoodChildren.cur_le_pos cs hcs
omega
mutual
theorem Good.mem_posts : ∀ {lo : } (t : IdTree), Good lo t →
∀ x, x ∈ IdTree.posts t ↔ lo ≤ x ∧ x ≤ t.rootId.post
| _, .node id cs, h, x => by
cases h with
| mk hlo hch =>
simp only [IdTree.posts_node, List.mem_cons, IdTree.rootId_node]
rw [GoodChildren.mem_postsList cs hch x]
simp only [NodeId.lo] at hlo
omega
theorem GoodChildren.mem_postsList : ∀ {cur : } (cs : List IdTree) {pos : },
GoodChildren cur cs pos → ∀ x, x ∈ IdTree.postsList cs ↔ cur ≤ x ∧ x < pos
| _, [], _, h, x => by
cases h
simp only [IdTree.postsList_nil]
constructor
· intro hx; exact absurd hx (List.not_mem_nil x)
· rintro ⟨h1, h2⟩; exfalso; omega
| _, c :: cs, _, h, x => by
cases h with
| cons hc hcs =>
simp only [IdTree.postsList_cons, List.mem_append]
rw [Good.mem_posts c hc x, GoodChildren.mem_postsList cs hcs x]
have := hc.lo_le_post
have := GoodChildren.cur_le_pos cs hcs
omega
end
mutual
theorem Good.nodup_posts : ∀ {lo : } (t : IdTree), Good lo t → (IdTree.posts t).Nodup
| _, .node id cs, h => by
cases h with
| mk hlo hch =>
simp only [IdTree.posts_node, List.nodup_cons]
refine ⟨?_, GoodChildren.nodup_postsList cs hch⟩
intro hmem
rw [GoodChildren.mem_postsList cs hch id.post] at hmem
omega
theorem GoodChildren.nodup_postsList : ∀ {cur : } (cs : List IdTree) {pos : },
GoodChildren cur cs pos → (IdTree.postsList cs).Nodup
| _, [], _, h => by cases h; simp only [IdTree.postsList_nil, List.nodup_nil]
| _, c :: cs, _, h => by
cases h with
| cons hc hcs =>
simp only [IdTree.postsList_cons, List.nodup_append]
refine ⟨Good.nodup_posts c hc, GoodChildren.nodup_postsList cs hcs, ?_⟩
intro x hx1 hx2
rw [Good.mem_posts c hc x] at hx1
rw [GoodChildren.mem_postsList cs hcs x] at hx2
omega
end
mutual
theorem Good.subtree_good : ∀ {lo : } (t : IdTree), Good lo t →
∀ s ∈ IdTree.subtrees t, Good s.rootId.lo s
| _, .node id cs, h, s, hs => by
cases h with
| mk hlo hch =>
rw [IdTree.subtrees_node, List.mem_cons] at hs
rcases hs with rfl | hs
· simp only [IdTree.rootId_node]; rw [hlo]; exact Good.mk hlo hch
· exact GoodChildren.subtree_good cs hch s hs
theorem GoodChildren.subtree_good : ∀ {cur : } (cs : List IdTree) {pos : },
GoodChildren cur cs pos → ∀ s ∈ IdTree.subtreesList cs, Good s.rootId.lo s
| _, [], _, _, s, hs => by simp only [IdTree.subtreesList_nil, List.not_mem_nil] at hs
| _, c :: cs, _, h, s, hs => by
cases h with
| cons hc hcs =>
rw [IdTree.subtreesList_cons, List.mem_append] at hs
rcases hs with hs | hs
· exact Good.subtree_good c hc s hs
· exact GoodChildren.subtree_good cs hcs s hs
end
mutual
theorem IdTree.subtrees_subset : ∀ (t : IdTree) {b : IdTree},
b ∈ subtrees t → subtrees b ⊆ subtrees t
| .node id cs, b, hb => by
rw [subtrees_node, List.mem_cons] at hb
rcases hb with rfl | hb
· exact fun _ h => h
· intro x hx
rw [subtrees_node, List.mem_cons]
exact Or.inr (IdTree.subtreesList_subset cs hb hx)
theorem IdTree.subtreesList_subset : ∀ (cs : List IdTree) {b : IdTree},
b ∈ subtreesList cs → subtrees b ⊆ subtreesList cs
| [], b, hb => by simp only [subtreesList_nil, List.not_mem_nil] at hb
| c :: cs, b, hb => by
rw [subtreesList_cons, List.mem_append] at hb
intro x hx
rw [subtreesList_cons, List.mem_append]
rcases hb with hb | hb
· exact Or.inl (IdTree.subtrees_subset c hb hx)
· exact Or.inr (IdTree.subtreesList_subset cs hb hx)
end
theorem IdTree.eq_of_post_eq {l : List IdTree}
(h : (l.map (fun s => s.rootId.post)).Nodup) {a c : IdTree}
(ha : a ∈ l) (hc : c ∈ l) (hpost : a.rootId.post = c.rootId.post) : a = c := by
induction l with
| nil => exact absurd ha (List.not_mem_nil a)
| cons d ds ih =>
simp only [List.map_cons, List.nodup_cons] at h
obtain ⟨hd, htl⟩ := h
simp only [List.mem_cons] at ha hc
rcases ha with rfl | ha <;> rcases hc with rfl | hc
· rfl
· exfalso; apply hd; rw [hpost]; exact List.mem_map_of_mem _ hc
· exfalso; apply hd; rw [← hpost]; exact List.mem_map_of_mem _ ha
· exact ih htl ha hc
theorem descendant_iff_of_good {lo : } {t : IdTree} (hg : Good lo t)
{a b : IdTree} (ha : a ∈ IdTree.subtrees t) (hb : b ∈ IdTree.subtrees t) :
a.rootId.DescendantOf b.rootId ↔ a ∈ IdTree.subtrees b := by
have hgb : Good b.rootId.lo b := Good.subtree_good t hg b hb
constructor
· rintro ⟨h1, h2⟩
have hmem : a.rootId.post ∈ IdTree.posts b := by
rw [Good.mem_posts b hgb a.rootId.post]; exact ⟨h1, h2⟩
rw [IdTree.posts, List.mem_map] at hmem
obtain ⟨c, hc_mem, hc_post⟩ := hmem
have hc_t : c ∈ IdTree.subtrees t := IdTree.subtrees_subset t hb hc_mem
have hac : a = c :=
IdTree.eq_of_post_eq (hg.nodup_posts t) ha hc_t hc_post.symm
rw [hac]; exact hc_mem
· intro hsub
have hmem : a.rootId.post ∈ IdTree.posts b := by
rw [IdTree.posts, List.mem_map]; exact ⟨a, hsub, rfl⟩
rw [Good.mem_posts b hgb a.rootId.post] at hmem
exact hmem
/-! ### Tagging produces a good tree
We bridge from the `tag` traversal to the abstract `Good` invariant, by induction
on the plain AST. Each lemma also records that the returned counter is one past
the root's postorder index. -/
theorem Expr.tag_spec : ∀ (e : Expr) (n : ),
Good n (e.tag n).1.toIdTree ∧ (e.tag n).1.toIdTree.rootId.post + 1 = (e.tag n).2 := by
intro e
induction e with
| num k =>
intro n
refine ⟨?_, ?_⟩
· simp only [Expr.tag, Expr.Tagged.toIdTree]
exact Good.mk (by simp only [NodeId.lo]; omega) GoodChildren.nil
· simp only [Expr.tag, Expr.Tagged.toIdTree, IdTree.rootId_node]
| var x =>
intro n
refine ⟨?_, ?_⟩
· simp only [Expr.tag, Expr.Tagged.toIdTree]
exact Good.mk (by simp only [NodeId.lo]; omega) GoodChildren.nil
· simp only [Expr.tag, Expr.Tagged.toIdTree, IdTree.rootId_node]
| add a b iha ihb =>
intro n
obtain ⟨gA, pA⟩ := iha n
obtain ⟨gB, pB⟩ := ihb (a.tag n).2
have lA := gA.lo_le_post
have lB := gB.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Expr.tag, Expr.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gA ?_
rw [pA]; refine GoodChildren.cons gB ?_; rw [pB]; exact GoodChildren.nil
· simp only [Expr.tag, Expr.Tagged.toIdTree, IdTree.rootId_node]
| sub a b iha ihb =>
intro n
obtain ⟨gA, pA⟩ := iha n
obtain ⟨gB, pB⟩ := ihb (a.tag n).2
have lA := gA.lo_le_post
have lB := gB.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Expr.tag, Expr.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gA ?_
rw [pA]; refine GoodChildren.cons gB ?_; rw [pB]; exact GoodChildren.nil
· simp only [Expr.tag, Expr.Tagged.toIdTree, IdTree.rootId_node]
theorem BasicStmt.tag_spec : ∀ (bs : BasicStmt) (n : ),
Good n (bs.tag n).1.toIdTree ∧ (bs.tag n).1.toIdTree.rootId.post + 1 = (bs.tag n).2 := by
intro bs
cases bs with
| noop =>
intro n
refine ⟨?_, ?_⟩
· simp only [BasicStmt.tag, BasicStmt.Tagged.toIdTree]
exact Good.mk (by simp only [NodeId.lo]; omega) GoodChildren.nil
· simp only [BasicStmt.tag, BasicStmt.Tagged.toIdTree, IdTree.rootId_node]
| assign x e =>
intro n
obtain ⟨gE, pE⟩ := Expr.tag_spec e n
have lE := gE.lo_le_post
refine ⟨?_, ?_⟩
· simp only [BasicStmt.tag, BasicStmt.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gE ?_
rw [pE]; exact GoodChildren.nil
· simp only [BasicStmt.tag, BasicStmt.Tagged.toIdTree, IdTree.rootId_node]
theorem Stmt.tag_spec : ∀ (s : Stmt) (n : ),
Good n (s.tag n).1.toIdTree ∧ (s.tag n).1.toIdTree.rootId.post + 1 = (s.tag n).2 := by
intro s
induction s with
| basic bs =>
intro n
obtain ⟨gBs, pBs⟩ := BasicStmt.tag_spec bs n
have lBs := gBs.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Stmt.tag, Stmt.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gBs ?_
rw [pBs]; exact GoodChildren.nil
· simp only [Stmt.tag, Stmt.Tagged.toIdTree, IdTree.rootId_node]
| andThen a b iha ihb =>
intro n
obtain ⟨gA, pA⟩ := iha n
obtain ⟨gB, pB⟩ := ihb (a.tag n).2
have lA := gA.lo_le_post
have lB := gB.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Stmt.tag, Stmt.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gA ?_
rw [pA]; refine GoodChildren.cons gB ?_; rw [pB]; exact GoodChildren.nil
· simp only [Stmt.tag, Stmt.Tagged.toIdTree, IdTree.rootId_node]
| ifElse e a b iha ihb =>
intro n
obtain ⟨gE, pE⟩ := Expr.tag_spec e n
obtain ⟨gA, pA⟩ := iha (e.tag n).2
obtain ⟨gB, pB⟩ := ihb (a.tag (e.tag n).2).2
have lE := gE.lo_le_post
have lA := gA.lo_le_post
have lB := gB.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Stmt.tag, Stmt.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gE ?_
rw [pE]; refine GoodChildren.cons gA ?_
rw [pA]; refine GoodChildren.cons gB ?_; rw [pB]; exact GoodChildren.nil
· simp only [Stmt.tag, Stmt.Tagged.toIdTree, IdTree.rootId_node]
| whileLoop e s ih =>
intro n
obtain ⟨gE, pE⟩ := Expr.tag_spec e n
obtain ⟨gS, pS⟩ := ih (e.tag n).2
have lE := gE.lo_le_post
have lS := gS.lo_le_post
refine ⟨?_, ?_⟩
· simp only [Stmt.tag, Stmt.Tagged.toIdTree]
refine Good.mk ?_ ?_
· simp only [NodeId.lo]; omega
· refine GoodChildren.cons gE ?_
rw [pE]; refine GoodChildren.cons gS ?_; rw [pS]; exact GoodChildren.nil
· simp only [Stmt.tag, Stmt.Tagged.toIdTree, IdTree.rootId_node]
/-- A freshly tagged program is a well-tagged tree (rooted at postorder start `0`). -/
theorem good_tagStmt (s : Stmt) : Good 0 (tagStmt s).toIdTree :=
(Stmt.tag_spec s 0).1
/-- **Descendant characterization.** The numeric `NodeId.DescendantOf` relation on
two nodes of a tagged program holds exactly when one is structurally contained in
the other's subtree. -/
theorem descendant_iff_tagStmt (s : Stmt) {a b : IdTree}
(ha : a ∈ IdTree.subtrees (tagStmt s).toIdTree)
(hb : b ∈ IdTree.subtrees (tagStmt s).toIdTree) :
a.rootId.DescendantOf b.rootId ↔ a ∈ IdTree.subtrees b :=
descendant_iff_of_good (good_tagStmt s) ha hb
```

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@@ -0,0 +1,509 @@
import Lean
import Mathlib.Tactic.DeriveTraversable
import Spa.Language.Base
import Spa.Language.Tagged.Id
/-!
# The `derive_tagged` command
`derive_tagged T₁ T₂ … Tₙ` takes a family of (possibly mutually recursive)
inductive types and generates, for each `Tᵢ`:
* a *tagged* mirror inductive `Tᵢ.Tagged (τ : Type)`, in which every constructor
carries a leading `tag : τ` field and every field whose type is a family
member is retyped to its `.Tagged τ` counterpart;
* `Tᵢ.Tagged.erase : Tᵢ.Tagged τ → Tᵢ`, forgetting all tags;
* `Tᵢ.tag : Tᵢ → → Tᵢ.Tagged RawId × `, assigning every node a unique
`RawId` (its postorder index) by a single unified traversal that threads a
counter; the whole family shares one counter, so identifiers are unique across
types.
The generated declarations have exactly the shape of the hand-written reference;
see `Spa/Language/Tagged/Basic.lean` (which invokes this command) and the proofs
in `Spa/Language/Tagged/Properties.lean`.
Scope: the generator handles non-indexed inductives whose constructor fields are
either scalars or *direct* references to a family member (which covers the object
language). Nested occurrences such as `List Tᵢ` are not supported.
-/
open Lean Elab Command Meta
namespace Spa.DeriveTagged
/-- One constructor field, classified as a recursive family reference or a scalar
(whose type syntax we keep verbatim for the mirror inductive). -/
structure FieldData where
isRec : Bool
recType : Name
typeStx : Term
/-- A constructor: its original (full) name, short name, and fields. -/
structure CtorData where
origName : Name
shortName : Name
fields : Array FieldData
/-- A family member together with its constructors. -/
structure TypeData where
name : Name
ctors : Array CtorData
def taggedOf (n : Name) : Name := n ++ `Tagged
def eraseOf (n : Name) : Name := n ++ `Tagged ++ `erase
def rootTagOf (n : Name) : Name := n ++ `Tagged ++ `rootTag
def tagOf (n : Name) : Name := n ++ `tag
def foldTagsOf (n : Name) : Name := n ++ `Tagged ++ `foldTags
def wfOf (n : Name) : Name := n ++ `Tagged ++ `WF
def narrowOf (n : Name) : Name := n ++ `Tagged ++ `narrow
def narrowEraseOf (n : Name) : Name := n ++ `Tagged ++ `narrow_erase
def tagLeOf (n : Name) : Name := n ++ `tag_le
def tagRootTagPostOf (n : Name) : Name := n ++ `tag_rootTag_post
def tagWfOf (n : Name) : Name := n ++ `tag_wf
/-- Project the `i`-th conjunct (1-based) out of `hyp`, which has type a
right-nested `And` of `total` conjuncts, e.g. `hyp |>.2 |>.2 |>.1`. -/
def projAnd {m : Type Type} [Monad m] [MonadQuotation m]
(hyp : Term) (i total : Nat) : m Term := do
let mut t := hyp
for _ in [0:i-1] do
t `($t |>.2)
if i < total then
t `($t |>.1)
return t
/-- Combine a non-empty array of propositions into a right-nested conjunction. -/
def mkAndR {m : Type Type} [Monad m] [MonadQuotation m]
(cs : Array Term) : m Term := do
let mut t := cs.back!
for c in cs.pop.reverse do
t `($c $t)
return t
/-- For a constructor, return one entry per *recursive* field: its argument
identifier, the family member it references, and the start-counter expression at
which it is tagged (`n`, then `(a.tag n).2`, …) — the same threading `mkTag`
uses. -/
def recChildren (cd : CtorData) (argNames : Array Ident) (nStart : Term) :
CommandElabM (Array (Ident × Name × Term)) := do
let mut res : Array (Ident × Name × Term) := #[]
let mut cur := nStart
for (f, a) in cd.fields.zip argNames do
if f.isRec then
res := res.push (a, f.recType, cur)
cur `(($(mkIdent (tagOf f.recType)) $a $cur) |>.2)
return res
/-- Inspect the family, classifying each constructor field. -/
def gather (family : Array Name) (τ : Ident) : TermElabM (Array TypeData) := do
let famSet : NameSet := family.foldl (·.insert ·) {}
family.mapM fun tn => do
let iv getConstInfoInduct tn
let ctors iv.ctors.toArray.mapM fun cn => do
let cv getConstInfoCtor cn
let fields forallTelescopeReducing cv.type fun args _ => do
let fieldArgs := args.extract iv.numParams args.size
fieldArgs.mapM fun a => do
let ty inferType a
match ty.getAppFn.constName? with
| some hn =>
if famSet.contains hn then
return { isRec := true, recType := hn, typeStx := `($(mkIdent (taggedOf hn)) $τ) }
else
return { isRec := false, recType := default, typeStx := Lean.PrettyPrinter.delab ty }
| none =>
return { isRec := false, recType := default, typeStx := Lean.PrettyPrinter.delab ty }
return { origName := cn, shortName := cn.componentsRev.head!, fields }
return { name := tn, ctors }
/-- The arrow type `τ → <fields…> → Self τ` of a tagged constructor. -/
def ctorArrow (cd : CtorData) (self : Term) (τ : Ident) : TermElabM Term := do
let mut t := self
for f in cd.fields.reverse do
t `($(f.typeStx) $t)
`($τ $t)
/-- The tagged mirror inductives, one per family member. The family is a DAG
(`Expr ← BasicStmt ← Stmt`), not genuinely mutual, so they are emitted as
separate inductives in dependency order rather than a `mutual` block.
`Functor`/`Traversable` instances are derived separately by `mkDeriveInstances`
below rather than via an inline `deriving` clause. -/
def mkInductives (tds : Array TypeData) (τ : Ident) :
CommandElabM (Array (TSyntax `command)) := do
tds.mapM fun td => do
let self `($(mkIdent (taggedOf td.name)) $τ)
let ctors td.ctors.mapM fun cd => do
let aty Command.liftTermElabM (ctorArrow cd self τ)
`(Lean.Parser.Command.ctor| | $(mkIdent cd.shortName):ident : $aty)
`(command| inductive $(mkIdent (taggedOf td.name)):ident ($τ : Type) where $ctors*)
/-- A `deriving instance Functor, Traversable for Tᵢ.Tagged` command per family
member. Since every tagged type is a single-parameter, direct-recursive
inductive in `τ`, Mathlib's deriving handler produces clean (`sorry`-free)
instances, giving `map`, `traverse`, and the `Traversable.foldr`/`toList` folds
for free.
These are emitted as *separate* commands in dependency order (rather than an
inline `deriving` clause on each inductive) for two reasons: deriving
`Stmt.Tagged` needs the `Expr.Tagged`/`BasicStmt.Tagged` instances already in
scope, and — because every member's type name ends in `.Tagged` — the handler's
auto-generated instance name (`instFunctorTagged`, built from the type's last
component) collides across the family unless each derive sees the environment
the previous one updated; separate commands give it that, so the names
disambiguate to `instFunctorTagged`, `instFunctorTagged_1`, ….
The hand-written `foldTags` is retained alongside these: it is a
structural-recursion fold that `simp`/`decide` reduce cleanly, unlike the
abstract `Traversable.foldr` (defined via the `FreeMonoid`/`Const` applicative),
which reduces under `decide`/`rfl` but not naive `simp` unfolding. -/
def mkDeriveInstances (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
tds.mapM fun td =>
`(command| deriving instance Functor, Traversable for $(mkIdent (taggedOf td.name)))
/-- The `erase` functions, one per family member (separate defs in dependency
order — each calls only already-defined lower members). -/
def mkErase (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
tds.mapM fun td => do
let mut pats : Array Term := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map (fun i => mkIdent (.mkSimple s!"a{i}"))
let pat `($(mkIdent (taggedOf td.name ++ cd.shortName)) _ $argNames*)
let eraseArgs (cd.fields.zip argNames).mapM fun (f, a) =>
if f.isRec then `($(mkIdent (eraseOf f.recType)) $a) else pure a
let rhs `($(mkIdent cd.origName) $eraseArgs*)
pats := pats.push pat
rhss := rhss.push rhs
`(command| def $(mkIdent (eraseOf td.name)) {τ : Type} :
$(mkIdent (taggedOf td.name)) τ $(mkIdent td.name) :=
fun x => match x with $[| $pats => $rhss]*)
/-- The `rootTag` accessors (one non-recursive `def` per type). -/
def mkRootTag (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let tIdent := mkIdent `t
tds.mapM fun td => do
let mut pats : Array Term := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let hole `(_)
let wilds := Array.mkArray cd.fields.size hole
pats := pats.push ( `($(mkIdent (taggedOf td.name ++ cd.shortName)) $tIdent $wilds*))
rhss := rhss.push tIdent
`(command| def $(mkIdent (rootTagOf td.name)) {τ : Type} :
$(mkIdent (taggedOf td.name)) τ τ :=
fun x => match x with $[| $pats => $rhss]*)
/-- The postorder `tag` functions, one per family member (separate defs in
dependency order). -/
def mkTag (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let nId := mkIdent ``Spa.RawId
tds.mapM fun td => do
let mut pats : Array Term := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map (fun i => mkIdent (.mkSimple s!"a{i}"))
let pat `($(mkIdent cd.origName) $argNames*)
let mut cur : Term `(n)
let mut lets : Array (Ident × Term) := #[]
let mut taggedArgs : Array Term := #[]
let mut ri := 0
for (f, a) in cd.fields.zip argNames do
if f.isRec then
let rName := mkIdent (.mkSimple s!"r{ri}")
let rhsCall `($(mkIdent (tagOf f.recType)) $a $cur)
lets := lets.push (rName, rhsCall)
taggedArgs := taggedArgs.push ( `($rName |>.1))
cur `($rName |>.2)
ri := ri + 1
else
taggedArgs := taggedArgs.push a
let last := cur
let tagged `($(mkIdent (taggedOf td.name ++ cd.shortName))
($last : $nId) $taggedArgs*)
let mut body `(($tagged, $last + 1))
for (rName, rhs) in lets.reverse do
body `(let $rName := $rhs; $body)
pats := pats.push pat
rhss := rhss.push body
`(command| def $(mkIdent (tagOf td.name)) :
$(mkIdent td.name) Nat $(mkIdent (taggedOf td.name)) $nId × Nat :=
fun e n => match e with $[| $pats => $rhss]*)
/-- The tag-fold functions: `foldTags f acc t` applies `f` to every tag in `t`,
right-to-left, threading `acc`. This is the `Foldable`/`foldr`-over-tags the
hand-written collectors (e.g. `subtreeIds`) reduce to. One separate def per
family member (the family is a DAG, so no `mutual` block is needed). -/
def mkFoldTags (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let τ := mkIdent
let m := mkIdent `M
let fId := mkIdent `f
let accId := mkIdent `acc
let tagId := mkIdent `t
tds.mapM fun td => do
let mut pats : Array Term := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map (fun i => mkIdent (.mkSimple s!"a{i}"))
let pat `($(mkIdent (taggedOf td.name ++ cd.shortName)) $tagId $argNames*)
let mut body : Term := accId
for (fld, a) in (cd.fields.zip argNames).reverse do
if fld.isRec then
body `($(mkIdent (foldTagsOf fld.recType)) $fId $body $a)
body `($fId $tagId $body)
pats := pats.push pat
rhss := rhss.push body
`(command| def $(mkIdent (foldTagsOf td.name)) {$τ:ident : Type} {$m:ident : Type}
($fId : $τ $m $m) ($accId : $m) :
$(mkIdent (taggedOf td.name)) $τ $m :=
fun x => match x with $[| $pats => $rhss]*)
/-- The well-formedness predicate `T.Tagged.WF : T.Tagged RawId → Prop`: every
recursive child's root tag has a strictly smaller postorder index than the node's
own tag, and each child is itself well-formed. Leaf constructors are `True`. -/
def mkWF (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let tId := mkIdent `t
let rawId := mkIdent ``Spa.RawId
tds.mapM fun td => do
let mut pats : Array Term := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let hasRec := cd.fields.any (·.isRec)
let mut patArgs : Array Term := #[]
let mut recArgs : Array Ident := #[]
let mut i := 0
for f in cd.fields do
if f.isRec then
let a := mkIdent (.mkSimple s!"a{i}")
patArgs := patArgs.push a
recArgs := recArgs.push a
else
patArgs := patArgs.push ( `(_))
i := i + 1
let tagBind : Term if hasRec then `($tId) else `(_)
let pat `($(mkIdent (taggedOf td.name ++ cd.shortName)) $tagBind $patArgs*)
let rhs if recArgs.isEmpty then `(True) else do
let bounds recArgs.mapM fun a => `($(a).rootTag.post < $(tId).post)
let wfs recArgs.mapM fun a => `($(a).WF)
mkAndR (bounds ++ wfs)
pats := pats.push pat
rhss := rhss.push rhs
`(command| def $(mkIdent (wfOf td.name)) :
$(mkIdent (taggedOf td.name)) $rawId Prop :=
fun x => match x with $[| $pats => $rhss]*)
/-- The `narrow` coercion `T.Tagged RawId → T.Tagged (Fin N)`, given a bound on
the root tag and a well-formedness proof. Each node's tag becomes the `Fin N`
built from its postorder index, and recursion threads the bound through `lt_trans`
and the (definitionally unfolded) `WF` conjunction. -/
def mkNarrow (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let rawId := mkIdent ``Spa.RawId
let tId := mkIdent `t
let nId := mkIdent `N
let hId := mkIdent `h
let hwfId := mkIdent `hwf
let tgId := mkIdent `tg
tds.mapM fun td => do
let self `($(mkIdent (taggedOf td.name)) $rawId)
let mut patss : Array (Array Term) := #[]
let mut rhss : Array Term := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map fun i => mkIdent (.mkSimple s!"a{i}")
let ctorPat `($(mkIdent (taggedOf td.name ++ cd.shortName)) $tgId $argNames*)
let k := (cd.fields.filter (·.isRec)).size
let mut newArgs : Array Term := #[]
let mut ri := 0
for (f, a) in cd.fields.zip argNames do
if f.isRec then
let bound projAnd hwfId (ri + 1) (2 * k)
let wf projAnd hwfId (k + ri + 1) (2 * k)
newArgs := newArgs.push ( `($(a).narrow (lt_trans $bound $hId) $wf))
ri := ri + 1
else
newArgs := newArgs.push a
let built `($(mkIdent (taggedOf td.name ++ cd.shortName)) $(tgId).post, $hId $newArgs*)
let nPat `(_)
let hPat `($hId)
let hwfPat : Term if k == 0 then `(_) else `($hwfId)
patss := patss.push #[ctorPat, nPat, hPat, hwfPat]
rhss := rhss.push built
`(command| def $(mkIdent (narrowOf td.name)) : ($tId : $self) {$nId : }
$(tId).rootTag.post < $nId $(tId).WF $(mkIdent (taggedOf td.name)) (Fin $nId)
$[| $[$patss],* => $rhss]*)
/-- `T.tag_rootTag_post`: the root tag of a freshly tagged node is exactly one
below the threaded-out counter, i.e. the node itself is numbered last (postorder).
A uniform `cases <;> simp` discharges every constructor. -/
def mkTagRootTagPost (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let eId := mkIdent `e
let nId := mkIdent `n
tds.mapM fun td =>
`(command| theorem $(mkIdent (tagRootTagPostOf td.name))
($eId : $(mkIdent td.name)) ($nId : ) :
($(eId).tag $nId).1.rootTag.post + 1 = ($(eId).tag $nId).2 := by
cases $eId:ident <;>
simp [$(mkIdent (tagOf td.name)):ident, $(mkIdent (rootTagOf td.name)):ident])
/-- `T.tag_le`: tagging only ever advances the counter (`n ≤ (e.tag n).2`).
Proved by induction; each arm threads the counter through its recursive children
(using the relevant `tag_le`/induction hypothesis) and closes with `omega`. -/
def mkTagLe (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let eId := mkIdent `e
let nId := mkIdent `n
tds.mapM fun td => do
let mut ctorLabels : Array Ident := #[]
let mut binderss : Array (Array Ident) := #[]
let mut tacs : Array (TSyntax ``Lean.Parser.Tactic.tacticSeq) := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map fun i => mkIdent (.mkSimple s!"a{i}")
let mut ihBinders : Array Ident := #[]
let mut haveTacs : Array (TSyntax `tactic) := #[]
let mut cur : Term `($nId)
let mut i := 0
for (f, a) in cd.fields.zip argNames do
if f.isRec then
let fact if f.recType == td.name then
`($(mkIdent (.mkSimple s!"ih{i}")) $cur)
else
`($(mkIdent (tagLeOf f.recType)) $a $cur)
if f.recType == td.name then
ihBinders := ihBinders.push (mkIdent (.mkSimple s!"ih{i}"))
haveTacs := haveTacs.push ( `(tactic| have := $fact))
cur `(($(mkIdent (tagOf f.recType)) $a $cur) |>.2)
i := i + 1
let simpTac `(tactic| simp only [$(mkIdent (tagOf td.name)):ident])
let omegaTac `(tactic| omega)
let allTacs := #[simpTac] ++ haveTacs ++ #[omegaTac]
ctorLabels := ctorLabels.push (mkIdent cd.shortName)
binderss := binderss.push (argNames ++ ihBinders)
tacs := tacs.push ( `(tacticSeq| $[$allTacs]*))
`(command| theorem $(mkIdent (tagLeOf td.name)) ($eId : $(mkIdent td.name)) ($nId : ) :
$nId ($(eId).tag $nId).2 := by
induction $eId:ident generalizing $nId:ident with
$[| $ctorLabels:ident $binderss* => $tacs]*)
/-- `T.tag_wf`: a freshly tagged term is well-formed. Each recursive child's
bound conjunct is closed by `omega` from that child's `tag_rootTag_post` plus the
`tag_le` of every later child (which bounds the threaded-out counter), and each
well-formedness conjunct is the child's induction hypothesis / `tag_wf`. -/
def mkTagWf (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let eId := mkIdent `e
let nId := mkIdent `n
tds.mapM fun td => do
let mut ctorLabels : Array Ident := #[]
let mut binderss : Array (Array Ident) := #[]
let mut tacs : Array (TSyntax ``Lean.Parser.Tactic.tacticSeq) := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map fun i => mkIdent (.mkSimple s!"a{i}")
-- recursive children: (arg, recType, startCounter, sameType?, fieldIndex)
let mut recs : Array (Ident × Name × Term × Bool × Nat) := #[]
let mut cur : Term `($nId)
let mut i := 0
for (f, a) in cd.fields.zip argNames do
if f.isRec then
recs := recs.push (a, f.recType, cur, f.recType == td.name, i)
cur `(($(mkIdent (tagOf f.recType)) $a $cur) |>.2)
i := i + 1
let k := recs.size
let ihBinders := (recs.filter (·.2.2.2.1)).map fun r => mkIdent (.mkSimple s!"ih{r.2.2.2.2}")
let tac : TSyntax ``Lean.Parser.Tactic.tacticSeq if k == 0 then
`(tacticSeq| exact True.intro)
else do
let mut comps : Array Term := #[]
-- bound conjuncts
for idx in [0:k] do
let (a, rt, s, _, _) := recs[idx]!
let mut bHaves : Array (TSyntax `tactic) :=
#[ `(tactic| have := $(mkIdent (tagRootTagPostOf rt)) $a $s)]
for j in [idx+1:k] do
let (aj, rtj, sj, _, _) := recs[j]!
bHaves := bHaves.push ( `(tactic| have := $(mkIdent (tagLeOf rtj)) $aj $sj))
bHaves := bHaves.push ( `(tactic| omega))
comps := comps.push ( `(by $( `(tacticSeq| $[$bHaves]*))))
-- well-formedness conjuncts
for idx in [0:k] do
let (a, rt, s, same, fi) := recs[idx]!
comps := comps.push <| if same then `($(mkIdent (.mkSimple s!"ih{fi}")) $s)
else `($(mkIdent (tagWfOf rt)) $a $s)
let simpTac `(tactic| simp only
[$(mkIdent (tagOf td.name)):ident, $(mkIdent (wfOf td.name)):ident])
let exactTac `(tactic| exact $comps,*)
`(tacticSeq| $[$(#[simpTac, exactTac])]*)
ctorLabels := ctorLabels.push (mkIdent cd.shortName)
binderss := binderss.push (argNames ++ ihBinders)
tacs := tacs.push tac
`(command| theorem $(mkIdent (tagWfOf td.name)) ($eId : $(mkIdent td.name)) ($nId : ) :
($(eId).tag $nId).1.WF := by
induction $eId:ident generalizing $nId:ident with
$[| $ctorLabels:ident $binderss* => $tacs]*)
/-- `T.Tagged.narrow_erase`: narrowing the tag type does not change the erased
(untagged) term. A per-constructor `simp` with the local `narrow`/`erase`
equations, the lower members' `narrow_erase`, and the induction hypotheses. -/
def mkNarrowErase (tds : Array TypeData) : CommandElabM (Array (TSyntax `command)) := do
let rawId := mkIdent ``Spa.RawId
let tId := mkIdent `t
let nId := mkIdent `N
let hId := mkIdent `h
let hwfId := mkIdent `hwf
let tgId := mkIdent `tg
tds.mapM fun td => do
let mut ctorLabels : Array Ident := #[]
let mut binderss : Array (Array Ident) := #[]
let mut tacs : Array (TSyntax ``Lean.Parser.Tactic.tacticSeq) := #[]
for cd in td.ctors do
let argNames := (Array.range cd.fields.size).map fun i => mkIdent (.mkSimple s!"a{i}")
let mut lemmas : Array Term :=
#[ `($(mkIdent (narrowOf td.name))), `($(mkIdent (eraseOf td.name)))]
let mut ihBinders : Array Ident := #[]
let mut seenLower : Array Name := #[]
let mut i := 0
for f in cd.fields do
if f.isRec then
if f.recType == td.name then
let ih := mkIdent (.mkSimple s!"ih{i}")
ihBinders := ihBinders.push ih
lemmas := lemmas.push ( `($ih))
else if !seenLower.contains f.recType then
seenLower := seenLower.push f.recType
lemmas := lemmas.push ( `($(mkIdent (narrowEraseOf f.recType))))
i := i + 1
let introTac `(tactic| intro $nId $hId $hwfId)
let simpTac `(tactic| simp [$[$lemmas:term],*])
ctorLabels := ctorLabels.push (mkIdent cd.shortName)
binderss := binderss.push (#[tgId] ++ argNames ++ ihBinders)
tacs := tacs.push ( `(tacticSeq| $[$(#[introTac, simpTac])]*))
`(command| theorem $(mkIdent (narrowEraseOf td.name)) :
($tId : $(mkIdent (taggedOf td.name)) $rawId) {$nId : }
($hId : $(tId).rootTag.post < $nId) ($hwfId : $(tId).WF),
($(tId).narrow $hId $hwfId).erase = $(tId).erase := by
intro $tId:ident
induction $tId:ident with
$[| $ctorLabels:ident $binderss* => $tacs]*)
/-- `derive_tagged T₁ … Tₙ` — generate tagged mirrors, `erase`, and `tag` for the
given family of inductives. -/
syntax (name := deriveTaggedCmd) "derive_tagged " ident+ : command
@[command_elab deriveTaggedCmd]
def elabDeriveTagged : CommandElab := fun stx => do
match stx with
| `(derive_tagged $ids*) =>
let family ids.mapM fun i => Command.liftCoreM (realizeGlobalConstNoOverload i)
let τ := mkIdent
let tds Command.liftTermElabM (gather family τ)
for d in ( mkInductives tds τ) do elabCommand d
for d in ( mkDeriveInstances tds) do elabCommand d
for d in ( mkRootTag tds) do elabCommand d
for d in ( mkErase tds) do elabCommand d
for d in ( mkTag tds) do elabCommand d
for d in ( mkFoldTags tds) do elabCommand d
for d in ( mkWF tds) do elabCommand d
for d in ( mkNarrow tds) do elabCommand d
for d in ( mkTagRootTagPost tds) do elabCommand d
for d in ( mkTagLe tds) do elabCommand d
for d in ( mkTagWf tds) do elabCommand d
for d in ( mkNarrowErase tds) do elabCommand d
| _ => throwUnsupportedSyntax
end Spa.DeriveTagged

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import Spa.Language
import Spa.Language.Graphs
import Spa.Language.Tagged.Basic
import Spa.Language.Tagged.Properties
namespace Spa
open GGraph
def Stmt.Tagged.cfg {τ : Type} : Stmt.Tagged τ GGraph (Option (BasicStmt.Tagged τ))
| .basic _ bs => GGraph.singleton (some bs)
| .andThen _ s₁ s₂ => s₁.cfg s₂.cfg
| .ifElse _ _ s₁ s₂ => s₁.cfg s₂.cfg
| .whileLoop _ _ s => GGraph.loop s.cfg
theorem Stmt.Tagged.cfg_graph {τ : Type} : (t : Stmt.Tagged τ),
(Option.map BasicStmt.Tagged.erase) <$> t.cfg = t.erase.cfg
| .basic _ bs => by simp [Stmt.Tagged.cfg, Stmt.cfg, Stmt.Tagged.erase, BasicStmt.Tagged.erase]
| .andThen _ s₁ s₂ => by
simp [Stmt.Tagged.cfg, Stmt.cfg, Stmt.Tagged.erase, Stmt.Tagged.cfg_graph s₁, Stmt.Tagged.cfg_graph s₂]
| .ifElse _ _ s₁ s₂ => by
simp [Stmt.Tagged.cfg, Stmt.cfg, Stmt.Tagged.erase, Stmt.Tagged.cfg_graph s₁, Stmt.Tagged.cfg_graph s₂]
| .whileLoop _ _ s => by
simp [Stmt.Tagged.cfg, Stmt.cfg, Stmt.Tagged.erase, Stmt.Tagged.cfg_graph s]
def GGraph.nodeLabel {τ : Type} (g : GGraph (Option (BasicStmt.Tagged τ))) (i : g.Index) :
Option τ :=
(g.nodes i).map BasicStmt.Tagged.rootTag
def GGraph.stateOf {τ : Type} [DecidableEq τ] (g : GGraph (Option (BasicStmt.Tagged τ)))
(id : τ) : Option g.Index :=
g.indices.find? (fun i => decide (g.nodeLabel i = some id))
theorem GGraph.stateOf_label {τ : Type} [DecidableEq τ]
{g : GGraph (Option (BasicStmt.Tagged τ))} {id : τ}
{i : g.Index} (h : g.stateOf id = some i) : g.nodeLabel i = some id := by
rw [GGraph.stateOf] at h
simpa using List.find?_some h
namespace Program
variable (p : Program)
def tagged : Stmt.Tagged RawId := tagStmt p.rootStmt
def size : := p.tagged.rootTag.post + 1
theorem size_pos : 0 < p.size := Nat.succ_pos _
abbrev NodeId : Type := Fin p.size
theorem tagged_wf : p.tagged.WF := Stmt.tag_wf p.rootStmt 0
def taggedFin : Stmt.Tagged p.NodeId :=
p.tagged.narrow (Nat.lt_succ_self _) p.tagged_wf
def taggedCfg : GGraph (Option (BasicStmt.Tagged p.NodeId)) :=
GGraph.wrap p.taggedFin.cfg
theorem taggedCfg_erase :
(Option.map BasicStmt.Tagged.erase) <$> p.taggedCfg = p.cfg := by
rw [taggedCfg, GGraph.map_wrap, Stmt.Tagged.cfg_graph, taggedFin,
Stmt.Tagged.narrow_erase, tagged, erase_tagStmt]
rfl
theorem taggedCfg_size : p.taggedCfg.size = p.cfg.size := by
conv_rhs => rw [ p.taggedCfg_erase]
rfl
def nodeIdOf (s : p.State) : Option p.NodeId :=
p.taggedCfg.nodeLabel (Fin.cast p.taggedCfg_size.symm s)
def stateOfNodeId (id : p.NodeId) : Option p.State :=
(p.taggedCfg.stateOf id).map (Fin.cast p.taggedCfg_size)
theorem cfg_nodes_eq (s : p.State) :
p.cfg.nodes s = Option.map BasicStmt.Tagged.erase
(p.taggedCfg.nodes (Fin.cast p.taggedCfg_size.symm s)) := by
have key : (g : Graph) (hsz : p.taggedCfg.size = g.size),
(Option.map BasicStmt.Tagged.erase) <$> p.taggedCfg = g
i : Fin g.size,
g.nodes i = Option.map BasicStmt.Tagged.erase
(p.taggedCfg.nodes (Fin.cast hsz.symm i)) := by
intro g hsz hg i
subst hg
rfl
exact key p.cfg p.taggedCfg_size p.taggedCfg_erase s
theorem nodeIdOf_isSome_of_code {s : p.State} {bs : BasicStmt}
(h : p.code s = some bs) : (p.nodeIdOf s).isSome = true := by
have hc : Option.map BasicStmt.Tagged.erase
(p.taggedCfg.nodes (Fin.cast p.taggedCfg_size.symm s)) = some bs := by
rw [ p.cfg_nodes_eq s]; exact h
unfold Program.nodeIdOf GGraph.nodeLabel
cases hcase : p.taggedCfg.nodes (Fin.cast p.taggedCfg_size.symm s) with
| none => rw [hcase] at hc; simp at hc
| some tbs => simp
def nodeIdOfNonempty (s : p.State) {bs : BasicStmt} (h : p.code s = some bs) : p.NodeId :=
(p.nodeIdOf s).get (p.nodeIdOf_isSome_of_code h)
end Program
end Spa

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import Mathlib.Data.Nat.Notation
namespace Spa
structure RawId where
post :
deriving DecidableEq, Repr
end Spa

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import Spa.Language.Tagged.Basic
namespace Spa
@[simp] theorem Expr.erase_tag (e : Expr) (n : ) : (e.tag n).1.erase = e := by
induction e generalizing n with
| add a b iha ihb => simp [Expr.tag, Expr.Tagged.erase, iha, ihb]
| sub a b iha ihb => simp [Expr.tag, Expr.Tagged.erase, iha, ihb]
| var x => simp [Expr.tag, Expr.Tagged.erase]
| num k => simp [Expr.tag, Expr.Tagged.erase]
@[simp] theorem BasicStmt.erase_tag (bs : BasicStmt) (n : ) :
(bs.tag n).1.erase = bs := by
cases bs with
| assign x e => simp [BasicStmt.tag, BasicStmt.Tagged.erase]
| noop => simp [BasicStmt.tag, BasicStmt.Tagged.erase]
@[simp] theorem Stmt.erase_tag (s : Stmt) (n : ) : (s.tag n).1.erase = s := by
induction s generalizing n with
| basic bs => simp [Stmt.tag, Stmt.Tagged.erase]
| andThen a b iha ihb => simp [Stmt.tag, Stmt.Tagged.erase, iha, ihb]
| ifElse e a b iha ihb => simp [Stmt.tag, Stmt.Tagged.erase, iha, ihb]
| whileLoop e s ih => simp [Stmt.tag, Stmt.Tagged.erase, ih]
/-- Erasing a freshly tagged program recovers it. -/
theorem erase_tagStmt (s : Stmt) : (tagStmt s).erase = s := by
simp [tagStmt]
end Spa

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# Tagged AST — follow-ups
## Descendant tracking — parked
The interval-labeling descendant test and its correctness proof
(`descendant_iff_tagStmt` and supporting rose-tree/`Good` machinery) have been
removed from the live code and parked in `DESCENDANT-TRACKING.md`, with a revival
checklist. It's a computational optimization not yet needed; revive it (and the
`NodeId.desc` field) when LICM wants fast ancestor queries.
## ID → CFG-state mapping — plan part B — DONE
`Graphs.lean` now defines a payload-generic `GGraph α` (with `Graph := GGraph
(List BasicStmt)` as the concrete CFG), so the labelled CFG **reuses** the graph
combinators instead of mirroring them. In `Cfg.lean`:
`buildCfgL : Stmt.Tagged NodeId → GGraph (List (BasicStmt.Tagged NodeId))` is just
`buildCfg` at the tagged payload; `buildCfgL_graph :
(buildCfgL t).map (List.map erase) = buildCfg t.erase` connects it to the real
CFG; and `GGraph.nodeLabel`/`GGraph.stateOf` read a node's id straight from its
payload (`stateOf_label` is the soundness). No `LGraph`, no separate `label`
field, no duplicated combinators.
## ID → CFG-state mapping — totality — DONE
The `Option`-valued `nodeIdOf`/`stateOfNodeId` are now proven total on the inputs
that matter (`Graphs.lean`), via a payload-list characterization of the CFG:
- `GGraph.nodeList` flattens `nodes` into the list of payloads, with combinator
lemmas (`nodeList_comp/link/loop/wrap`) reducing it through the CFG builders.
- `Stmt.Tagged.basics` lists a program's basic statements; the master lemma
`Stmt.Tagged.cfg_nodeList_filter` (and its program-level
`taggedCfg_nodeList_filter`) shows the non-empty CFG nodes are *exactly* the
singletons `[bs]` for `bs ∈ basics`.
- AST ⇒ CFG: `exists_state_of_mem_basics` (a state with payload `[bs]`) and
`stateOfNodeId_isSome` (the search succeeds).
- CFG ⇒ AST: `exists_basic_of_code_ne_nil` (a non-empty node is `[bs]`, with
`code = [bs.erase]` and `nodeIdOf = some bs.rootTag`) and `nodeIdOf_isSome`.
All `propext`/`Quot.sound`-only (no `sorry`, no choice).
Remaining nice-to-have:
- Injectivity: distinct basic-statement ids map to distinct states, giving a
two-sided id ↔ state correspondence (upgrading the existence results above to a
genuine bijection, and pinning `stateOfNodeId (bs.rootTag)` to *the* state
holding `bs`). The `tag`-uniqueness fact this needs (`Nodup` of postorder tags)
was part of the parked descendant machinery in `DESCENDANT-TRACKING.md`.

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@@ -1,26 +1,266 @@
import Spa.Language.Semantics import Spa.Language.Semantics
import Spa.Language.Graphs import Spa.Language.Graphs
import Spa.Language.Program
/-!
# Program Traces
This module defines program traces tied to Control Flow Graphs, or CFGs
(see `Spa.GGraph` and `Spa.Graph`). These traces boil town to sequences of
basic-block executions (really, `Spa.BasicStmt` executions), each of which must
have an actual basic block in the graph _and_ be connected to the previous
basic block by an edge. In this way, traces encode executions admitted
by the CFG.
While the regular `Trace` is just _any_ path through the graph, an
`EndToEndTrace` is a path from the entry node to the exit node, denoting
full program execution.
Properties about graphs and language semantics (especially,
the fact that the graph contains the proper basic block and edges
to represent any program execution according to the
language's big-step semantics `EvalStmt`) is found
in `Spa/Language/Properties.lean`.
-/
namespace Spa namespace Spa
inductive Trace (g : Graph) : g.Index g.Index Env Env Prop /-- A partial trace through a graph `g`, starting right before
the execution of the basic block at the first index, and
ending right after the execution of the basic block at the last index. -/
inductive Trace (g : Graph) : g.Index g.Index Env Env Type
| single {ρ₁ ρ₂ : Env} {idx : g.Index} : | single {ρ₁ ρ₂ : Env} {idx : g.Index} :
EvalBasicStmts ρ₁ (g.nodes idx) ρ₂ Trace g idx idx ρ₁ ρ₂ EvalBasicStmtOpt ρ₁ (g.nodes idx) ρ₂ Trace g idx idx ρ₁ ρ₂
| edge {ρ₁ ρ₂ ρ₃ : Env} {idx₁ idx₂ idx₃ : g.Index} : | edge {ρ₁ ρ₂ ρ₃ : Env} {idx₁ idx₂ idx₃ : g.Index} :
EvalBasicStmts ρ₁ (g.nodes idx₁) ρ₂ (idx₁, idx₂) g.edges EvalBasicStmtOpt ρ₁ (g.nodes idx₁) ρ₂ (idx₁, idx₂) g.edges
Trace g idx₂ idx₃ ρ₂ ρ₃ Trace g idx₁ idx₃ ρ₁ ρ₃ Trace g idx₂ idx₃ ρ₂ ρ₃ Trace g idx₁ idx₃ ρ₁ ρ₃
lemma Trace.concat {g : Graph} {idx₁ idx₂ idx₃ idx₄ : g.Index} /-!
## Open Traces
A normal `Trace` starts right before one state, and ends right after another.
This is convenient for inductively proving correctness / sufficience, but
awkward because 1) no empty traces exist and 2) concatenation requires an extra
edge.
However, when attempting an "empty" trace, two types are equally possible:
traces that end _right before_ executing a state (`Traceₗ`) and
traces that begin _right after_ executing a state (`Traceᵣ`). They
are symmetric and can be concatenated with full traces on the left
and right, respectively. -/
/-- Left-open trace, representing execution that ends right before `idx₂`. -/
inductive Traceₗ (g : Graph) : g.Index g.Index Env Env Type where
| nil {idx : g.Index} {ρ : Env} : Traceₗ g idx idx ρ ρ
| cons {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
EvalBasicStmtOpt ρ₁ (g.nodes idx₁) ρ₂
(idx₁, idx₂) g.edges
Traceₗ g idx₂ idx₃ ρ₂ ρ₃ Traceₗ g idx₁ idx₃ ρ₁ ρ₃
def Traceₗ.single (g : Graph) (idx : g.Index) (ρ : Env) : Traceₗ g idx idx ρ ρ := .nil
/-- Right-open trace, representing execution that starts right after `idx₁`. -/
inductive Traceᵣ (g : Graph) : g.Index g.Index Env Env Type where
| nil {idx : g.Index} {ρ : Env} : Traceᵣ g idx idx ρ ρ
| cons {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
Traceᵣ g idx₁ idx₂ ρ₁ ρ₂
(idx₂, idx₃) g.edges
EvalBasicStmtOpt ρ₂ (g.nodes idx₃) ρ₃ Traceᵣ g idx₁ idx₃ ρ₁ ρ₃
def Traceᵣ.single (g : Graph) (idx : g.Index) (ρ : Env) : Traceᵣ g idx idx ρ ρ := .nil
/-- Sequence two traces together. Since the endpoint of the first trace
is _after_ its last basic block's execution, and the beginning of
the next trace is _before_ its first basic block's execution,
there must be an edge to connect the two. -/
def Trace.concat {g : Graph} {idx₁ idx₂ idx₃ idx₄ : g.Index}
{ρ₁ ρ₂ ρ₃ : Env} (tr₁ : Trace g idx₁ idx₂ ρ₁ ρ₂) {ρ₁ ρ₂ ρ₃ : Env} (tr₁ : Trace g idx₁ idx₂ ρ₁ ρ₂)
(he : (idx₂, idx₃) g.edges) (tr₂ : Trace g idx₃ idx₄ ρ₂ ρ₃) : (he : (idx₂, idx₃) g.edges) (tr₂ : Trace g idx₃ idx₄ ρ₂ ρ₃) :
Trace g idx₁ idx₄ ρ₁ ρ₃ := by Trace g idx₁ idx₄ ρ₁ ρ₃ :=
induction tr₁ with match tr₁ with
| single hbs => exact Trace.edge hbs he tr₂ | single hbs => edge hbs he tr₂
| edge hbs he' _ ih => exact Trace.edge hbs he' (ih he tr₂) | edge hbs he' tr₁' => edge hbs he' (tr₁'.concat he tr₂)
inductive EndToEndTrace (g : Graph) (ρ₁ ρ₂ : Env) : Prop scoped notation:65 tr₁:66 " ++< " he " >++ " tr₂:65 => Trace.concat tr₁ he tr₂
def Trace.addEdge {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ : Env} :
Trace g idx₁ idx₂ ρ₁ ρ₂
(idx₂, idx₃) g.edges
Traceₗ g idx₁ idx₃ ρ₁ ρ₂
| .single hnode, hedge => .cons hnode hedge .nil
| .edge hnode hedge' rest, hedge => .cons hnode hedge' (rest.addEdge hedge)
@[aesop simp]
def Traceₗ.append {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
Traceₗ g idx₁ idx₂ ρ₁ ρ₂ Traceₗ g idx₂ idx₃ ρ₂ ρ₃
Traceₗ g idx₁ idx₃ ρ₁ ρ₃
| .nil, rhs => rhs
| .cons hnode hedge rest, rhs => .cons hnode hedge (rest.append rhs)
@[simp] def traceₗ_append_nil {g : Graph} {idx₁ idx₂ : g.Index} {ρ₁ ρ₂ : Env}
{trₗ : Traceₗ g idx₁ idx₂ ρ₁ ρ₂} : trₗ.append Traceₗ.nil = trₗ := by
induction trₗ <;> aesop
def Traceₗ.appendTrace {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
Traceₗ g idx₁ idx₂ ρ₁ ρ₂ Trace g idx₂ idx₃ ρ₂ ρ₃
Trace g idx₁ idx₃ ρ₁ ρ₃
| .nil, rhs => rhs
| .cons hnode hedge rest, rhs => .edge hnode hedge (rest.appendTrace rhs)
def Traceₗ.appendStep {g : Graph} {idx₁ idx₂ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
Traceₗ g idx₁ idx₂ ρ₁ ρ₂ EvalBasicStmtOpt ρ₂ (g.nodes idx₂) ρ₃
Trace g idx₁ idx₂ ρ₁ ρ₃ := fun trₗ hbs => trₗ.appendTrace (Trace.single hbs)
def Trace.appendRight {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
Trace g idx₁ idx₂ ρ₁ ρ₂ Traceᵣ g idx₂ idx₃ ρ₂ ρ₃
Trace g idx₁ idx₃ ρ₁ ρ₃
| lhs, .nil => lhs
| lhs, .cons rest hedge hnode => Trace.concat (lhs.appendRight rest) hedge (.single hnode)
instance instHAppendTraceLTraceL {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
HAppend (Traceₗ g idx₁ idx₂ ρ₁ ρ₂) (Traceₗ g idx₂ idx₃ ρ₂ ρ₃) (Traceₗ g idx₁ idx₃ ρ₁ ρ₃) where
hAppend := Traceₗ.append
instance instHAppendTraceLTrace {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
HAppend (Traceₗ g idx₁ idx₂ ρ₁ ρ₂) (Trace g idx₂ idx₃ ρ₂ ρ₃) (Trace g idx₁ idx₃ ρ₁ ρ₃) where
hAppend := Traceₗ.appendTrace
instance instHAppendTraceLStep {g : Graph} {idx₁ idx₂ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
HAppend (Traceₗ g idx₁ idx₂ ρ₁ ρ₂) (EvalBasicStmtOpt ρ₂ (g.nodes idx₂) ρ₃) (Trace g idx₁ idx₂ ρ₁ ρ₃) where
hAppend := Traceₗ.appendStep
instance instHAppendTraceTraceR {g : Graph} {idx₁ idx₂ idx₃ : g.Index} {ρ₁ ρ₂ ρ₃ : Env} :
HAppend (Trace g idx₁ idx₂ ρ₁ ρ₂) (Traceᵣ g idx₂ idx₃ ρ₂ ρ₃) (Trace g idx₁ idx₃ ρ₁ ρ₃) where
hAppend := Trace.appendRight
/-!
## Trace Steps
Analyses that care about *which statements executed* (e.g. reaching
definitions) need to project a trace down to its list of executed statements.
Defining that projection here, once, as a chronological mathlib `List` means
all the re-association facts about concatenating traces come for free from
`List.append_assoc` and friends, instead of being re-proven per analysis. -/
/-- The (index, statement) pairs executed by a single optional-statement step:
none if the node is empty, and the node's statement otherwise. -/
def EvalBasicStmtOpt.steps {α : Type*} (idx : α) {ρ₁ ρ₂ : Env} {obs : Option BasicStmt} :
EvalBasicStmtOpt ρ₁ obs ρ₂ List (α × BasicStmt)
| .none => []
| .some (bs := bs) _ => [(idx, bs)]
/-- The statements executed by a left-open trace, in chronological order. -/
def Traceₗ.steps {g : Graph} {idx₁ idx₂ : g.Index} {ρ₁ ρ₂ : Env} :
Traceₗ g idx₁ idx₂ ρ₁ ρ₂ List (g.Index × BasicStmt)
| .nil => []
| .cons (idx₁ := idx) hnode _ rest => hnode.steps idx ++ rest.steps
/-- The statements executed by a trace, in chronological order. -/
def Trace.steps {g : Graph} {idx₁ idx₂ : g.Index} {ρ₁ ρ₂ : Env} :
Trace g idx₁ idx₂ ρ₁ ρ₂ List (g.Index × BasicStmt)
| .single (idx := idx) hnode => hnode.steps idx
| .edge (idx₁ := idx) hnode _ rest => hnode.steps idx ++ rest.steps
@[simp] lemma Traceₗ.steps_append {g : Graph} {idx₁ idx₂ idx₃ : g.Index}
{ρ₁ ρ₂ ρ₃ : Env} (tr₁ : Traceₗ g idx₁ idx₂ ρ₁ ρ₂)
(tr₂ : Traceₗ g idx₂ idx₃ ρ₂ ρ₃) :
(tr₁ ++ tr₂).steps = tr₁.steps ++ tr₂.steps := by
show (tr₁.append tr₂).steps = _
induction tr₁ <;> simp [Traceₗ.append, Traceₗ.steps, *]
@[simp] lemma Traceₗ.steps_appendTrace {g : Graph} {idx₁ idx₂ idx₃ : g.Index}
{ρ₁ ρ₂ ρ₃ : Env} (tr₁ : Traceₗ g idx₁ idx₂ ρ₁ ρ₂)
(tr₂ : Trace g idx₂ idx₃ ρ₂ ρ₃) :
(tr₁ ++ tr₂).steps = tr₁.steps ++ tr₂.steps := by
show (tr₁.appendTrace tr₂).steps = _
induction tr₁ <;> simp [Traceₗ.appendTrace, Traceₗ.steps, Trace.steps, *]
@[simp] lemma Traceₗ.steps_appendStep {g : Graph} {idx₁ idx₂ : g.Index}
{ρ₁ ρ₂ ρ₃ : Env} (tr : Traceₗ g idx₁ idx₂ ρ₁ ρ₂)
(hbs : EvalBasicStmtOpt ρ₂ (g.nodes idx₂) ρ₃) :
(tr ++ hbs).steps = tr.steps ++ hbs.steps idx₂ :=
Traceₗ.steps_appendTrace tr (Trace.single hbs)
@[simp] lemma Trace.steps_addEdge {g : Graph} {idx₁ idx₂ idx₃ : g.Index}
{ρ₁ ρ₂ : Env} (tr : Trace g idx₁ idx₂ ρ₁ ρ₂)
(hedge : (idx₂, idx₃) g.edges) :
(tr.addEdge hedge).steps = tr.steps := by
induction tr <;> simp [Trace.addEdge, Trace.steps, Traceₗ.steps, *]
@[simp] lemma Traceₗ.append_addEdge {g : Graph}
{idx₁ idx₂ idx₃ idx₄ : g.Index} {ρ₁ ρ₂ ρ₃ ρ₄ : Env}
(trₗ : Traceₗ g idx₁ idx₂ ρ₁ ρ₂)
(hnode : EvalBasicStmtOpt ρ₂ (g.nodes idx₂) ρ₃)
(hedge : (idx₂, idx₃) g.edges)
(rest : Traceₗ g idx₃ idx₄ ρ₃ ρ₄) :
trₗ.append (Traceₗ.cons hnode hedge rest) =
(Trace.addEdge (trₗ.appendStep hnode) hedge).append rest := by
induction trₗ <;> simp [Traceₗ.append, Traceₗ.appendStep, Traceₗ.appendTrace, Trace.addEdge, *]
@[simp] lemma Traceₗ.appendTrace_addEdge {g : Graph}
{idx₁ idx₂ idx₃ idx₄ : g.Index} {ρ₁ ρ₂ ρ₃ ρ₄ : Env}
(trₗ : Traceₗ g idx₁ idx₂ ρ₁ ρ₂)
(hnode : EvalBasicStmtOpt ρ₂ (g.nodes idx₂) ρ₃)
(hedge : (idx₂, idx₃) g.edges)
(rest : Trace g idx₃ idx₄ ρ₃ ρ₄) :
trₗ.appendTrace (Trace.edge hnode hedge rest) =
(Trace.addEdge (trₗ.appendStep hnode) hedge).appendTrace rest := by
induction trₗ <;> simp [Traceₗ.appendTrace, Traceₗ.appendStep, Trace.addEdge, *]
/-- A beginning-to-end trace corresponding to the CFG `g`. -/
inductive EndToEndTrace (g : Graph) (ρ₁ ρ₂ : Env) : Type
| intro (idx₁ : g.Index) (idx₁_mem : idx₁ g.inputs) | intro (idx₁ : g.Index) (idx₁_mem : idx₁ g.inputs)
(idx₂ : g.Index) (idx₂_mem : idx₂ g.outputs) (idx₂ : g.Index) (idx₂_mem : idx₂ g.outputs)
(trace : Trace g idx₁ idx₂ ρ₁ ρ₂) : EndToEndTrace g ρ₁ ρ₂ (trace : Trace g idx₁ idx₂ ρ₁ ρ₂) : EndToEndTrace g ρ₁ ρ₂
inductive Reaches {prog : Program} : {s₁ s₂ : prog.State} {ρ₁ ρ₂ : Env}
Trace prog.cfg s₁ s₂ ρ₁ ρ₂
(s : prog.State) (ρin ρout : Env) Type
| single_here {s₁ : prog.State} {ρ₁ ρ₂ : Env}
(hnode : EvalBasicStmtOpt ρ₁ (prog.code s₁) ρ₂) :
Reaches (.single hnode) s₁ ρ₁ ρ₂
| edge_here {s₁ s₂ s₃ : prog.State} {ρ₁ ρ₂ ρ₃ : Env}
(hnode : EvalBasicStmtOpt ρ₁ (prog.code s₁) ρ₂)
(hedge : (s₁, s₂) prog.cfg.edges) (rest : Trace prog.cfg s₂ s₃ ρ₂ ρ₃) :
Reaches (.edge hnode hedge rest) s₁ ρ₁ ρ₂
| edge_there {s₁ s₂ s₃ : prog.State} {ρ₁ ρ₂ ρ₃ : Env}
(hnode : EvalBasicStmtOpt ρ₁ (prog.code s₁) ρ₂)
(hedge : (s₁, s₂) prog.cfg.edges) (rest : Trace prog.cfg s₂ s₃ ρ₂ ρ₃)
{s : prog.State} {ρin ρout : Env} :
Reaches rest s ρin ρout
Reaches (.edge hnode hedge rest) s ρin ρout
def Reaches.pre {prog : Program} {s₁ s₂ s: prog.State}
{ρ₁ ρ₂ ρin ρout : Env} {tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂} :
(r : Reaches tr s ρin ρout) Traceₗ prog.cfg s₁ s ρ₁ ρin
| .single_here _ => .nil
| .edge_here _ _ _ => .nil
| .edge_there hnode hedge _ r => .cons hnode hedge r.pre
def Reaches.post {prog : Program} {s₁ s₂ s: prog.State}
{ρ₁ ρ₂ ρin ρout : Env} {tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂} :
(r : Reaches tr s ρin ρout) Trace prog.cfg s₁ s ρ₁ ρout
| .single_here hnode => .single hnode
| .edge_here hnode _ _ => .single hnode
| .edge_there hnode hedge _ r => .edge hnode hedge r.post
def Reaches.first {prog : Program} {s₁ s₂ s: prog.State}
{ρ₁ ρ₂ ρin ρout : Env} {tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂} :
(r : Reaches tr s ρin ρout) Σ ρ₁', Reaches tr s₁ ρ₁ ρ₁'
| .single_here hnode => _, .single_here hnode
| .edge_here hnode hedge hrest => _, .edge_here hnode hedge hrest
| .edge_there hnode hedge hrest tmp' => _, .edge_here hnode hedge hrest
def Reaches.step {prog : Program} {s₁ s₂ s: prog.State}
{ρ₁ ρ₂ ρin ρout : Env} {tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂} :
(r : Reaches tr s ρin ρout) EvalBasicStmtOpt ρin (prog.code s) ρout
| .single_here hnode => hnode
| .edge_here hnode hedge hrest => hnode
| .edge_there hnode hedge hrest tmp' => tmp'.step
end Spa end Spa

View File

@@ -12,6 +12,18 @@ etc.. What remains are a couple of theorems about folds, as well
as `FiniteHeightLattice`, the core concept of lattice-based static as `FiniteHeightLattice`, the core concept of lattice-based static
program analyses. See the documentation on that class for more information. -/ program analyses. See the documentation on that class for more information. -/
namespace Option
/-- Equality-sensitive eliminator for options in which the `some` case
is sensitive to the base `β`. This makes it mirror a one-element fold
more closely. -/
def elimEq {α : Type*} {β : Sort*} :
(o : Option α) β ((a : α) o = some a β β) β
| none, b, _ => b
| some a, b, f => f a rfl b
end Option
namespace Spa namespace Spa
/-- Predicate for binary functions independently monotone in both their arguments. -/ /-- Predicate for binary functions independently monotone in both their arguments. -/
@@ -61,6 +73,16 @@ lemma foldl_mono' (l : List α) (f : β → α → β)
| nil => exact hb | nil => exact hb
| cons x xs ih => exact ih (hf x hb) | cons x xs ih => exact ih (hf x hb)
omit [Preorder α] in
/-- The equality-aware eliminator (that also alters its behavior dependent on base case)
for option is monotonic. -/
lemma elimEq_self_mono (o : Option α) (g : (a : α) o = some a β β)
(hg : a h, Monotone (g a h)) :
Monotone (o.elimEq · g) := by
cases o with
| none => exact monotone_id
| some a => exact hg a rfl
end Folds end Folds
/-- Predicate on types with `Preorder` that claims all $<$ chains in the type have at most `n` comparisons. -/ /-- Predicate on types with `Preorder` that claims all $<$ chains in the type have at most `n` comparisons. -/
@@ -76,69 +98,53 @@ lemma boundedChains_of_subsingleton (α : Type*) [Preorder α] [Subsingleton α]
exact (c.step 0, by omega).ne (Subsingleton.elim _ _) exact (c.step 0, by omega).ne (Subsingleton.elim _ _)
/-- A finite height lattice is a lattice in which all chains $a < \ldots < z$ have a maximum height `height`. -/ /-- A finite height lattice is a lattice in which all chains $a < \ldots < z$ have a maximum height `height`. -/
class FiniteHeightLattice (α : Type*) extends Lattice α where class FiniteHeightLattice (α : Type*) extends Lattice α, OrderBot α, OrderTop α where
longestChain : LTSeries α height :
chains_bounded : BoundedChains α longestChain.length chains_bounded : BoundedChains α height
-- a < ... < z -- a < ... < z
-- ----------- length <= height -- ----------- length <= height
namespace FiniteHeightLattice namespace FiniteHeightLattice
def height (α : Type*) [FiniteHeightLattice α] : :=
(longestChain (α := α)).length
variable (α : Type*) [FiniteHeightLattice α]
instance (priority := 100) : Bot α := (longestChain (α := α)).head
instance (priority := 100) : Top α := (longestChain (α := α)).last
/-- The bottom element `⊥` of a finite height lattice is _actually_ the least element. -/
lemma bot_le (a : α) : ( : α) a := by
by_cases heq : a =
· exact inf_eq_left.mp heq
· exfalso
have hlt : a < (longestChain (α := α)).head :=
lt_of_le_of_ne inf_le_left heq
have hbound := chains_bounded ((longestChain (α := α)).cons ( a) hlt)
rw [RelSeries.cons_length] at hbound
omega
/-- The top element `` of a finite height lattice is _actually_ the greatest element. -/
lemma le_top (a : α) : a ( : α) := by
by_cases heq : a =
· exact sup_eq_right.mp heq
· exfalso
have hlt : (longestChain (α := α)).last < a :=
lt_of_le_of_ne le_sup_right (Ne.symm heq)
have hbound := chains_bounded ((longestChain (α := α)).snoc (a ) hlt)
rw [RelSeries.snoc_length] at hbound
omega
/-- This is something like a lemma about isomorphic types having the same height. /-- This is something like a lemma about isomorphic types having the same height.
Given a finite-height lattice `α`, lattice `β`, and a `Monotone` bijection Given a finite-height lattice `α`, lattice `β`, and a `Monotone` bijection
between the two, we can show that lattice `β` also has a finite height. between the two, we can show that lattice `β` also has a finite height.
The proof is fairly trivial: the longest chain in `α` can be transported The proof is fairly trivial: any chain in `β` can be transported to a chain in `α`,
to be a longest chain in `β` (by monotonicity), establishing a height witness.
At the same time, any chain in `β` can be transported to a chain in `α`,
and must be bounded by the same height by `FiniteHeightLattice.chains_bounded`. -/ and must be bounded by the same height by `FiniteHeightLattice.chains_bounded`. -/
def transport {α β : Type*} [Lattice β] def transport {α β : Type*} [Lattice β]
[I : FiniteHeightLattice α] (f : α β) (g : β α) [I : FiniteHeightLattice α] (f : α β) (g : β α)
(hf : Monotone f) (hg : Monotone g) (hf : Monotone f) (hg : Monotone g)
(hgf : Function.LeftInverse g f) (hfg : Function.LeftInverse f g) : (hfg : Function.LeftInverse f g) :
FiniteHeightLattice β where FiniteHeightLattice β where
toLattice := inferInstance toLattice := inferInstance
longestChain := toOrderBot := {
I.longestChain.map f (hf.strictMono_of_injective hgf.injective) bot := f ( : α)
bot_le := fun b => by
rw [ hfg b]
exact hf (_root_.bot_le : ( : α) g b) }
toOrderTop := {
top := f ( : α)
le_top := fun b => by
rw [ hfg b]
exact hf (_root_.le_top : g b ( : α)) }
height := I.height
chains_bounded := fun c => chains_bounded := fun c =>
I.chains_bounded (c.map g (hg.strictMono_of_injective hfg.injective)) I.chains_bounded (c.map g (hg.strictMono_of_injective hfg.injective))
/-- A `Unique` lattice trivially has finite height: its only chain is the singleton /-- A `Unique` lattice trivially has finite height: its only chain is the singleton
`[default]`, and there are no nontrivial `<` chains in a subsingleton. -/ `[default]`, and there are no nontrivial `<` chains in a subsingleton. -/
def ofUnique (α : Type*) [Lattice α] [Unique α] : FiniteHeightLattice α where def ofUnique (α : Type*) [Lattice α] [Unique α] :
FiniteHeightLattice α where
toLattice := inferInstance toLattice := inferInstance
longestChain := RelSeries.singleton _ default toOrderBot := {
bot := default
bot_le := fun _ => le_of_eq (Subsingleton.elim _ _) }
toOrderTop := {
top := default
le_top := fun _ => le_of_eq (Subsingleton.elim _ _) }
height := 0
chains_bounded := boundedChains_of_subsingleton α 0 chains_bounded := boundedChains_of_subsingleton α 0
end FiniteHeightLattice end FiniteHeightLattice

View File

@@ -1,7 +1,38 @@
import Spa.Lattice import Spa.Lattice
/-!
# The Above-Below Lattice
This file defines the `AboveBelow` lattice, which takes a flat domain
$a_1, \ldots, a_n \in \alpha$ and lifts it into a lattice bounded
above by a synthetic $\top$ element, and below by a synthetic $\bot$
element.
$$
\begin{array}{ccccc}
&& \top && \\
& \swarrow & \downarrow & \searrow & \\
a_1 & & … & & a_n \\
& \searrow & \downarrow & \swarrow & \\
&& \bot &&
\end{array}
$$
This lattice is also a `Spa.FiniteHeightLattice`, because no chain can
exceed the bottom-to-top chain $\bot < a_i < \top$.
The above-below lattice is helpful for for analyses such as
`Spa/Analysis/Sign.lean` and `Spa/Analysis/Constant.lean`, whose
classifications of values (by sign or by exact value) do not have
any inherent structure beyond "matching exactly".
-/
namespace Spa namespace Spa
/-- The above-below lattice, with bottom element `bot` and top element `top`. -/
@[aesop safe cases]
inductive AboveBelow (α : Type*) where inductive AboveBelow (α : Type*) where
| bot | bot
| top | top
@@ -48,37 +79,12 @@ instance : Min (AboveBelow α) where
@[simp] lemma mk_inf_mk (x y : α) : @[simp] lemma mk_inf_mk (x y : α) :
(mk x mk y : AboveBelow α) = if x = y then mk x else bot := rfl (mk x mk y : AboveBelow α) = if x = y then mk x else bot := rfl
protected lemma sup_comm (a b : AboveBelow α) : a b = b a := by protected lemma sup_comm (a b : AboveBelow α) : a b = b a := by aesop
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;> simp only protected lemma sup_assoc (a b c : AboveBelow α) : a b c = a (b c) := by aesop
[bot_sup, sup_bot, top_sup, sup_top, mk_sup_mk] protected lemma inf_comm (a b : AboveBelow α) : a b = b a := by aesop
split_ifs with h₁ h₂ h₂ <;> simp_all protected lemma inf_assoc (a b c : AboveBelow α) : a b c = a (b c) := by aesop
protected lemma sup_inf_self (a b : AboveBelow α) : a a b = a := by aesop
protected lemma sup_assoc (a b c : AboveBelow α) : a b c = a (b c) := by protected lemma inf_sup_self (a b : AboveBelow α) : a (a b) = a := by aesop
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;> rcases c with _ | _ | z <;>
simp only [bot_sup, sup_bot, top_sup, sup_top, mk_sup_mk]
split_ifs <;> simp_all
protected lemma inf_comm (a b : AboveBelow α) : a b = b a := by
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;> simp only
[bot_inf, inf_bot, top_inf, inf_top, mk_inf_mk]
split_ifs with h₁ h₂ h₂ <;> simp_all
protected lemma inf_assoc (a b c : AboveBelow α) : a b c = a (b c) := by
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;> rcases c with _ | _ | z <;>
simp only [bot_inf, inf_bot, top_inf, inf_top, mk_inf_mk]
split_ifs <;> simp_all
protected lemma sup_inf_self (a b : AboveBelow α) : a a b = a := by
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;>
simp only [bot_sup, sup_bot, top_sup, sup_top, mk_sup_mk,
bot_inf, inf_bot, top_inf, inf_top, mk_inf_mk] <;>
try (split_ifs <;> simp_all)
protected lemma inf_sup_self (a b : AboveBelow α) : a (a b) = a := by
rcases a with _ | _ | x <;> rcases b with _ | _ | y <;>
simp only [bot_sup, sup_bot, top_sup, sup_top, mk_sup_mk,
bot_inf, inf_bot, top_inf, inf_top, mk_inf_mk] <;>
try (split_ifs <;> simp_all)
instance : Lattice (AboveBelow α) := instance : Lattice (AboveBelow α) :=
Lattice.mk' AboveBelow.sup_comm AboveBelow.sup_assoc Lattice.mk' AboveBelow.sup_comm AboveBelow.sup_assoc
@@ -93,129 +99,80 @@ lemma bot_le' (a : AboveBelow α) : (bot : AboveBelow α) ≤ a :=
lemma le_top' (a : AboveBelow α) : a (top : AboveBelow α) := lemma le_top' (a : AboveBelow α) : a (top : AboveBelow α) :=
le_iff.mpr (sup_top a) le_iff.mpr (sup_top a)
lemma bot_lt_mk (x : α) : (bot : AboveBelow α) < mk x := instance : OrderBot (AboveBelow α) where
lt_of_le_of_ne (bot_le' _) (by simp) bot := bot
bot_le := bot_le'
lemma mk_lt_top (x : α) : (mk x : AboveBelow α) < top := instance : OrderTop (AboveBelow α) where
lt_of_le_of_ne (le_top' _) (by simp) top := top
le_top := le_top'
lemma bot_lt_top : (bot : AboveBelow α) < top := lemma bot_lt_mk (x : α) : (bot : AboveBelow α) < mk x := lt_of_le_of_ne (bot_le' _) (by simp)
lt_of_le_of_ne (bot_le' _) (by simp) lemma mk_lt_top (x : α) : (mk x : AboveBelow α) < top := lt_of_le_of_ne (le_top' _) (by simp)
lemma bot_lt_top : (bot : AboveBelow α) < top := lt_of_le_of_ne (bot_le' _) (by simp)
lemma le_cases {a b : AboveBelow α} (h : a b) : lemma le_cases {a b : AboveBelow α} (h : a b) :
a = bot b = top a = b := by a = bot b = top a = b := by
have hsup := le_iff.mp h rw [le_iff] at h
rcases a with _ | _ | x <;> rcases b with _ | _ | y rcases a with _ | _ | x <;> rcases b with _ | _ | y <;> simp_all
· exact Or.inl rfl
· exact Or.inr (Or.inl rfl)
· exact Or.inl rfl
· exact absurd hsup (by simp)
· exact Or.inr (Or.inl rfl)
· exact absurd hsup (by simp)
· exact absurd hsup (by simp)
· exact Or.inr (Or.inl rfl)
· rw [mk_sup_mk] at hsup
by_cases hxy : x = y
· exact Or.inr (Or.inr (by rw [hxy]))
· rw [if_neg hxy] at hsup
exact absurd hsup (by simp)
/-- Monotonicity for *strict* operations on flat lattices: if `f` sends `` to /-- If `f` sends `⊥` to `⊥` (in both arguments) and `` to ``
`⊥` (in either argument) and `` to `` (against any non-`⊥` argument), it is (against any non-`⊥` argument), it is monotone in both arguments.
monotone in both arguments — regardless of its values on plain elements. The values of the the elements in `α` are irrelevant since they
`Analysis/Sign.agda` and `Analysis/Constant.agda` postulated exactly these are always incomparable. This makes it easy to prove monotonicity
monotonicity facts for their `plus`/`minus`, all of which have this shape. -/ for operations that "just" combine their flat elements, or give up. -/
lemma monotone₂_of_strict {β γ : Type*} [DecidableEq β] [DecidableEq γ] lemma monotone₂_of_strict {β γ : Type*} [DecidableEq β] [DecidableEq γ]
(f : AboveBelow α AboveBelow β AboveBelow γ) (f : AboveBelow α AboveBelow β AboveBelow γ)
(hbotl : y, f bot y = bot) (hbotr : x, f x bot = bot) (hbotl : y, f bot y = bot) (hbotr : x, f x bot = bot)
(htopl : y, y bot f top y = top) (htopl : y, y bot f top y = top)
(htopr : x, x bot f x top = top) : Monotone₂ f := by (htopr : x, x bot f x top = top) : Monotone₂ f := by
constructor constructor <;> intro c a b hab <;>
· intro y a b hab rcases eq_or_ne c bot with rfl | hc <;>
show f a y f b y rcases le_cases hab with rfl | rfl | rfl <;>
rcases le_cases hab with rfl | rfl | rfl simp [hbotl, hbotr, htopl, htopr, bot_le', le_top', *]
· rw [hbotl]; exact bot_le' _
· rcases eq_or_ne y bot with rfl | hy
· rw [hbotr, hbotr]
· rw [htopl y hy]; exact le_top' _
· exact le_rfl
· intro x a b hab
show f x a f x b
rcases le_cases hab with rfl | rfl | rfl
· rw [hbotr]; exact bot_le' _
· rcases eq_or_ne x bot with rfl | hx
· rw [hbotl, hbotl]
· rw [htopr x hx]; exact le_top' _
· exact le_rfl
/-! ### Interpretations of flat lattices -/
section Interp section Interp
variable {V : Type*} {P : AboveBelow α V Prop} variable {V : Type*} {P : AboveBelow α V Prop}
/-- As long as the interpretation of a the above-below lattice respects the
fact that `bot` means "impossible", interpreting the above-below
lattice agrees with its `⊔`. -/
lemma interp_sup_of (hbot : v, ¬P bot v) (htop : v, P top v) lemma interp_sup_of (hbot : v, ¬P bot v) (htop : v, P top v)
{s₁ s₂ : AboveBelow α} (v : V) (h : P s₁ v P s₂ v) : P (s₁ s₂) v := by {s₁ s₂ : AboveBelow α} (v : V) (h : P s₁ v P s₂ v) : P (s₁ s₂) v := by aesop
rcases s₁ with _ | _ | x
· rw [bot_sup]; exact h.resolve_left (hbot v)
· rw [top_sup]; exact htop v
· rcases s₂ with _ | _ | y
· rw [sup_bot]; exact h.resolve_right (hbot v)
· rw [sup_top]; exact htop v
· rw [mk_sup_mk]
split
· next heq => subst heq; exact h.elim id id
· exact htop v
/-- As long as two distinct values in the flat domain don't overlap,
interpreting the above-below lattice agrees with its `⊔` -/
lemma interp_inf_of lemma interp_inf_of
(hdisj : {x y : α}, x y v, ¬(P (mk x) v P (mk y) v)) (hdisj : {x y : α}, x y v, ¬(P (mk x) v P (mk y) v))
{s₁ s₂ : AboveBelow α} (v : V) (h : P s₁ v P s₂ v) : P (s₁ s₂) v := by {s₁ s₂ : AboveBelow α} (v : V) (h : P s₁ v P s₂ v) : P (s₁ s₂) v := by
rcases s₁ with _ | _ | x rcases s₁ with _ | _ | x <;> rcases s₂ with _ | _ | y <;> simp_all
· rw [bot_inf]; exact h.1 split
· rw [top_inf]; exact h.2 · exact h.2
· rcases s₂ with _ | _ | y · next hne => exact (hdisj hne v h.1 h.2).elim
· rw [inf_bot]; exact h.2
· rw [inf_top]; exact h.1
· rw [mk_inf_mk]
split
· next heq => subst heq; exact h.1
· next hne => exact absurd h (hdisj hne v)
end Interp end Interp
/-- Rank of an element: `⊥ ↦ 0`, `[x] ↦ 1`, ` ↦ 2`. Used to bound chains /-- synthetic rank of an element, used to prove chain bounds. -/
(Agda's `isLongest` / `x≺[y]⇒x≡⊥` / `[x]≺y⇒y≡` case analysis lives here). -/ private def rank : AboveBelow α
def rank : AboveBelow α
| bot => 0 | bot => 0
| mk _ => 1 | mk _ => 1
| top => 2 | top => 2
/-- Agda: the impossibility of `[x] ≺ [y]` (combines `x≺[y]⇒x≡⊥` and /-- It's not possible for any two lifted flat-domain elements to be less
`[x]≺y⇒y≡`: the flat middle layer is an antichain). -/ than one another. -/
lemma not_mk_lt_mk (x y : α) : ¬(mk x : AboveBelow α) < mk y := by lemma not_mk_lt_mk (x y : α) : ¬(mk x : AboveBelow α) < mk y := by
intro h intro h
obtain hle, hne := lt_iff_le_and_ne.mp h obtain hle, hne := lt_iff_le_and_ne.mp h
have hsup := le_iff.mp hle rcases le_cases hle with h | h | h <;> simp_all
rw [mk_sup_mk] at hsup
by_cases hxy : x = y
· rw [if_pos hxy] at hsup
exact hne hsup
· rw [if_neg hxy] at hsup
exact absurd hsup (by simp)
/-- The rank of elements is strictly monotonic. -/
lemma rank_strictMono : StrictMono (rank : AboveBelow α ) := by lemma rank_strictMono : StrictMono (rank : AboveBelow α ) := by
intro a b hab intro a b hab
rcases a with _ | _ | x <;> rcases b with _ | _ | y rcases a with _ | _ | x <;> rcases b with _ | _ | y <;>
· exact absurd hab (lt_irrefl _) simp_all [rank, not_mk_lt_mk, (bot_le' _).not_lt, (le_top' _).not_lt]
· simp [rank]
· simp [rank]
· exact absurd hab (bot_le' _).not_lt
· exact absurd hab (lt_irrefl _)
· exact absurd hab (le_top' _).not_lt
· exact absurd hab (bot_le' _).not_lt
· simp [rank]
· exact absurd hab (not_mk_lt_mk x y)
/-- All chains in the above-below lattice have at most 2 comparisons. -/
lemma boundedChains : BoundedChains (AboveBelow α) 2 := fun c => by lemma boundedChains : BoundedChains (AboveBelow α) 2 := fun c => by
have h := LTSeries.head_add_length_le_nat (c.map rank rank_strictMono) have h := LTSeries.head_add_length_le_nat (c.map rank rank_strictMono)
rw [LTSeries.head_map, LTSeries.last_map, LTSeries.map_length] at h rw [LTSeries.head_map, LTSeries.last_map, LTSeries.map_length] at h
@@ -224,10 +181,9 @@ lemma boundedChains : BoundedChains (AboveBelow α) 2 := fun c => by
instance [Inhabited α] : FiniteHeightLattice (AboveBelow α) where instance [Inhabited α] : FiniteHeightLattice (AboveBelow α) where
toLattice := inferInstance toLattice := inferInstance
longestChain := toOrderBot := inferInstance
((RelSeries.singleton _ bot).snoc (mk default) toOrderTop := inferInstance
(by rw [RelSeries.last_singleton]; exact bot_lt_mk default)).snoc top height := 2
(by rw [RelSeries.last_snoc]; exact mk_lt_top default)
chains_bounded := boundedChains chains_bounded := boundedChains
end AboveBelow end AboveBelow

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@@ -29,8 +29,9 @@ lemma boundedChains : BoundedChains Bool 1 := fun c => by
instance : FiniteHeightLattice Bool where instance : FiniteHeightLattice Bool where
toLattice := inferInstance toLattice := inferInstance
longestChain := (RelSeries.singleton _ ( : Bool)).snoc ( : Bool) toOrderBot := inferInstance
(by rw [RelSeries.last_singleton]; exact bot_lt_top) toOrderTop := inferInstance
height := 1
chains_bounded := boundedChains chains_bounded := boundedChains
end Bool end Bool

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@@ -1,64 +1,79 @@
import Spa.Lattice.Tuple import Spa.Lattice.Tuple
import Mathlib.Data.List.Nodup import Mathlib.Data.List.Nodup
/-!
# Finite Maps
This file defines _finite maps_, or key-value maps with a finite domain. This
is encoded as a map from `Fin` into the value type. Finite maps form a
lattice from pointwise composition: $(f \land g) k = f k \land g k$,
and, provided the domain `\beta` is of finite height, so is the map
lattice as a whole.
In fact, the isomorphism is described and proven in `Spa/Lattice/Tuple.lean`.
-/
namespace Spa namespace Spa
def FiniteMap (A B : Type*) (ks : List A) : Type _ := Fin ks.length B /-- Key-value map with domain `α` and codomain `β`, with possible keys $\textit{ks} \subseteq \alpha$. -/
def FiniteMap (α β : Type*) (ks : List α) : Type _ := Fin ks.length β
namespace FiniteMap namespace FiniteMap
variable {A B : Type*} {ks : List A} variable {α β : Type*} {ks : List α}
instance [Lattice B] : Lattice (FiniteMap A B ks) := instance [Lattice β] : Lattice (FiniteMap α β ks) :=
inferInstanceAs (Lattice (Fin ks.length B)) inferInstanceAs (Lattice (Fin ks.length β))
instance [FiniteHeightLattice B] : FiniteHeightLattice (FiniteMap A B ks) := instance [FiniteHeightLattice β] : FiniteHeightLattice (FiniteMap α β ks) :=
inferInstanceAs (FiniteHeightLattice (Fin ks.length B)) inferInstanceAs (FiniteHeightLattice (Fin ks.length β))
instance [DecidableEq B] : DecidableEq (FiniteMap A B ks) := instance [DecidableEq β] : DecidableEq (FiniteMap α β ks) :=
inferInstanceAs (DecidableEq (Fin ks.length B)) inferInstanceAs (DecidableEq (Fin ks.length β))
instance : Membership (A × B) (FiniteMap A B ks) := instance : Membership (α × β) (FiniteMap α β ks) :=
fun fm p => i : Fin ks.length, ks.get i = p.1 fm i = p.2 fun fm p => i : Fin ks.length, ks.get i = p.1 fm i = p.2
lemma mem_iff {fm : FiniteMap A B ks} {p : A × B} : lemma mem_iff {fm : FiniteMap α β ks} {p : α × β} :
p fm i : Fin ks.length, ks.get i = p.1 fm i = p.2 := Iff.rfl p fm i : Fin ks.length, ks.get i = p.1 fm i = p.2 := Iff.rfl
def MemKey (k : A) (_fm : FiniteMap A B ks) : Prop := k ks def MemKey (k : α) (_fm : FiniteMap α β ks) : Prop := k ks
lemma MemKey_iff {k : A} {fm : FiniteMap A B ks} : MemKey k fm k ks := Iff.rfl lemma MemKey_iff {k : α} {fm : FiniteMap α β ks} : MemKey k fm k ks := Iff.rfl
instance {k : A} {fm : FiniteMap A B ks} [DecidableEq A] : Decidable (MemKey k fm) := instance {k : α} {fm : FiniteMap α β ks} [DecidableEq α] : Decidable (MemKey k fm) :=
decidable_of_iff _ MemKey_iff.symm decidable_of_iff _ MemKey_iff.symm
lemma mem_key_of_mem {k : A} {v : B} {fm : FiniteMap A B ks} lemma mem_key_of_mem {k : α} {v : β} {fm : FiniteMap α β ks}
(h : (k, v) fm) : MemKey k fm := by (h : (k, v) fm) : MemKey k fm := by
obtain i, hi, _ := h obtain i, hi, _ := h
have hik : ks.get i = k := hi have hik : ks.get i = k := hi
exact hik ks.get_mem i exact hik ks.get_mem i
def toList (fm : FiniteMap A B ks) : List (A × B) := def toList (fm : FiniteMap α β ks) : List (α × β) :=
(List.finRange ks.length).map fun i => (ks.get i, fm i) (List.finRange ks.length).map fun i => (ks.get i, fm i)
lemma le_def [Lattice B] {fm₁ fm₂ : FiniteMap A B ks} : lemma le_def [Lattice β] {fm₁ fm₂ : FiniteMap α β ks} :
fm₁ fm₂ i, fm₁ i fm₂ i := Iff.rfl fm₁ fm₂ i, fm₁ i fm₂ i := Iff.rfl
section Locate section Locate
variable [DecidableEq A] variable [DecidableEq α]
/-- Recover the value stored under a present key. -/ /-- Recover the value stored under a present key. -/
def locate {k : A} {fm : FiniteMap A B ks} (h : MemKey k fm) : def locate {k : α} {fm : FiniteMap α β ks} (h : MemKey k fm) :
{v : B // (k, v) fm} := {v : β // (k, v) fm} :=
let i : Fin ks.length := ks.idxOf k, List.idxOf_lt_length_iff.mpr h let i : Fin ks.length := ks.idxOf k, List.idxOf_lt_length_iff.mpr h
fm i, i, List.idxOf_get _, rfl fm i, i, List.idxOf_get _, rfl
end Locate end Locate
variable [Lattice B] variable [Lattice β]
lemma le_of_mem_mem (hks : ks.Nodup) {fm₁ fm₂ : FiniteMap A B ks} lemma le_of_mem_mem (hks : ks.Nodup) {fm₁ fm₂ : FiniteMap α β ks}
(hle : fm₁ fm₂) {k : A} {v₁ v₂ : B} (hle : fm₁ fm₂) {k : α} {v₁ v₂ : β}
(h₁ : (k, v₁) fm₁) (h₂ : (k, v₂) fm₂) : v₁ v₂ := by (h₁ : (k, v₁) fm₁) (h₂ : (k, v₂) fm₂) : v₁ v₂ := by
obtain i, hi, rfl := h₁ obtain i, hi, rfl := h₁
obtain j, hj, rfl := h₂ obtain j, hj, rfl := h₂
@@ -66,38 +81,44 @@ lemma le_of_mem_mem (hks : ks.Nodup) {fm₁ fm₂ : FiniteMap A B ks}
subst hij subst hij
exact le_def.mp hle i exact le_def.mp hle i
lemma mem_sup {fm₁ fm₂ : FiniteMap A B ks} {k : A} {v : B} lemma mem_sup {fm₁ fm₂ : FiniteMap α β ks} {k : α} {v : β}
(h : (k, v) fm₁ fm₂) : (h : (k, v) fm₁ fm₂) :
v₁ v₂, v = v₁ v₂ (k, v₁) fm₁ (k, v₂) fm₂ := by v₁ v₂, v = v₁ v₂ (k, v₁) fm₁ (k, v₂) fm₂ := by
obtain i, hi, rfl := h obtain i, hi, rfl := h
exact fm₁ i, fm₂ i, rfl, i, hi, rfl, i, hi, rfl exact fm₁ i, fm₂ i, rfl, i, hi, rfl, i, hi, rfl
lemma mem_inf {fm₁ fm₂ : FiniteMap α β ks} {k : α} {v : β}
(h : (k, v) fm₁ fm₂) :
v₁ v₂, v = v₁ v₂ (k, v₁) fm₁ (k, v₂) fm₂ := by
obtain i, hi, rfl := h
exact fm₁ i, fm₂ i, rfl, i, hi, rfl, i, hi, rfl
section Updating section Updating
variable [DecidableEq A] variable [DecidableEq α]
def updating (fm : FiniteMap A B ks) (ks' : List A) (g : A B) : FiniteMap A B ks := def updating (fm : FiniteMap α β ks) (ks' : List α) (g : α β) : FiniteMap α β ks :=
fun i => if ks.get i ks' then g (ks.get i) else fm i fun i => if ks.get i ks' then g (ks.get i) else fm i
omit [Lattice B] in omit [Lattice β] in
lemma eq_of_mem_updating {k : A} {v : B} {fm : FiniteMap A B ks} lemma eq_of_mem_updating {k : α} {v : β} {fm : FiniteMap α β ks}
{ks' : List A} {g : A B} (hk : k ks') {ks' : List α} {g : α β} (hk : k ks')
(h : (k, v) updating fm ks' g) : v = g k := by (h : (k, v) updating fm ks' g) : v = g k := by
obtain i, hi, rfl := h obtain i, hi, rfl := h
show (if ks.get i ks' then g (ks.get i) else fm i) = g k show (if ks.get i ks' then g (ks.get i) else fm i) = g k
rw [if_pos (by rw [hi]; exact hk), hi] rw [if_pos (by rw [hi]; exact hk), hi]
omit [Lattice B] in omit [Lattice β] in
lemma mem_of_mem_updating {k : A} {v : B} {fm : FiniteMap A B ks} lemma mem_of_mem_updating {k : α} {v : β} {fm : FiniteMap α β ks}
{ks' : List A} {g : A B} (hk : k ks') {ks' : List α} {g : α β} (hk : k ks')
(h : (k, v) updating fm ks' g) : (k, v) fm := by (h : (k, v) updating fm ks' g) : (k, v) fm := by
obtain i, hi, rfl := h obtain i, hi, rfl := h
refine i, hi, ?_ refine i, hi, ?_
show fm i = (if ks.get i ks' then g (ks.get i) else fm i) show fm i = (if ks.get i ks' then g (ks.get i) else fm i)
rw [if_neg (by rw [hi]; exact hk)] rw [if_neg (by rw [hi]; exact hk)]
lemma updating_mono {fm₁ fm₂ : FiniteMap A B ks} {ks' : List A} lemma updating_mono {fm₁ fm₂ : FiniteMap α β ks} {ks' : List α}
{g₁ g₂ : A B} (hfm : fm₁ fm₂) (hg : k, g₁ k g₂ k) : {g₁ g₂ : α β} (hfm : fm₁ fm₂) (hg : k, g₁ k g₂ k) :
updating fm₁ ks' g₁ updating fm₂ ks' g₂ := by updating fm₁ ks' g₁ updating fm₂ ks' g₂ := by
rw [le_def] rw [le_def]
intro i intro i
@@ -111,25 +132,25 @@ end Updating
section GeneralizedUpdate section GeneralizedUpdate
variable [DecidableEq A] {L : Type*} [Lattice L] variable [DecidableEq α] {L : Type*} [Lattice L]
def generalizedUpdate (f : L FiniteMap A B ks) (g : A L B) def generalizedUpdate (f : L FiniteMap α β ks) (g : α L β)
(ks' : List A) : L FiniteMap A B ks := fun l => (ks' : List α) : L FiniteMap α β ks := fun l =>
(f l).updating ks' (fun k => g k l) (f l).updating ks' (fun k => g k l)
variable {f : L FiniteMap A B ks} {g : A L B} {ks' : List A} variable {f : L FiniteMap α β ks} {g : α L β} {ks' : List α}
lemma generalizedUpdate_monotone (hf : Monotone f) lemma generalizedUpdate_monotone (hf : Monotone f)
(hg : k, Monotone (g k)) : Monotone (generalizedUpdate f g ks') := (hg : k, Monotone (g k)) : Monotone (generalizedUpdate f g ks') :=
fun _ _ hl => updating_mono (hf hl) (fun k => hg k hl) fun _ _ hl => updating_mono (hf hl) (fun k => hg k hl)
omit [Lattice B] [Lattice L] in omit [Lattice β] [Lattice L] in
lemma generalizedUpdate_mem_eq {k : A} {v : B} {l : L} (hk : k ks') lemma generalizedUpdate_mem_eq {k : α} {v : β} {l : L} (hk : k ks')
(h : (k, v) generalizedUpdate f g ks' l) : v = g k l := (h : (k, v) generalizedUpdate f g ks' l) : v = g k l :=
eq_of_mem_updating (g := fun k => g k l) hk h eq_of_mem_updating (g := fun k => g k l) hk h
omit [Lattice B] [Lattice L] in omit [Lattice β] [Lattice L] in
lemma generalizedUpdate_not_mem_backward {k : A} {v : B} {l : L} (hk : k ks') lemma generalizedUpdate_not_mem_backward {k : α} {v : β} {l : L} (hk : k ks')
(h : (k, v) generalizedUpdate f g ks' l) : (k, v) f l := (h : (k, v) generalizedUpdate f g ks' l) : (k, v) f l :=
mem_of_mem_updating hk h mem_of_mem_updating hk h
@@ -137,19 +158,19 @@ end GeneralizedUpdate
section ValuesAt section ValuesAt
variable [DecidableEq A] variable [DecidableEq α]
/-- The value stored under `k`, if `k` is a key. -/ /-- The value stored under `k`, if `k` is a key. -/
private def lookup (fm : FiniteMap A B ks) (k : A) : Option B := private def lookup (fm : FiniteMap α β ks) (k : α) : Option β :=
if h : k ks then some (fm ks.idxOf k, List.idxOf_lt_length_iff.mpr h) else none if h : k ks then some (fm ks.idxOf k, List.idxOf_lt_length_iff.mpr h) else none
/-- The values stored under the keys `ks'` (skipping any that are not keys). -/ /-- The values stored under the keys `ks'` (skipping any that are not keys). -/
def valuesAt (fm : FiniteMap A B ks) (ks' : List A) : List B := def valuesAt (fm : FiniteMap α β ks) (ks' : List α) : List β :=
ks'.filterMap fm.lookup ks'.filterMap fm.lookup
omit [Lattice B] in omit [Lattice β] in
lemma mem_valuesAt (hks : ks.Nodup) {fm : FiniteMap A B ks} {k : A} {v : B} lemma mem_valuesAt (hks : ks.Nodup) {fm : FiniteMap α β ks} {k : α} {v : β}
{ks' : List A} (hk : k ks') (h : (k, v) fm) : v valuesAt fm ks' := by {ks' : List α} (hk : k ks') (h : (k, v) fm) : v valuesAt fm ks' := by
refine List.mem_filterMap.mpr k, hk, ?_ refine List.mem_filterMap.mpr k, hk, ?_
obtain i, hi, rfl := h obtain i, hi, rfl := h
have hik : ks.get i = k := hi have hik : ks.get i = k := hi
@@ -161,7 +182,7 @@ lemma mem_valuesAt (hks : ks.Nodup) {fm : FiniteMap A B ks} {k : A} {v : B}
hks.get_inj_iff.mp (by rw [List.idxOf_get, hi]) hks.get_inj_iff.mp (by rw [List.idxOf_get, hi])
rw [this] rw [this]
private lemma lookup_rel {fm₁ fm₂ : FiniteMap A B ks} (hle : fm₁ fm₂) (k : A) : private lemma lookup_rel {fm₁ fm₂ : FiniteMap α β ks} (hle : fm₁ fm₂) (k : α) :
Option.Rel (· ·) (fm₁.lookup k) (fm₂.lookup k) := by Option.Rel (· ·) (fm₁.lookup k) (fm₂.lookup k) := by
show Option.Rel _ show Option.Rel _
(if h : k ks then some (fm₁ ks.idxOf k, List.idxOf_lt_length_iff.mpr h) else none) (if h : k ks then some (fm₁ ks.idxOf k, List.idxOf_lt_length_iff.mpr h) else none)
@@ -170,8 +191,8 @@ private lemma lookup_rel {fm₁ fm₂ : FiniteMap A B ks} (hle : fm₁ ≤ fm₂
· rw [dif_pos hk, dif_pos hk]; exact Option.Rel.some (le_def.mp hle _) · rw [dif_pos hk, dif_pos hk]; exact Option.Rel.some (le_def.mp hle _)
· rw [dif_neg hk, dif_neg hk]; exact Option.Rel.none · rw [dif_neg hk, dif_neg hk]; exact Option.Rel.none
lemma valuesAt_le {fm₁ fm₂ : FiniteMap A B ks} (hle : fm₁ fm₂) lemma valuesAt_le {fm₁ fm₂ : FiniteMap α β ks} (hle : fm₁ fm₂)
(ks' : List A) : (ks' : List α) :
List.Forall₂ (· ·) (valuesAt fm₁ ks') (valuesAt fm₂ ks') := by List.Forall₂ (· ·) (valuesAt fm₁ ks') (valuesAt fm₂ ks') := by
induction ks' with induction ks' with
| nil => exact List.Forall₂.nil | nil => exact List.Forall₂.nil

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@@ -0,0 +1,38 @@
import Spa.Lattice
import Mathlib.Data.Finset.Lattice.Basic
import Mathlib.Data.Fintype.Lattice
import Mathlib.Data.Fintype.Card
/-! # Power Sets of Finite Type
For a `Fintype α`, `Finset α` is the power-set lattice: `⊔` is union, `⊓` is
intersection, `⊥ = ∅`, ` = univ`. This lattice also has a finite height.
The `Finset α` representation s isomorphic to `Fin α → Bool`, but far more
efficient because it avoids building up stacks of layered closures. -/
namespace Spa
variable {α : Type*} [Fintype α] [DecidableEq α]
omit [Fintype α] [DecidableEq α] in
private lemma finset_card_strictMono : StrictMono (Finset.card : Finset α ) :=
fun _ _ h => Finset.card_lt_card h
omit [DecidableEq α] in
/-- A strictly increasing chain of finsets grows its cardinality by at least one
each step, and cardinality is capped by `Fintype.card α`. -/
lemma finset_boundedChains : BoundedChains (Finset α) (Fintype.card α) := fun c => by
have h := LTSeries.head_add_length_le_nat (c.map Finset.card finset_card_strictMono)
rw [LTSeries.head_map, LTSeries.last_map, LTSeries.map_length] at h
have h2 : c.last.card Fintype.card α := Finset.card_le_univ _
omega
instance instFiniteHeightFinset : FiniteHeightLattice (Finset α) where
toLattice := inferInstance
toOrderBot := inferInstance
toOrderTop := inferInstance
height := Fintype.card α
chains_bounded := finset_boundedChains
end Spa

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@@ -107,62 +107,18 @@ section FiniteHeight
variable [FiniteHeightLattice β] variable [FiniteHeightLattice β]
private lemma consBot_strictMono {n : } :
StrictMono (fun b : β => (Fin.cons b ( : Fin n β) : Fin (n + 1) β)) := by
intro a b hab
refine lt_iff_le_and_ne.mpr ?_, ?_
· refine Pi.le_def.mpr (fun i => Fin.cases ?_ (fun j => ?_) i)
· simpa using hab.le
· simp
· exact fun h => hab.ne (by simpa using congrFun h 0)
private lemma consTop_strictMono {n : } :
StrictMono (fun f : Fin n β => (Fin.cons ( : β) f : Fin (n + 1) β)) := by
intro f g hfg
refine lt_iff_le_and_ne.mpr ?_, ?_
· refine Pi.le_def.mpr (fun i => Fin.cases ?_ (fun j => ?_) i)
· simp
· simpa using Pi.le_def.mp hfg.le j
· intro h
apply hfg.ne
funext j
simpa using congrFun h j.succ
/-- The maximal chain in `Fin n → β`: walk the first tuple element from `⊥` to ``
through `β`'s longest chain, then do that with the second element, and so on. -/
private def stdChain : (n : )
{ s : LTSeries (Fin n β) //
s.head = ( : Fin n β)
s.length = n * (FiniteHeightLattice.longestChain (α := β)).length }
| 0 => RelSeries.singleton _ , by rw [RelSeries.head_singleton], by simp
| n + 1 =>
let prev := stdChain n
RelSeries.smash
((FiniteHeightLattice.longestChain (α := β)).map
(fun b => (Fin.cons b ( : Fin n β) : Fin (n + 1) β)) consBot_strictMono)
(prev.1.map (fun f => (Fin.cons ( : β) f : Fin (n + 1) β)) consTop_strictMono)
(by rw [LTSeries.last_map, LTSeries.head_map, prev.2.1]; rfl),
by
simp only [RelSeries.head_smash, LTSeries.head_map]
rw [show (FiniteHeightLattice.longestChain (α := β)).head = ( : β) from rfl]
funext i
refine Fin.cases ?_ (fun j => ?_) i <;> simp [Pi.bot_apply],
by
show (FiniteHeightLattice.longestChain (α := β)).length + prev.1.length
= (n + 1) * (FiniteHeightLattice.longestChain (α := β)).length
rw [prev.2.2, Nat.succ_mul]; exact Nat.add_comm _ _
instance instFiniteHeight {n : } : FiniteHeightLattice (Fin n β) where instance instFiniteHeight {n : } : FiniteHeightLattice (Fin n β) where
toLattice := inferInstance toLattice := inferInstance
longestChain := (stdChain n).1 toOrderBot := inferInstance
toOrderTop := inferInstance
height := n * FiniteHeightLattice.height (α := β)
chains_bounded := fun c => by chains_bounded := fun c => by
obtain cs, _, _, hbound := exists_unzip c obtain cs, _, _, hbound := exists_unzip c
refine hbound.trans ?_ refine hbound.trans ?_
rw [(stdChain n).2.2]
calc i, (cs i).length calc i, (cs i).length
_i : Fin n, (FiniteHeightLattice.longestChain (α := β)).length := _i : Fin n, FiniteHeightLattice.height (α := β) :=
Finset.sum_le_sum (fun i _ => FiniteHeightLattice.chains_bounded (cs i)) Finset.sum_le_sum (fun i _ => FiniteHeightLattice.chains_bounded (cs i))
_ = n * (FiniteHeightLattice.longestChain (α := β)).length := by _ = n * FiniteHeightLattice.height (α := β) := by
simp [Finset.sum_const, Finset.card_univ, Fintype.card_fin] simp [Finset.sum_const, Finset.card_univ, Fintype.card_fin]
end FiniteHeight end FiniteHeight

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import Spa.Analysis.Reaching
import Spa.Language.Tagged.Graphs
/-!
# Finding loop-invariant assignments (LICM groundwork)
This wires the **reaching-definitions** analysis (`Spa/Analysis/Reaching.lean`)
to the **tagged AST** to *find* — not yet move — assignments inside a `while`
loop whose right-hand side depends only on definitions made *outside* the loop.
These are the candidates a later LICM pass could hoist.
The pipeline, for each assignment immediately enclosed by a loop:
1. locate its CFG state via the tagged-graph bridge (`Program.stateOfNodeId`);
2. read the reaching definitions at the assignment's *entry*
(`joinForKey s result` — the join over predecessors, i.e. before the
assignment itself runs);
3. union the definition sets of the RHS variables;
4. map each definition site back to its `RawId` (`Program.nodeIdOf`) and check
it is **not** inside the loop body (structural `subtreeIds` membership).
If every reaching definition of every RHS variable lies outside the loop, the
assignment is reported as loop-invariant. This is the first-order check ("all
reaching definitions outside the loop"); transitive/iterated invariance and the
actual hoisting are out of scope here.
-/
namespace Spa
namespace LicmTransformation
open Forward
/-- An assignment found inside a loop, paired with the data needed to test its
invariance against that (immediately enclosing) loop. -/
structure Candidate (prog : Program) where
/-- The enclosing `whileLoop`'s tag (for reporting). -/
loopId : prog.NodeId
/-- Every node id inside the loop body (the "is-child-of-loop" set). -/
bodyIds : List prog.NodeId
/-- The assignment `BasicStmt`'s tag — what labels its CFG node. -/
assignId : prog.NodeId
/-- The variables read by the assignment's RHS. -/
rhsVars : List String
/-- Collect every assignment together with its *immediately enclosing* loop.
`enclosing` carries the current loop's tag and body id-set, or `none` outside any
loop (in which case assignments are skipped — only in-loop assignments are
candidates). -/
def collectCandidates (prog : Program) (enc : Option (prog.NodeId × List prog.NodeId)) :
Stmt.Tagged prog.NodeId List (Candidate prog)
| .basic _ bs =>
match bs, enc with
| .assign t _ e, some (loopId, bodyIds) =>
[{ loopId := loopId, bodyIds := bodyIds, assignId := t,
rhsVars := e.erase.vars.sort (· ·) }]
| _, _ => []
| .andThen _ a b => collectCandidates prog enc a ++ collectCandidates prog enc b
| .ifElse _ _ a b => collectCandidates prog enc a ++ collectCandidates prog enc b
| .whileLoop loopT _ body =>
collectCandidates prog (some (loopT, body.subtreeIds)) body
/-- Read the definition set assigned to variable `k`, or `⊥` if absent. -/
def lookupDef (prog : Program) (vs : VariableValues (DefSet prog) prog)
(k : String) : DefSet prog :=
if h : FiniteMap.MemKey k vs then (FiniteMap.locate h).1 else
/-- The AST node ids marked as definition sites in a `DefSet`. With the
`Finset`-of-AST-ids lattice these are just the elements of the set. -/
def defSites (prog : Program) (d : DefSet prog) : List prog.NodeId :=
(List.finRange prog.size).filter (fun i => decide (i d))
/-- Is the candidate assignment loop-invariant: do all reaching definitions of
its RHS variables lie outside the loop body? Reaching sets are now keyed by AST
node id, so we compare against the loop-body ids directly (embedding the raw
body ids into `p.NodeId`). -/
def isInvariant (prog : Program) (c : Candidate prog) : Bool :=
match prog.stateOfNodeId c.assignId with
| none => false
| some s =>
let entry := joinForKey s (result (DefSet prog) prog)
let combined : DefSet prog :=
c.rhsVars.foldl (fun acc k => acc lookupDef prog entry k)
(defSites prog combined).all (fun nid => ! decide (nid c.bodyIds))
/-- The loop-invariant assignments of `prog`, as `(loopId, assignId)` pairs. -/
def licmCandidates (prog : Program) : List (prog.NodeId × prog.NodeId) :=
(collectCandidates prog none prog.taggedFin).filterMap (fun c =>
if isInvariant prog c then some (c.loopId, c.assignId) else none)
/-- A human-readable report of the loop-invariant assignments. -/
def output (prog : Program) : String :=
match licmCandidates prog with
| [] => "no loop-invariant assignments found"
| cands =>
"loop-invariant assignments (loop ↦ assignment):\n" ++
String.intercalate "\n"
(cands.map (fun p => s!" loop #{p.1.val}: assignment #{p.2.val}"))
end LicmTransformation
end Spa