43 Commits

Author SHA1 Message Date
53f8bd47dc Add function back in to Embedding 2026-08-09 21:43:20 -05:00
fd371ba175 Remove trace suffix from Reaching type 2026-08-09 21:23:21 -05:00
df4d072f22 Clean up comments in Graphs.lean and Program.lean 2026-08-09 18:17:02 -05:00
c0542d0811 Allow negative numbers in expressions 2026-08-09 17:51:58 -05:00
a19f9fa148 Get rid of Tagged 2026-08-09 17:38:56 -05:00
269906871f Update LICM/Reaching to node use NodeId 2026-08-09 17:35:30 -05:00
1eecf45c0f Add more machinery to use embeddings as "proofs of child-ship" 2026-08-09 17:30:38 -05:00
827d55c6b6 Switch embeddings to index-offset.
This is a special case of an embedding, but it has the nice
property for checking inclusion.
2026-08-09 17:23:46 -05:00
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
a5f533d67a Use a direct N-way unzip instead of induction over product size
This makes a finite-height proof for any `Fin n -> a` lattice
immediate, and precludes the need for IterProd and Prod altogether.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 12:16:04 -05:00
c281d78d1d Add documentation for IterProd 2026-06-26 12:16:04 -05:00
1a843747bf Delete unused code and moved some lemmas into Lattice.lean
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-26 12:16:04 -05:00
352e0bb8cc Fold Isomorphism module into Lattice.lean
Signed-off-by: Danila Fedorin <danila.fedorin@gmail.com>
2026-06-26 12:16:04 -05:00
a12b6c0c3c Write more documentation
Signed-off-by: Danila Fedorin <danila.fedorin@gmail.com>
2026-06-25 19:36:26 -05:00
30 changed files with 1931 additions and 794 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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@@ -1,10 +1,7 @@
import Spa.Lattice import Spa.Lattice
import Spa.Fixedpoint import Spa.Fixedpoint
import Spa.Isomorphism
import Spa.Lattice.Unit import Spa.Lattice.Unit
import Spa.Lattice.Prod
import Spa.Lattice.AboveBelow import Spa.Lattice.AboveBelow
import Spa.Lattice.IterProd
import Spa.Lattice.FiniteMap import Spa.Lattice.FiniteMap
import Spa.Lattice.Bool import Spa.Lattice.Bool
import Spa.Language.Base import Spa.Language.Base
@@ -22,3 +19,5 @@ 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.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 : ℤ} lemma plus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : ℤ}
(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 : ℤ} lemma minus_valid {g₁ g₂ : ConstLattice} {z₁ z₂ : ℤ}
(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 +137,12 @@ 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 {s : prog.State} {ρin ρout : Env}
(hr : Reaches s ρin ρout) :
⟦ joinForKey s (result ConstLattice prog) ⟧ ρin
∧ ⟦ variablesAt s (result ConstLattice prog) ⟧ ρout :=
Forward.analyze_correct_at ConstLattice prog 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 +53,100 @@ 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 {s₁ s₂ : prog.State} {sv : StateVariables L prog}
{vs : VariableValues L prog} {ρ₁ ρ₂ : Env} {ρ₁ ρ₂ ρ₃ : Env}
(hbss : EvalBasicStmts ρ₁ bss ρ₂) (hvs : ⟦ vs ⟧ ρ₁) : (tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂)
⟦ bss.foldl (fun vs bs => E.eval s bs vs) vs ⟧ ρ₂ := by (hnode : EvalBasicStmtOpt ρ₂ (prog.code s₂) 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) ⟧ ρ₁) (tr : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂)
(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 propagates along an execution prefix: if the analysis is sound at
(hjoin : ⟦ joinForKey s₁ (result L prog) ⟧ ρ₁) `s₂` for the run so far (`trₗ`), then it is sound wherever the further prefix
(tr : Trace prog.cfg s₁ s₂ ρ₁ ρ₂) : `mid` ends up. -/
⟦ variablesAt s₂ (result L prog) ⟧ ρ₂ := by lemma walkPrefix : ∀ {s₂ s : prog.State} {ρ₂ ρin : Env}
induction tr with (mid : Traceₗ prog.cfg s₂ s ρ₂ ρin) {s₁ : prog.State} {ρ₁ : Env}
| single hbss => exact stepTrace hjoin hbss (trₗ : Traceₗ prog.cfg s₁ s₂ ρ₁ ρ₂),
| @edge _ ρ' _ i₁ i₂ _ hbss hedge _ ih => ⟦ joinForKey s₂ (result L prog) ⟧ (S.Pre trₗ) →
have hstep : ⟦ variablesAt i₁ (result L prog) ⟧ ρ' := ⟦ joinForKey s (result L prog) ⟧ (S.Pre (trₗ ++ mid)) := by
stepTrace hjoin hbss intro s₂ s ρ₂ ρin mid
have hmem : variablesAt i₁ (result L prog) induction mid with
∈ (result L prog).valuesAt (prog.incoming i₂) := | nil => intro s₁ ρ₁ trₗ hjoin; simpa [HAppend.hAppend, Traceₗ.append] using hjoin
FiniteMap.mem_valuesAt prog.states_nodup | cons hnode hedge rest ih =>
(prog.mem_incoming_of_edge hedge) (variablesAt_mem i₁ (result L prog)) intro s₁ ρ₁ trₗ hjoin
exact ih (interp_foldr hstep hmem) 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 [HAppend.hAppend, Traceₗ.append] 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 `walkPrefix`. -/
rw [joinForKey_initialState] def reaches_final {s : prog.State} {ρ : Env}
exact interp_botV_nil (tr : Trace prog.cfg prog.initialState s [] ρ) : Σ ρin, Reaches s ρin ρ :=
⟨_, ⟨tr.split.2.1, tr.split.2.2⟩⟩
omit [DecidableEq L] in
@[simp] lemma reaches_final_post {s : prog.State} {ρ : Env}
(tr : Trace prog.cfg prog.initialState s [] ρ) :
(reaches_final tr).2.post = tr := Trace.split_append tr
variable (L prog) in variable (L prog) in
theorem analyze_correct {ρ : Env} (hrun : EvalStmt [] prog.rootStmt ρ) : /-- Soundness at every program point an execution actually visits: the analysis
over-approximates both the environment entering that point and the one leaving
it. -/
theorem analyze_correct_at {s : prog.State} {ρin ρout : Env} (hr : Reaches s ρin ρout) :
⟦ joinForKey s (result L prog) ⟧ (S.Pre hr.pre)
∧ ⟦ variablesAt s (result L prog) ⟧ (S.Post hr.post) :=
have hpre := walkPrefix hr.pre Traceₗ.nil
(by rw [joinForKey_initialState]; exact ValidStateEvaluator.botV_init)
⟨hpre, stepTrace hr.pre hpre hr.step⟩
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 (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)
(g := fun _ vs => E.eval e vs) (List.mem_singleton_self k) hk'l₀
rw [hl]
exact ValidExprEvaluator.valid hev hvs exact ValidExprEvaluator.valid hev hvs
| there _ _ _ _ _ hne hmem' => · have hl := FiniteMap.generalizedUpdate_not_mem_backward
have hk'l₀ : (k', l) ∈ FiniteMap.generalizedUpdate (ks := prog.vars) id (fun hmem => hne (List.mem_singleton.mp hmem)) hkl'
(fun _ vs => E.eval e vs) [k] vs := hk'l apply hvs _ _ hl _ hmem
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 ∨ ⟦ vs₂ ⟧ ρ) : ⟦ vs₁ ⊔ vs₂ ⟧ 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 +1,38 @@
import Spa.Analysis.Forward import Spa.Analysis.Forward
import Spa.Lattice.Bool import Spa.Lattice.Finset
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 : 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.State
namespace ReachingAnalysis namespace ReachingAnalysis
variable (prog : Program) variable (prog : Program)
def genSet (s : prog.State) : DefSet prog := def eval (s : prog.State) (vs : VariableValues (DefSet prog) prog) : VariableValues (DefSet prog) prog :=
FiniteMap.updating (⊥ : DefSet prog) [s] (fun _ => true) match prog.code s with
| none => vs
| some bs =>
match bs with
| .assign k _ => FiniteMap.generalizedUpdate id (fun _ _ => {s}) [k] vs
| .noop => vs
def eval (s : prog.State) : lemma eval_mono (s : prog.State) :
BasicStmt → VariableValues (DefSet prog) prog → VariableValues (DefSet prog) prog Monotone (eval prog s) := by
| .assign k _, vs => intros vs₁ vs₂ hle
FiniteMap.generalizedUpdate id (fun _ _ => genSet prog s) [k] vs unfold eval; split <;> try simpa
| .noop, vs => vs split <;> try simpa
apply FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => monotone_const)
lemma eval_mono (s : prog.State) (bs : BasicStmt) : assumption
Monotone (eval prog s bs) := by
cases bs with
| assign k e =>
exact FiniteMap.generalizedUpdate_monotone monotone_id (fun _ => monotone_const)
| noop => exact monotone_id
instance stmtEvaluator : StmtEvaluator (DefSet prog) prog := instance stmtEvaluator : StmtEvaluator (DefSet prog) prog :=
⟨eval prog, eval_mono prog⟩ ⟨eval prog, eval_mono prog⟩
@@ -36,6 +40,90 @@ 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.State → Prop
| here (s : prog.State) (e : Expr) (rest : Run prog) :
LastAssign prog x ((s, .assign x e) :: rest) s
| there (s : prog.State) (bs : BasicStmt) (hc : prog.code s = some bs)
(rest : Run prog) {n : prog.State} :
(∀ 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.State), 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 [hd] <;> 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 {s : prog.State} {ρin ρout : Env}
(hr : Reaches 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 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
@@ -117,13 +111,16 @@ namespace SignAnalysis
variable (prog : Program) variable (prog : Program)
/-- The sign of an integer literal. -/
def signOf (z : ℤ) : SignLattice :=
if z = 0 then .mk .zero else if 0 < z then .mk .plus else .mk .minus
def eval : Expr → VariableValues SignLattice prog → SignLattice def eval : Expr → VariableValues SignLattice prog → SignLattice
| .add e₁ e₂, vs => plus (eval e₁ vs) (eval e₂ vs) | .add e₁ e₂, vs => plus (eval e₁ vs) (eval e₂ vs)
| .sub e₁ e₂, vs => minus (eval e₁ vs) (eval e₂ vs) | .sub e₁ e₂, vs => minus (eval e₁ vs) (eval e₂ vs)
| .var k, vs => | .var k, vs =>
if h : FiniteMap.MemKey k vs then (FiniteMap.locate h).1 else .top if h : FiniteMap.MemKey k vs then (FiniteMap.locate h).1 else .top
| .num 0, _ => .mk .zero | .num z, _ => signOf z
| .num (_ + 1), _ => .mk .plus
lemma eval_mono (e : Expr) : Monotone (eval prog e) := by lemma eval_mono (e : Expr) : Monotone (eval prog e) := by
induction e with induction e with
@@ -145,7 +142,7 @@ lemma eval_mono (e : Expr) : Monotone (eval prog e) := by
dif_neg (fun hm => hk (FiniteMap.MemKey_iff.mp hm))] dif_neg (fun hm => hk (FiniteMap.MemKey_iff.mp hm))]
| num n => | num n =>
intro vs₁ vs₂ _ intro vs₁ vs₂ _
cases n <;> exact le_refl _ exact le_refl _
instance exprEvaluator : ExprEvaluator SignLattice prog := instance exprEvaluator : ExprEvaluator SignLattice prog :=
⟨eval prog, eval_mono prog⟩ ⟨eval prog, eval_mono prog⟩
@@ -165,6 +162,20 @@ private lemma int_neg_iff (z : ℤ) : (∃ n : ℕ, z = -((n : ℤ) + 1)) ↔ z
· rintro ⟨n, rfl⟩; omega · rintro ⟨n, rfl⟩; omega
· intro h; exact ⟨(-z - 1).toNat, by omega⟩ · intro h; exact ⟨(-z - 1).toNat, by omega⟩
/-- `signOf` really does describe the literal it was computed from. -/
lemma interp_signOf (z : ℤ) : ⟦signOf z⟧ (Value.int z) := by
unfold signOf
split
· case isTrue h => subst h; rfl
· rename_i hne
split
· case isTrue hpos =>
simp only [signInterpretation, interpSign, Value.int.injEq, int_pos_iff]
exact hpos
· case isFalse hnpos =>
simp only [signInterpretation, interpSign, Value.int.injEq, int_neg_iff]
omega
lemma plus_valid {g₁ g₂ : SignLattice} {z₁ z₂ : ℤ} lemma plus_valid {g₁ g₂ : SignLattice} {z₁ z₂ : ℤ}
(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
@@ -190,9 +201,7 @@ instance eval_valid : ValidExprEvaluator SignLattice prog := by
| num n => | num n =>
intro _ intro _
show ⟦eval prog (.num n) vs⟧ (.int n) show ⟦eval prog (.num n) vs⟧ (.int n)
cases n with exact interp_signOf n
| zero => rfl
| succ n' => exact ⟨n', congrArg Value.int (by norm_cast)⟩
| var x v hxv => | var x v hxv =>
intro hvs intro hvs
show ⟦eval prog (.var x) vs⟧ v show ⟦eval prog (.var x) vs⟧ v
@@ -219,6 +228,12 @@ 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 {s : prog.State} {ρin ρout : Env}
(hr : Reaches s ρin ρout) :
⟦ joinForKey s (result SignLattice prog) ⟧ ρin
∧ ⟦ variablesAt s (result SignLattice prog) ⟧ ρout :=
Forward.analyze_correct_at SignLattice prog hr
end SignAnalysis end SignAnalysis
end Spa end Spa

View File

@@ -12,7 +12,7 @@ def doStep (f : α → α) (hf : Monotone f) :
∀ (g : ℕ) (c : LTSeries α), c.length + g = height (α := α) + 1 → ∀ (g : ℕ) (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 : α → α) (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 : α → α) (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 : α → α) (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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@@ -1,16 +0,0 @@
import Spa.Lattice
namespace Spa
def FiniteHeightLattice.transport {α β : Type*} [Lattice β]
[I : FiniteHeightLattice α] (f : α → β) (g : β → α)
(hf : Monotone f) (hg : Monotone g)
(hgf : Function.LeftInverse g f) (hfg : Function.LeftInverse f g) :
FiniteHeightLattice β where
toLattice := inferInstance
longestChain :=
I.longestChain.map f (hf.strictMono_of_injective hgf.injective)
chains_bounded := fun c =>
I.chains_bounded (c.map g (hg.strictMono_of_injective hfg.injective))
end Spa

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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

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@@ -5,9 +5,13 @@ import Mathlib.Data.Finset.Basic
# Base Language # Base Language
This file defines the core object language for the program analysis and This file defines the core object language for the program analysis and
transformation. It's a very basic imperative language. The `Spa/Language/Tagged/Basic.lean` transformation. It's a very basic imperative language.
file provides an auto-derived version of the `Expr`, `BasicStmt`, and `Stmt` data
types with unique IDs per condtructor, enabling in-AST pointers. Program points are identified by their node in the control flow graph rather than
by an identifier stored in the AST: a recursion over a `Stmt` threads a
`Spa.GGraph.Embed` of the subtree's CFG into the whole program's (starting from
`Spa.Program.rootEmbed`), which yields the CFG index of each basic statement
along with a proof that the node carries it.
-/ -/
@@ -18,7 +22,7 @@ inductive Expr where
| add (e₁ e₂ : Expr) | add (e₁ e₂ : Expr)
| sub (e₁ e₂ : Expr) | sub (e₁ e₂ : Expr)
| var (x : String) | var (x : String)
| num (n : ℕ) | num (z : ℤ)
deriving DecidableEq deriving DecidableEq
/-- A statement that cannot alter control flow (and thus, can be part of a basic block). /-- A statement that cannot alter control flow (and thus, can be part of a basic block).

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 : ℕ} (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 : ℕ} (l : List (Fin n)) (m : ℕ) : List (Fin (n + m)) := def List.finCastAdd {n : ℕ} (l : List (Fin n)) (m : ℕ) : 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 +201,118 @@ 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
To be able to reason compositionally about traces through the graphs,
we need to be able to reason about how a trace within a sub-graph maps
to the full graph. Fortunately, graphs are built using composition operators,
and these composition operators always include their arguments as embedded
subgraphs in the full result. Moreover, each embedding "just" offsets the
existing node IDs by a given amount.
This section formalizes this fact by providing an `Embed` type that
represents an offset-based embedding, and showing that such an embedding
exists for all arguments given to graph composition operators. Furthermore,
because of the offset-based embedding, we can determine whether a node
came from a particular subgraph simply by examining its offset and sub-graph
size. This is captured by `Embed.mem_range_iff`. -/
/-- A special-case embedding of `g` into `h` in which all edges and nodes
of `g` are present in `h` at a given offset `off`. -/
structure Embed (g h : GGraph α) where
f : g.Index → h.Index
off : ℕ
f_val : ∀ i, (f i).val = off + i.val
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
lemma Embed.f_inj {g h : GGraph α} (e : Embed g h) : Function.Injective e.f := by
intro i j hij
have := congrArg Fin.val hij
rw [e.f_val, e.f_val] at this
exact Fin.ext (by omega)
/-- An embedding's range is the interval `[off, off + g.size)`. -/
lemma Embed.mem_range_iff {g h : GGraph α} (e : Embed g h) (j : h.Index) :
(∃ i, e.f i = j) ↔ e.off ≤ j.val ∧ j.val < e.off + g.size := by
constructor
· rintro ⟨i, rfl⟩; have := i.isLt; rw [e.f_val]; omega
· rintro ⟨hlo, hhi⟩
refine ⟨⟨j.val - e.off, by omega⟩, Fin.ext ?_⟩
rw [e.f_val]
show e.off + (j.val - e.off) = j.val
omega
/-- Build an embedding from an index map that is pointwise the shift. The five
inclusions below are naturally written with `Fin.castAdd`/`Fin.natAdd` — the form
the `Fin.append` lemmas are stated in — so this lets them keep those proofs
verbatim. The trailing argument is boilerplate at every call site and defaults
to discharging itself. -/
private def Embed.ofIndexMap {g h : GGraph α} (off : ℕ) (k : g.Index → h.Index)
(hn : ∀ i, h.nodes (k i) = g.nodes i)
(hem : ∀ {e : g.Edge}, e ∈ g.edges → (k e.1, k e.2) ∈ h.edges)
(hk : ∀ i, (k i).val = off + i.val := by intro i; simp) :
Embed g h where
f := k
off := off
f_val := hk
nodes_eq := hn
edges_mem := hem
/-- Embeddings compose (offsets add). -/
def Embed.trans {g₁ g₂ g₃ : GGraph α} (e₁ : Embed g₁ g₂) (e₂ : Embed g₂ g₃) :
Embed g₁ g₃ :=
ofIndexMap (e₂.off + e₁.off) (fun i => e₂.f (e₁.f i))
(fun i => (e₂.nodes_eq (e₁.f i)).trans (e₁.nodes_eq i))
(fun he => e₂.edges_mem (e₁.edges_mem he))
(hk := fun i => by rw [e₂.f_val, e₁.f_val]; omega)
/-- The left operand's inclusion into a sequenced graph. -/
def Embed.sequenceLeft (g₁ g₂ : GGraph α) : Embed g₁ (g₁ ⤳ g₂) :=
ofIndexMap 0 (fun i => i.castAdd g₂.size) (Fin.append_left g₁.nodes g₂.nodes)
(fun 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) :=
ofIndexMap g₁.size (fun i => i.natAdd g₁.size) (Fin.append_right g₁.nodes g₂.nodes)
(fun 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) :=
ofIndexMap 0 (fun i => i.castAdd g₂.size) (Fin.append_left g₁.nodes g₂.nodes)
(fun 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) :=
ofIndexMap g₁.size (fun i => i.natAdd g₁.size) (Fin.append_right g₁.nodes g₂.nodes)
(fun 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 (GGraph.loop g) :=
ofIndexMap 2 (fun i => i.natAdd 2) (Fin.append_right (fun _ : Fin 2 => none) g.nodes)
(fun he => List.mem_append_left _ (List.mem_append_left _
(List.mem_append_left _ (List.mem_map_of_mem _ he))))
/-- A `singleton` subgraph has exactly one node; this is where it sits in the ambient graph. -/
def Embed.singletonIndex {a : α} {h : GGraph α} (e : Embed (singleton a) h) : h.Index :=
e.f ⟨0, Nat.zero_lt_one⟩
@[simp] lemma Embed.nodes_singletonIndex {a : α} {h : GGraph α}
(e : Embed (singleton a) h) : h.nodes e.singletonIndex = a :=
e.nodes_eq ⟨0, Nat.zero_lt_one⟩
variable (g : GGraph α) variable (g : GGraph α)
/-- All the nodes in the graph. -/ /-- All the nodes in the graph. -/
@@ -205,6 +330,35 @@ 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 +374,12 @@ 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 +389,7 @@ 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 +1,82 @@
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
/-- The root statement's CFG sits inside the program's CFG. -/
def rootEmbed : GGraph.Embed p.rootStmt.cfg p.cfg :=
(GGraph.Embed.sequenceLeft p.rootStmt.cfg (Graph.singleton none)).trans
(GGraph.Embed.sequenceRight (Graph.singleton none) _)
/-- 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 : ℕ} (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) (idx₁.natAdd 2) (idx₂.natAdd 2) ρ₁ ρ₂ := by noncomputable def Trace.loop {idx₁ idx₂ : 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

View File

@@ -2,12 +2,27 @@ import Spa.Language.Base
import Spa.Lattice import Spa.Lattice
import Spa.Interp import Spa.Interp
/-!
# Operational Semantics
This file contains the operational semantics for the object language defined in
`Spa.Language.Base`. Right now, all values in the language are integers.
The semantics are big-step, and lead to a fully constructed proof tree
containing the derivation connecting the initial and final states.
All pretty standard.
-/
namespace Spa namespace Spa
/-- A value in the object language. Currently, the only possible case is
an integer. -/
inductive Value where inductive Value where
| int (z : ℤ) | int (z : ℤ)
deriving DecidableEq deriving DecidableEq
/-- An environment mapping variables to their values. -/
def Env : Type := List (String × Value) def Env : Type := List (String × Value)
inductive Env.Mem : String × Value → Env → Prop inductive Env.Mem : String × Value → Env → Prop
@@ -15,8 +30,10 @@ inductive Env.Mem : String × Value → Env → Prop
| there (s s' : String) (v v' : Value) (ρ : Env) : | there (s s' : String) (v v' : Value) (ρ : Env) :
¬(s = s') → Env.Mem (s, v) ρ → Env.Mem (s, v) ((s', v') :: ρ) ¬(s = s') → Env.Mem (s, v) ρ → Env.Mem (s, v) ((s', v') :: ρ)
/-- Inference rules for evaluating an expression (`Spa.Expr`) in a given
environment. Pretty standard big-step expression evaluation. -/
inductive EvalExpr : Env → Expr → Value → Prop inductive EvalExpr : Env → Expr → Value → Prop
| num (ρ : Env) (n : ℕ) : EvalExpr ρ (.num n) (.int n) | num (ρ : Env) (z : ℤ) : EvalExpr ρ (.num z) (.int z)
| var (ρ : Env) (x : String) (v : Value) : | var (ρ : Env) (x : String) (v : Value) :
Env.Mem (x, v) ρ → EvalExpr ρ (.var x) v Env.Mem (x, v) ρ → EvalExpr ρ (.var x) v
| add (ρ : Env) (e₁ e₂ : Expr) (z₁ z₂ : ℤ) : | add (ρ : Env) (e₁ e₂ : Expr) (z₁ z₂ : ℤ) :
@@ -26,18 +43,25 @@ inductive EvalExpr : Env → Expr → Value → Prop
EvalExpr ρ e₁ (.int z₁) → EvalExpr ρ e₂ (.int z₂) → EvalExpr ρ e₁ (.int z₁) → EvalExpr ρ e₂ (.int z₂) →
EvalExpr ρ (.sub e₁ e₂) (.int (z₁ - z₂)) EvalExpr ρ (.sub e₁ e₂) (.int (z₁ - z₂))
inductive EvalBasicStmt : Env → BasicStmt → Env → Prop /-- Inference rules for evaluating a basic statement (`Spa.BasicStmt`) in
a given environment, potentially changing the environment.
Pretty standard big-step evaluation. -/
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)
inductive EvalBasicStmts : Env → List BasicStmt → Env → Prop /-- Inference rules for evaluating a basic-statement-or-nothing,
| nil {ρ : Env} : EvalBasicStmts ρ [] ρ which is the current representation of CFGs nodes. -/
| cons {ρ₁ ρ₂ ρ₃ : Env} {bs : BasicStmt} {bss : List BasicStmt} : inductive EvalBasicStmtOpt : Env → Option BasicStmt → Env → Type
EvalBasicStmt ρ₁ bs ρ₂ → EvalBasicStmts ρ₂ bss ρ₃ → | none {ρ : Env} : EvalBasicStmtOpt ρ Option.none ρ
EvalBasicStmts ρ₁ (bs :: bss) ρ₃ | some {ρ₁ ρ₂ : Env} {bs : BasicStmt} :
EvalBasicStmt ρ₁ bs ρ₂ → EvalBasicStmtOpt ρ₁ (Option.some bs) ρ₂
inductive EvalStmt : Env → Stmt → Env → Prop /-- Inference rules for evaluating statements (`Spa.Stmt`) in a given
environment, potentially changing the environment.
Pretty standard big-step evaluation. -/
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) :
@@ -57,6 +81,15 @@ inductive EvalStmt : Env → Stmt → Env → Prop
EvalExpr ρ e (.int 0) → EvalExpr ρ e (.int 0) →
EvalStmt ρ (.whileLoop e s) ρ EvalStmt ρ (.whileLoop e s) ρ
/-- For the purpose of static analysis, lattices we define describe program
state, or better yet, they describe _values_ in the program.
This class should be provided by each analysis' lattice (see also `Spa/Analysis/Forward.lean`)
to describe what each lattice value means in terms of the language.
In addition to providing the interpretation (`Spa.Interp`), the lattice
combinators `⊔` and `⊓` must respect disjunction and conjunction respectively.
This is because possible paths through a control flow graph (`Spa/Language/Graphs.lean`),
are tied to lattice operations used by the analysis engine. -/
class LatticeInterpretation (L : Type*) [Lattice L] extends Interp L (Value → Prop) where class LatticeInterpretation (L : Type*) [Lattice L] extends Interp L (Value → Prop) where
interp_sup : ∀ {l₁ l₂ : L} (v : Value), interp_sup : ∀ {l₁ l₂ : L} (v : Value),
interp l₁ v ∨ interp l₂ v → interp (l₁ ⊔ l₂) v interp l₁ v ∨ interp l₂ v → interp (l₁ ⊔ l₂) v

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@@ -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 : ℕ }`); `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 : ℕ
desc : ℕ -- 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) : ℕ := 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 ℕ := (subtrees t).map (fun s => s.rootId.post)
def postsList (cs : List IdTree) : List ℕ := (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 : ℕ → IdTree → Prop
| mk {lo : ℕ} {id : NodeId} {cs : List IdTree} :
id.lo = lo → GoodChildren lo cs id.post →
Good lo (.node id cs)
inductive GoodChildren : ℕ → List IdTree → ℕ → Prop
| nil {pos : ℕ} : GoodChildren pos [] pos
| cons {cur : ℕ} {c : IdTree} {cs : List IdTree} {pos : ℕ} :
Good cur c → GoodChildren (c.rootId.post + 1) cs pos →
GoodChildren cur (c :: cs) pos
end
theorem Good.lo_le_post {lo : ℕ} {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 : ℕ} (cs : List IdTree) {pos : ℕ},
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 : ℕ} (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 : ℕ} (cs : List IdTree) {pos : ℕ},
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 : ℕ} (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 : ℕ} (cs : List IdTree) {pos : ℕ},
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 : ℕ} (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 : ℕ} (cs : List IdTree) {pos : ℕ},
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 : ℕ} {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 : 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 : 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 : 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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# 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`.

View File

@@ -1,26 +1,246 @@
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
/-- Every trace splits into the prefix that arrives at its last node and that node's own step. -/
def Trace.split {g : Graph} {i₁ i₂ : g.Index} {ρ₁ ρ₂ : Env} :
Trace g i₁ i₂ ρ₁ ρ₂ → Σ ρ, Traceₗ g i₁ i₂ ρ₁ ρ × EvalBasicStmtOpt ρ (g.nodes i₂) ρ₂
| .single hnode => ⟨_, .nil, hnode⟩
| .edge hnode hedge rest =>
let ⟨ρ, pre, step⟩ := rest.split
⟨ρ, .cons hnode hedge pre, step⟩
@[simp] lemma Trace.split_append {g : Graph} {i₁ i₂ : g.Index} {ρ₁ ρ₂ : Env}
(tr : Trace g i₁ i₂ ρ₁ ρ₂) : tr.split.2.1 ++ tr.split.2.2 = tr := by
induction tr with
| single hnode => rfl
| edge hnode hedge rest ih =>
show Traceₗ.appendStep _ _ = _
simpa [Trace.split, Traceₗ.appendStep, Traceₗ.appendTrace] using ih
structure Reaches {prog : Program} (s : prog.State) (ρin ρout : Env) : Type where
pre : Traceₗ prog.cfg prog.initialState s [] ρin
step : EvalBasicStmtOpt ρin (prog.code s) ρout
/-- Forget the environment before the last evaluated state. -/
def Reaches.post {prog : Program} {s : prog.State} {ρin ρout : Env}
(r : Reaches s ρin ρout) : Trace prog.cfg prog.initialState s [] ρout :=
r.pre ++ r.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. -/
@@ -61,51 +73,79 @@ 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. -/
def BoundedChains (α : Type*) [Preorder α] (n : ℕ) : Prop := def BoundedChains (α : Type*) [Preorder α] (n : ℕ) : Prop :=
∀ c : LTSeries α, c.length ≤ n ∀ c : LTSeries α, c.length ≤ n
/-- Since a singleton type's preorder has no nonempty `<` chains,
they are vacuously bounded by any minimum height. -/
lemma boundedChains_of_subsingleton (α : Type*) [Preorder α] [Subsingleton α]
(n : ℕ) : BoundedChains α n := fun c => by
by_contra hc
push_neg at hc
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 : ℕ
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] : ℕ := /-- This is something like a lemma about isomorphic types having the same height.
(longestChain (α := α)).length 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.
variable (α : Type*) [FiniteHeightLattice α] The proof is fairly trivial: any chain in `β` can be transported to a chain in `α`,
and must be bounded by the same height by `FiniteHeightLattice.chains_bounded`. -/
def transport {α β : Type*} [Lattice β]
[I : FiniteHeightLattice α] (f : α → β) (g : β → α)
(hf : Monotone f) (hg : Monotone g)
(hfg : Function.LeftInverse f g) :
FiniteHeightLattice β where
toLattice := inferInstance
toOrderBot := {
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 =>
I.chains_bounded (c.map g (hg.strictMono_of_injective hfg.injective))
instance (priority := 100) : Bot α := ⟨(longestChain (α := α)).head⟩ /-- A `Unique` lattice trivially has finite height: its only chain is the singleton
instance (priority := 100) : Top α := ⟨(longestChain (α := α)).last⟩ `[default]`, and there are no nontrivial `<` chains in a subsingleton. -/
def ofUnique (α : Type*) [Lattice α] [Unique α] :
/-- The bottom element `⊥` of a finite height lattice is _actually_ the least element. -/ FiniteHeightLattice α where
lemma bot_le (a : α) : (⊥ : α) ≤ a := by toLattice := inferInstance
by_cases heq : ⊥ ⊓ a = ⊥ toOrderBot := {
· exact inf_eq_left.mp heq bot := default
· exfalso bot_le := fun _ => le_of_eq (Subsingleton.elim _ _) }
have hlt : ⊥ ⊓ a < (longestChain (α := α)).head := toOrderTop := {
lt_of_le_of_ne inf_le_left heq top := default
have hbound := chains_bounded ((longestChain (α := α)).cons (⊥ ⊓ a) hlt) le_top := fun _ => le_of_eq (Subsingleton.elim _ _) }
rw [RelSeries.cons_length] at hbound height := 0
omega chains_bounded := boundedChains_of_subsingleton α 0
/-- 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
end FiniteHeightLattice end FiniteHeightLattice

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@@ -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
· rw [top_inf]; exact h.2
· rcases s₂ with _ | _ | y
· rw [inf_bot]; exact h.2
· rw [inf_top]; exact h.1
· rw [mk_inf_mk]
split split
· next heq => subst heq; exact h.1 · exact h.2
· next hne => exact absurd h (hdisj hne v) · next hne => exact (hdisj hne v h.1 h.2).elim
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 → ℕ
def rank : AboveBelow α → ℕ
| 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 → ℕ) := by lemma rank_strictMono : StrictMono (rank : AboveBelow α → ℕ) := 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

View File

@@ -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

View File

@@ -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 → ℕ) :=
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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@@ -1,35 +0,0 @@
import Spa.Lattice.Prod
import Spa.Lattice.Unit
namespace Spa
universe u
def IterProd (A B : Type u) : ℕ → Type u
| 0 => B
| k + 1 => A × IterProd A B k
namespace IterProd
variable {A B : Type u}
instance decidableEq [DecidableEq A] [DecidableEq B] :
∀ k, DecidableEq (IterProd A B k)
| 0 => inferInstanceAs (DecidableEq B)
| k + 1 => @instDecidableEqProd A (IterProd A B k) _ (decidableEq k)
def build (a : A) (b : B) : (k : ℕ) → IterProd A B k
| 0 => b
| k + 1 => (a, build a b k)
def fixedHeight [FiniteHeightLattice A] [FiniteHeightLattice B] :
∀ k, FiniteHeightLattice (IterProd A B k)
| 0 => inferInstanceAs (FiniteHeightLattice B)
| k + 1 => @Spa.prod A (IterProd A B k) _ (fixedHeight k)
instance finiteHeight [FiniteHeightLattice A] [FiniteHeightLattice B] (k : ℕ) :
FiniteHeightLattice (IterProd A B k) := fixedHeight k
end IterProd
end Spa

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@@ -1,82 +0,0 @@
import Spa.Lattice
namespace Spa
section Unzip
variable {α β : Type*} [PartialOrder α] [PartialOrder β]
lemma LTSeries.exists_unzip (c : LTSeries (α × β)) :
∃ (c₁ : LTSeries α) (c₂ : LTSeries β),
c₁.head = c.head.1 ∧ c₁.last = c.last.1 ∧
c₂.head = c.head.2 ∧ c₂.last = c.last.2 ∧
c.length ≤ c₁.length + c₂.length := by
suffices H : ∀ (n : ℕ) (c : LTSeries (α × β)), c.length = n →
∃ (c₁ : LTSeries α) (c₂ : LTSeries β),
c₁.head = c.head.1 ∧ c₁.last = c.last.1 ∧
c₂.head = c.head.2 ∧ c₂.last = c.last.2 ∧
c.length ≤ c₁.length + c₂.length from H c.length c rfl
intro n
induction n with
| zero =>
intro c hn
refine ⟨RelSeries.singleton _ c.head.1, RelSeries.singleton _ c.head.2,
rfl, ?_, rfl, ?_, by simp [hn]⟩ <;>
· have hlast : Fin.last c.length = 0 := by ext; simp [hn]
simp [RelSeries.last, RelSeries.head, hlast]
| succ n ih =>
intro c hn
have h0 : c.length ≠ 0 := by omega
haveI : NeZero c.length := ⟨h0⟩
obtain ⟨c₁, c₂, hh₁, hl₁, hh₂, hl₂, hlen⟩ :=
ih (c.tail h0) (by simp [RelSeries.tail_length, hn])
rw [RelSeries.last_tail] at hl₁ hl₂
rw [RelSeries.head_tail] at hh₁ hh₂
rw [RelSeries.tail_length] at hlen
have hstep : c.head < c 1 := c.strictMono Fin.one_pos'
obtain ⟨hle1, hle2⟩ := Prod.le_def.mp hstep.le
rcases eq_or_lt_of_le hle1 with heq1 | hlt1 <;>
rcases eq_or_lt_of_le hle2 with heq2 | hlt2
· exact absurd (Prod.ext heq1 heq2) hstep.ne
· refine ⟨c₁, c₂.cons c.head.2 (hh₂ ▸ hlt2),
hh₁.trans heq1.symm, hl₁, RelSeries.head_cons .., by
rw [RelSeries.last_cons]; exact hl₂, by
simp only [RelSeries.cons_length]; omega⟩
· refine ⟨c₁.cons c.head.1 (hh₁ ▸ hlt1), c₂,
RelSeries.head_cons .., by
rw [RelSeries.last_cons]; exact hl₁,
hh₂.trans heq2.symm, hl₂, by
simp only [RelSeries.cons_length]; omega⟩
· refine ⟨c₁.cons c.head.1 (hh₁ ▸ hlt1), c₂.cons c.head.2 (hh₂ ▸ hlt2),
RelSeries.head_cons .., by
rw [RelSeries.last_cons]; exact hl₁,
RelSeries.head_cons .., by
rw [RelSeries.last_cons]; exact hl₂, by
simp only [RelSeries.cons_length]; omega⟩
end Unzip
section FixedHeight
variable {α β : Type*}
instance prod [A : FiniteHeightLattice α] [B : FiniteHeightLattice β] :
FiniteHeightLattice (α × β) where
toLattice := inferInstance
longestChain :=
RelSeries.smash
(A.longestChain.map (fun a => (a, (⊥ : β)))
(fun _ _ h => Prod.mk_lt_mk_iff_left.mpr h))
(B.longestChain.map (fun b => ((⊤ : α), b))
(fun _ _ h => Prod.mk_lt_mk_iff_right.mpr h))
rfl
chains_bounded := fun c => by
obtain ⟨c₁, c₂, -, -, -, -, hlen⟩ := LTSeries.exists_unzip c
have h₁ := A.chains_bounded c₁
have h₂ := B.chains_bounded c₂
show c.length ≤ A.longestChain.length + B.longestChain.length
omega
end FixedHeight
end Spa

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@@ -1,64 +1,127 @@
import Spa.Lattice.IterProd import Spa.Lattice
import Spa.Isomorphism import Mathlib.Data.Fin.Tuple.Basic
import Mathlib.Algebra.Order.BigOperators.Group.Finset
/-!
# Finite Tuple Lattices
This file provides a proof that, in addition to being a lattice, the function
space `Fin n → β` is itself a `Spa.FiniteHeightLattice` if the element type
`β` is a lattice.
Finite tuple lattices are the workhorse behind `FiniteMap`, whose carrier is
`Fin ks.length → β`.
The proof proceeds by "unzipping" a chain (`LTSeries`):
$$
(a_1, b_1, c_1) < \ldots < (a_1, b_1, c_o) < \ldots < (a_1, b_m, c_o) <
\ldots < (a_n, b_m, c_o)
$$
In which, at each step, at least one of the components must have increased
(otherwise, the chain is not striclty increasing), into `n` chains
(`LTSeries`).
$$
\begin{aligned}
a_1 < \ldots < a_n \\
b_1 < \ldots < b_m \
c_1 < \ldots < c_o \
\end{aligned}
$$
Because at least one of the two "unzipped" chains grows with each element of
the product chain, the full chain length can't exceed the sum of the
components. By the definition of finite height, these two chains are bounded,
and therefore, the product chain is bounded too. -/
namespace Spa namespace Spa
namespace Tuple namespace Tuple
universe u variable {β : Type*}
variable {B : Type u} section Unzip
private def iterOfFun : {n : ℕ} → (Fin n → B) → IterProd B PUnit n variable [PartialOrder β]
| 0, _ => PUnit.unit
| _ + 1, f => (f 0, iterOfFun (Fin.tail f))
private def funOfIter : {n : ℕ} → IterProd B PUnit n → (Fin n → B) open Classical in -- chain bounds are in Prop, so classical helps here.
| 0, _ => Fin.elim0 /-- The generalized unzip: any chain in `Fin n → β` decomposes into a family of
| _ + 1, ip => Fin.cons ip.1 (funOfIter ip.2) per-tuple-coordinate chains in `β`, agreeing with the original at each end, whose
lengths sum to an upper bound on the original chain's length. -/
lemma exists_unzip {n : ℕ} (c : LTSeries (Fin n → β)) :
∃ cs : Fin n → LTSeries β,
(∀ i, (cs i).head = c.head i) ∧ (∀ i, (cs i).last = c.last i) ∧
c.length ≤ ∑ i, (cs i).length := by
suffices H : ∀ (m : ℕ) (c : LTSeries (Fin n → β)), c.length = m →
∃ cs : Fin n → LTSeries β,
(∀ i, (cs i).head = c.head i) ∧ (∀ i, (cs i).last = c.last i) ∧
c.length ≤ ∑ i, (cs i).length from H c.length c rfl
intro m
induction m with
| zero =>
intro c hn
have hlast : (Fin.last c.length) = 0 := by ext; simp [hn]
have hhl : c.last = c.head := by rw [RelSeries.last, RelSeries.head, hlast]
refine ⟨fun i => RelSeries.singleton _ (c.head i), fun i => ?_, fun i => ?_, ?_⟩
· exact RelSeries.head_singleton _
· rw [RelSeries.last_singleton, hhl]
· simp [hn, RelSeries.singleton]
| succ m ih =>
intro c hn
have h0 : c.length ≠ 0 := by omega
haveI : NeZero c.length := ⟨h0⟩
obtain ⟨cs', hh', hl', hlen'⟩ := ih (c.tail h0) (by rw [RelSeries.tail_length]; omega)
have hstep : c.head < c 1 := c.strictMono Fin.one_pos'
obtain ⟨hle, j, hjlt⟩ := Pi.lt_def.mp hstep
have hh'1 : ∀ i, (cs' i).head = c 1 i := fun i => by rw [hh' i, RelSeries.head_tail]
refine ⟨fun i =>
if hlt : c.head i < c 1 i then
(cs' i).cons (c.head i) (by rw [hh'1 i]; exact hlt)
else cs' i,
fun i => ?_, fun i => ?_, ?_⟩
· by_cases hlt : c.head i < c 1 i
· simp only [dif_pos hlt, RelSeries.head_cons]
· simp only [dif_neg hlt]
rw [hh'1 i]
exact ((lt_or_eq_of_le (hle i)).resolve_left hlt).symm
· by_cases hlt : c.head i < c 1 i
· simp only [dif_pos hlt, RelSeries.last_cons, hl' i, RelSeries.last_tail]
· simp only [dif_neg hlt, hl' i, RelSeries.last_tail]
· calc c.length
= (c.tail h0).length + 1 := by rw [RelSeries.tail_length]; omega
_ ≤ (∑ i, (cs' i).length) + 1 := Nat.add_le_add_right hlen' 1
_ ≤ ∑ i, (if hlt : c.head i < c 1 i then
(cs' i).cons (c.head i) (by rw [hh'1 i]; exact hlt) else cs' i).length :=
Nat.succ_le_of_lt (Finset.sum_lt_sum (fun i _ => by
split
· rw [RelSeries.cons_length]; omega
· exact le_rfl)
⟨j, Finset.mem_univ j, by rw [dif_pos hjlt, RelSeries.cons_length]; omega⟩)
private lemma funOfIter_iterOfFun : ∀ {n : ℕ} (f : Fin n → B), end Unzip
funOfIter (iterOfFun f) = f
| 0, _ => funext fun i => i.elim0
| _ + 1, f => by
show Fin.cons (f 0) (funOfIter (iterOfFun (Fin.tail f))) = f
rw [funOfIter_iterOfFun (Fin.tail f), Fin.cons_self_tail]
private lemma iterOfFun_funOfIter : ∀ {n : ℕ} (ip : IterProd B PUnit n), section FiniteHeight
iterOfFun (funOfIter ip) = ip
| 0, PUnit.unit => rfl
| _ + 1, ip => by
show (funOfIter ip 0, iterOfFun (Fin.tail (funOfIter ip))) = ip
rw [show funOfIter ip = Fin.cons ip.1 (funOfIter ip.2) from rfl]
simp [Fin.cons_zero, Fin.tail_cons, iterOfFun_funOfIter ip.2]
variable [FiniteHeightLattice B] variable [FiniteHeightLattice β]
private lemma funOfIter_mono {n : ℕ} : instance instFiniteHeight {n : ℕ} : FiniteHeightLattice (Fin n → β) where
Monotone (funOfIter : IterProd B PUnit n → (Fin n → B)) := by toLattice := inferInstance
induction n with toOrderBot := inferInstance
| zero => intro _ _ _ i; exact i.elim0 toOrderTop := inferInstance
| succ n ih => height := n * FiniteHeightLattice.height (α := β)
intro ip₁ ip₂ h i chains_bounded := fun c => by
obtain ⟨h1, h2⟩ := Prod.le_def.mp h obtain ⟨cs, _, _, hbound⟩ := exists_unzip c
rw [show funOfIter ip₁ = Fin.cons ip₁.1 (funOfIter ip₁.2) from rfl, refine hbound.trans ?_
show funOfIter ip₂ = Fin.cons ip₂.1 (funOfIter ip₂.2) from rfl] calc ∑ i, (cs i).length
induction i using Fin.cases with ≤ ∑ _i : Fin n, FiniteHeightLattice.height (α := β) :=
| zero => rw [Fin.cons_zero, Fin.cons_zero]; exact h1 Finset.sum_le_sum (fun i _ => FiniteHeightLattice.chains_bounded (cs i))
| succ j => rw [Fin.cons_succ, Fin.cons_succ]; exact ih h2 j _ = n * FiniteHeightLattice.height (α := β) := by
simp [Finset.sum_const, Finset.card_univ, Fintype.card_fin]
private lemma iterOfFun_mono {n : ℕ} : end FiniteHeight
Monotone (iterOfFun : (Fin n → B) → IterProd B PUnit n) := by
induction n with
| zero => intro f g _; exact le_of_eq rfl
| succ n ih =>
intro f g h
exact Prod.le_def.mpr ⟨h 0, ih fun i => h i.succ⟩
instance instFiniteHeight {n : ℕ} :
FiniteHeightLattice (Fin n → B) :=
FiniteHeightLattice.transport funOfIter iterOfFun
funOfIter_mono iterOfFun_mono iterOfFun_funOfIter funOfIter_iterOfFun
end Tuple end Tuple

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@@ -1,16 +1,14 @@
import Spa.Lattice import Spa.Lattice
/-!
# Unit Lattice
This file provides a proof that in addition to being a lattice,
`PUnit` is a `Spa.FiniteHeightLattice`. This is a fairly trivial result. -/
namespace Spa namespace Spa
lemma boundedChains_of_subsingleton (α : Type*) [Preorder α] [Subsingleton α] instance : FiniteHeightLattice PUnit := FiniteHeightLattice.ofUnique PUnit
(n : ℕ) : BoundedChains α n := fun c => by
by_contra hc
push_neg at hc
exact (c.step ⟨0, by omega⟩).ne (Subsingleton.elim _ _)
instance : FiniteHeightLattice PUnit where
toLattice := inferInstance
longestChain := RelSeries.singleton _ PUnit.unit
chains_bounded := boundedChains_of_subsingleton PUnit 0
end Spa end Spa

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@@ -0,0 +1,116 @@
import Spa.Analysis.Reaching
/-!
# Finding loop-invariant assignments (LICM groundwork)
This wires the **reaching-definitions** analysis (`Spa/Analysis/Reaching.lean`)
to the 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 traversal recurses over the plain `Stmt`, threading a `GGraph.Embed` of the
current subtree's CFG into the program's (`Program.rootEmbed`, then one
`Embed.trans` per descent). That embedding is what supplies program states:
1. at an assignment, its CFG state is `Embed.singletonIndex` — the subtree's CFG
is a `singleton`, so its sole node is the state, and `nodes_eq` proves it
holds that very statement;
2. read the reaching definitions at the assignment's *entry* (`joinForKey s
result` — the join over predecessors, i.e. before the assignment runs);
3. union the definition sets of the RHS variables;
4. check no definition site lies in the loop body's CFG range. Every embedding is
a constant index shift, so the body occupies the interval
`[off, off + size)` (`GGraph.Embed.mem_range_iff`) and the test is two
comparisons.
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 GGraph
/-- The CFG footprint of an enclosing loop: its entry node (for reporting) and
the index interval its body occupies. -/
structure Enclosing (prog : Program) where
/-- The loop's entry node, i.e. `GGraph.loopIn` embedded into the program. -/
loopState : prog.State
/-- Start of the body's index range. -/
bodyOff : ℕ
/-- Length of the body's index range. -/
bodySize : ℕ
/-- Is this definition site inside the loop body's CFG range? -/
def Enclosing.covers {prog : Program} (l : Enclosing prog) (d : prog.State) : Bool :=
decide (l.bodyOff ≤ d.val ∧ d.val < l.bodyOff + l.bodySize)
/-- 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 loop. -/
encl : Enclosing prog
/-- The assignment's CFG state. -/
assignState : prog.State
/-- The variables read by the assignment's RHS. -/
rhsVars : List String
/-- Collect every assignment together with its *immediately enclosing* loop.
`enc` is `none` outside any loop, in which case assignments are skipped — only
in-loop assignments are candidates. -/
def collectCandidates (prog : Program) (enc : Option (Enclosing prog)) :
(s : Stmt) → Embed s.cfg prog.cfg → List (Candidate prog)
| .basic bs, e =>
match bs, enc with
| .assign _ ex, some l =>
[{ encl := l, assignState := e.singletonIndex,
rhsVars := ex.vars.sort (· ≤ ·) }]
| _, _ => []
| .andThen s₁ s₂, e =>
collectCandidates prog enc s₁ ((Embed.sequenceLeft s₁.cfg s₂.cfg).trans e) ++
collectCandidates prog enc s₂ ((Embed.sequenceRight s₁.cfg s₂.cfg).trans e)
| .ifElse _ s₁ s₂, e =>
collectCandidates prog enc s₁ ((Embed.overlayLeft s₁.cfg s₂.cfg).trans e) ++
collectCandidates prog enc s₂ ((Embed.overlayRight s₁.cfg s₂.cfg).trans e)
| .whileLoop _ body, e =>
let be := (Embed.loop body.cfg).trans e
collectCandidates prog
(some { loopState := e.f body.cfg.loopIn, bodyOff := be.off,
bodySize := body.cfg.size }) body be
/-- 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 ⊥
/-- Is the candidate assignment loop-invariant: do all reaching definitions of
its RHS variables lie outside the loop body? -/
def isInvariant (prog : Program) (c : Candidate prog) : Bool :=
let entry := joinForKey c.assignState (result (DefSet prog) prog)
let combined : DefSet prog :=
c.rhsVars.foldl (fun acc k => acc ⊔ lookupDef prog entry k) ⊥
-- `Finset.toList` is noncomputable; the decidable bounded-∀ folds over the
-- underlying multiset and keeps `lake exe` working.
decide (∀ d ∈ combined, c.encl.covers d = false)
/-- The loop-invariant assignments of `prog`, as `(loop, assignment)` state pairs. -/
def licmCandidates (prog : Program) : List (prog.State × prog.State) :=
(collectCandidates prog none prog.rootStmt prog.rootEmbed).filterMap (fun c =>
if isInvariant prog c then some (c.encl.loopState, c.assignState) 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