Add the first post in CS325 series

code/cs325-langs/hws/hw1.txt

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+CS 325-001, Analysis of Algorithms, Fall 2019
+HW1 - Python 3, qsort, BST, and qselect
+Due electronically on flip on Monday 9/30 at 11:59pm. 
+No late submission will be accepted.
+
+Need to submit on flip: report.txt, qsort.py, and qselect.py.
+qselect.py will be automatically graded for correctness (1%).
+
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw1 qselect.py qsort.py report.txt
+
+Note:
+
+1. You can ssh to flip machines from your own machine by:
+   $ ssh access.engr.oregonstate.edu
+
+2. You can add /nfs/farm/classes/eecs/fall2019/cs325-001/ to your $PATH:
+   $ export PATH=$PATH:/nfs/farm/classes/eecs/fall2019/cs325-001/
+   and add the above command to your ~/.bash_profile,
+   so that you don't need to type it every time.
+
+   (alternatively, you can use symbolic links or aliases to avoid typing the long path)
+
+3. You can choose to submit each file separately, or submit them together.
+
+Textbooks for References:
+[1] CLRS Ch. 9.2 and Ch. 12
+
+0. Q: What's the best-case, worst-case, and average-case time complexities of quicksort.
+   Briefly explain each case.
+
+1. [WILL BE GRADED] 
+   Quickselect with Randomized Pivot (CLRS Ch. 9.2).
+
+   >>> from qselect import *
+   >>> qselect(2, [3, 10, 4, 7, 19])
+   4
+   >>> qselect(4, [11, 2, 8, 3])
+   11
+
+   Q: What's the best-case, worst-case, and average-case time complexities? Briefly explain.
+
+   Filename: qselect.py
+
+
+2. Buggy Qsort Revisited
+
+   In the slides we showed a buggy version of qsort which is weird in an interesting way:
+   it actually returns a binary search tree for the given array, rooted at the pivot:
+
+   >>> from qsort import *
+   >>> tree = sort([4,2,6,3,5,7,1,9])
+   >>> tree
+   [[[[], 1, []], 2, [[], 3, []]], 4, [[[], 5, []], 6, [[], 7, [[], 9, []]]]]
+
+   which encodes a binary search tree:
+
+                      4
+                    /   \
+                  2       6
+                 / \     / \
+                1   3   5   7
+                             \
+                              9
+   
+   Now on top of that piece of code, add three functions: 
+   * sorted(t): returns the sorted order (infix traversal)
+   * search(t, x): returns whether x is in t
+   * insert(t, x): inserts x into t (in-place) if it is missing, otherwise does nothing.
+
+   >>> sorted(tree)
+   [1, 2, 3, 4, 5, 6, 7, 9]
+   >>> search(tree, 6)
+   True
+   >>> search(tree, 6.5)
+   False
+   >>> insert(tree, 6.5)
+   >>> tree
+   [[[[], 1, []], 2, [[], 3, []]], 4, [[[], 5, []], 6, [[[], 6.5, []], 7, [[], 9, []]]]]
+   >>> insert(tree, 3)
+   >>> tree
+   [[[[], 1, []], 2, [[], 3, []]], 4, [[[], 5, []], 6, [[[], 6.5, []], 7, [[], 9, []]]]]
+
+   Hint: both search and insert should depend on a helper function _search(tree, x) which 
+   returns the subtree (a list) rooted at x when x is found, or the [] where x should 
+   be inserted.
+
+   e.g., 
+   >>> tree = sort([4,2,6,3,5,7,1,9])        # starting from the initial tree
+   >>> _search(tree, 3)
+   [[], 3, []]
+   >>> _search(tree, 0)
+   []
+   >>> _search(tree, 6.5)
+   []
+   >>> _search(tree, 0) is _search(tree, 6.5)
+   False
+   >>> _search(tree, 0) == _search(tree, 6.5)
+   True
+   
+   Note the last two []'s are different nodes (with different memory addresses): 
+   the first one is the left child of 1, while the second one is the left child of 7
+   (so that insert is very easy).
+   
+   Filename: qsort.py
+   
+   Q: What are the time complexities for the operations implemented?
+
+Debriefing (required!): --------------------------
+
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%–100%)? 
+5. Any other comments?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+

code/cs325-langs/hws/hw10.txt

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+CS 325, Algorithms (MS/MEng-level), Fall 2019
+
+HW10 - Challenge Problem - RNA Structure Prediction (6%)
+This problem combines dynamic programming and priority queues.
+
+Due Wednesday 12/4, 11:59pm.
+No late submission will be accepted.
+
+Include in your submission: report.txt, rna.py.
+Grading: 
+* report.txt -- 1%
+* 1-best structure -- 2%
+* number of structures -- 1%
+* k-best structures -- 2%
+
+Textbooks for References:
+[1] KT Ch. 6.5 (DP over intervals -- RNA structure)    
+[2] KT slides: DP I (RNA section)
+    http://www.cs.princeton.edu/~wayne/kleinberg-tardos/
+
+***Please analyze time/space complexities for each problem in report.txt.
+
+1. Given an RNA sequence, such as ACAGU, we can predict its secondary structure 
+   by tagging each nucleotide as (, ., or ). Each matching pair of () must be 
+   AU, GC, or GU (or their mirror symmetries: UA, CG, UG). 
+   We also assume pairs can _not_ cross each other. 
+   The following are valid structures for ACAGU:
+
+   ACAGU
+   .....
+   ...()
+   ..(.)
+   .(.).
+   (...)
+   ((.))    
+
+   We want to find the structure with the maximum number of matching pairs. 
+   In the above example, the last structure is optimal (2 pairs). 
+
+   >>> best("ACAGU")
+   (2, '((.))')
+
+   Tie-breaking: arbitrary. Don't worry as long as your structure
+   is one of the correct best structures.
+
+   some other cases (more cases at the bottom):
+
+   GCACG
+   (2, '().()')
+   UUCAGGA
+   (3, '(((.)))')
+   GUUAGAGUCU
+   (4, '(.()((.)))')
+   AUAACCUUAUAGGGCUCUG
+   (8, '.(((..)()()((()))))')
+   AACCGCUGUGUCAAGCCCAUCCUGCCUUGUU
+   (11, '(((.(..(.((.)((...().))()))))))')
+   GAUGCCGUGUAGUCCAAAGACUUCACCGUUGG
+   (14, '.()()(()(()())(((.((.)(.))()))))')
+   CAUCGGGGUCUGAGAUGGCCAUGAAGGGCACGUACUGUUU
+   (18, '(()())(((((.)))()(((())(.(.().()()))))))')
+   ACGGCCAGUAAAGGUCAUAUACGCGGAAUGACAGGUCUAUCUAC
+   (19, '.()(((.)(..))(((.()()(())))(((.)((())))))())')
+   AGGCAUCAAACCCUGCAUGGGAGCACCGCCACUGGCGAUUUUGGUA
+   (20, '.(()())...((((()()))((()(.()(((.)))()())))))()')
+
+2. Total number of all possible structures
+
+   >>> total("ACAGU")
+   6
+
+3. k-best structures: output the 1-best, 2nd-best, ... kth-best structures.
+
+   >>> kbest("ACAGU", 3)
+   [(2, '((.))'), (1, '(...)'), (1, '.(.).')]
+   
+   The list must be sorted. 
+   Tie-breaking: arbitrary.
+
+   In case the input k is bigger than the number of possible structures, output all.
+
+   Sanity check: kbest(s, 1)[0][0] == best(s)[0] for each RNA sequence s.
+
+All three functions should be in one file: rna.py.
+
+See more testcases at the end.
+   
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Any other comments?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+
+
+TESTCASES:
+
+for each sequence s, we list three lines:
+best(s)
+total(s)
+kbest(s, 10)
+
+
+
+ACAGU
+(2, '((.))')
+6
+[(2, '((.))'), (1, '.(.).'), (1, '..(.)'), (1, '...()'), (1, '(...)'), (0, '.....')]
+------
+AC
+(0, '..')
+1
+[(0, '..')]
+------
+GUAC
+(2, '(())')
+5
+[(2, '(())'), (1, '()..'), (1, '.().'), (1, '(..)'), (0, '....')]
+------
+GCACG
+(2, '().()')
+6
+[(2, '().()'), (1, '(..).'), (1, '()...'), (1, '.(..)'), (1, '...()'), (0, '.....')]
+------
+CCGG
+(2, '(())')
+6
+[(2, '(())'), (1, '(.).'), (1, '.().'), (1, '.(.)'), (1, '(..)'), (0, '....')]
+------
+CCCGGG
+(3, '((()))')
+20
+[(3, '((()))'), (2, '((.)).'), (2, '(.()).'), (2, '.(()).'), (2, '.(().)'), (2, '.((.))'), (2, '((.).)'), (2, '(.(.))'), (2, '(.().)'), (2, '((..))')]
+------
+UUCAGGA
+(3, '(((.)))')
+24
+[(3, '(((.)))'), (2, '((.).).'), (2, '((..)).'), (2, '(.(.)).'), (2, '((.))..'), (2, '.((.)).'), (2, '.((.).)'), (2, '.((..))'), (2, '((..).)'), (2, '((.)..)')]
+------
+AUAACCUA
+(2, '.((...))')
+19
+[(2, '((.)..).'), (2, '(()...).'), (2, '()(...).'), (2, '().(..).'), (2, '()....()'), (2, '.()(..).'), (2, '.()...()'), (2, '.(.)..()'), (2, '.((...))'), (2, '.(.(..))')]
+------
+UUGGACUUG
+(4, '(()((.)))')
+129
+[(4, '(())(.)()'), (4, '(()((.)))'), (3, '(().)..()'), (3, '(().).(.)'), (3, '(().)(..)'), (3, '((.))..()'), (3, '((.)).(.)'), (3, '((.))(..)'), (3, '(())(..).'), (3, '(())(.)..')]
+------
+UUUGGCACUA
+(4, '(.()()(.))')
+179
+[(4, '((()).).()'), (4, '((.)()).()'), (4, '(.()()).()'), (4, '.(()()).()'), (4, '.(()()(.))'), (4, '((()).(.))'), (4, '((.)()(.))'), (4, '((()())..)'), (4, '(.()()(.))'), (3, '((()).)...')]
+------
+GAUGCCGUGUAGUCCAAAGACUUC
+(11, '(((()()((()(.))))((.))))')
+2977987
+[(11, '(()())(((()().))(((.))))'), (11, '(()())(((()()).)(((.))))'), (11, '(()())(((()(.)))(((.))))'), (11, '(()()()((()(.)))(((.))))'), (11, '(((()()((()().)))((.))))'), (11, '(((()()((()(.))))((.))))'), (11, '(()()()((()()).)(((.))))'), (11, '(()()()((()().))(((.))))'), (11, '(((()()((()()).))((.))))'), (10, '(()()()((()().).)((.))).')]
+------
+AGGCAUCAAACCCUGCAUGGGAGCG
+(10, '.(()())...((((()()))).())')
+560580
+[(10, '.(()())...((((())())).)()'), (10, '.(()())...((((()()))).)()'), (10, '.(()())...(((()(()))).)()'), (10, '.(()())...(((()(()))).())'), (10, '.(()())...((((())())).())'), (10, '.(()())...((((()()))).())'), (9, '((.).)(...(.((()()))).)()'), (9, '((.).)(...(((.)(()))).)()'), (9, '((.).)(...(.(()(()))).)()'), (9, '((.).)(...((.(()()))).)()')]
+------

code/cs325-langs/hws/hw11.txt

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+HW11 -- OPTIONAL (for your practice only -- solutions will be released on Tuesday)
+
+Edit Distance (see updated final review solutions)
+
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw11 edit.py
+
+Implement two functions:
+* distance1(s, t): Viterbi-style (either top-down or bottom-up)
+* distance2(s, t): Dijkstra-style (best-first)
+
+For Dijkstra, you can use either heapdict or heapq (see review problem 7).
+Given that this graph is extremely sparse (why?), heapq (ElogE) might be faster than heapdict (ElogV)
+because the latter has overhead for hash.
+
+They should return the same result (just return the edit distance).
+
+We have 10 testcases (listed below); the first 5 test distance1(), 
+and the second 5 test distance2() on the same 5 string pairs.
+
+My solutions (on flip2):
+Testing Case  1 (open)...	  0.001 s, Correct
+Testing Case  2 (open)...	  0.000 s, Correct
+Testing Case  3 (open)...	  0.012 s, Correct
+Testing Case  4 (open)...	  0.155 s, Correct
+Testing Case  5 (open)...	  0.112 s, Correct
+Testing Case  6 (hidden)...	  0.000 s, Correct
+Testing Case  7 (hidden)...	  0.000 s, Correct
+Testing Case  8 (hidden)...	  0.004 s, Correct
+Testing Case  9 (hidden)...	  0.009 s, Correct
+Testing Case 10 (hidden)...	  0.021 s, Correct
+Total Time: 0.316 s
+
+distance1("abcdefh", "abbcdfg") == 3
+distance1("pretty", "prettier") == 3
+distance1("aaaaaaadaaaaaaaaaaaaaaaaacaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "aaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaxaaaaaaaaaaaaaaaaaaaaaa") == 5
+distance1('cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbxtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfjbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwy', 'cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasonrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwy') == 3
+distance1('cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpasdfkecyywrbvhlqgxzutdjfmvlhsezfbhbllmfhzlqlcwibubyyjupbwhztsxyksfthkptxqlmhivfjbgclhombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrttoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwydmbihjkvziitusmkjljrsbafytsinql', 'cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfjbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwydmbihjkvziitusmkjljrsbafytsinql') == 11
+distance2("abcdefh", "abbcdfg") == 3
+distance2("pretty", "prettier") == 3
+distance2("aaaaaaadaaaaaaaaaaaaaaaaacaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "aaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaxaaaaaaaaaaaaaaaaaaaaaa") == 5
+distance2('cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbxtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfjbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwy', 'cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasonrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwy') == 3
+distance2('cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpasdfkecyywrbvhlqgxzutdjfmvlhsezfbhbllmfhzlqlcwibubyyjupbwhztsxyksfthkptxqlmhivfjbgclhombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrttoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwydmbihjkvziitusmkjljrsbafytsinql', 'cpuyedzrwcbritzclzhwwabmlyresvewkdxwkamyzbtwiqzvokqpkecyywrbvhlqgxzutdjfmvlhsezfbhfjbllmfhzlqlcwibubyyjupbwhztskyksfthkptxqlmhivfjbgclwsombvytdztapwpzmdqfwwrhqsgztobeuiatcwmrzfbwhfnpzzasomrhotoqiwvexlgxsnafiagfewmopdzwanxswfsmbxsmsczbwsgnwydmbihjkvziitusmkjljrsbafytsinql') == 11

code/cs325-langs/hws/hw2.txt

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+CS 325-001, Analysis of Algorithms, Fall 2019
+HW2 - Divide-n-conquer: mergesort, number of inversions, longest path
+
+Due Monday Oct 7, 11:59pm (same submission instructions as HW1).
+No late submission will be accepted.
+
+Need to submit: report.txt, msort.py, inversions.py, and longest.py.
+longest.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw2 report.txt {msort,inversions,longest}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw2
+
+
+Textbooks for References:
+[1] CLRS Ch. 2
+
+0. Which of the following sorting algorithms are (or can be made) stable?
+   (a) mergesort
+   (b) quicksort with the first element as pivot
+   (c) quicksort with randomized pivot
+   (d) selection sort
+   (e) insertion sort
+   (f) heap sort --- not covered yet (see CLRS Ch. 6)
+
+1. Implement mergesort.
+   
+   >>> mergesort([4, 2, 5, 1, 6, 3])
+   [1, 2, 3, 4, 5, 6]   
+   
+   Filename: msort.py
+   
+2. Calculate the number of inversions in a list.
+
+   >>> num_inversions([4, 1, 3, 2])
+   4
+   >>> num_inversions([2, 4, 1, 3])
+   3
+
+   Filename: inversions.py
+   Must run in O(nlogn) time.
+
+3. [WILL BE GRADED] 
+
+   Length of the longest path in a binary tree (number of edges).
+   
+   We will use the "buggy qsort" representation of binary trees from HW1:
+   [left_subtree, root, right_subtree]
+
+   >>> longest([[], 1, []])
+   0
+
+   >>> longest([[[], 1, []], 2, [[], 3, []]])
+   2
+
+   >>> longest([[[[], 1, []], 2, [[], 3, []]], 4, [[[], 5, []], 6, [[], 7, [[], 9, []]]]])
+   5
+
+   Note the answer is 5 because the longest path is 1-2-4-6-7-9.   
+
+   Filename: longest.py
+   Must run in O(n) time.
+
+Debriefing (required!): --------------------------
+
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+   Note you are encouraged to discuss with your classmates, 
+   but each students should submit his/her own code.
+4. How deeply do you feel you understand the material it covers (0%–100%)? 
+5. Any other comments?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+

code/cs325-langs/hws/hw3.txt

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+CS 325, Algorithms, Fall 2019
+HW3 - K closest numbers; Two Pointers
+
+Due Monday Oct 14, 11:59pm. (same submission instructions as HW1-2).
+No late submission will be accepted.
+
+Need to submit: report.txt, closest_unsorted.py, closest_sorted.py, xyz.py.
+closest_sorted.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw3 report.txt {closest*,xyz}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw3
+
+
+1. Given an array A of n numbers, a query x, and a number k,
+   find the k numbers in A that are closest (in value) to x.
+   For example:
+
+   find([4,1,3,2,7,4], 5.2, 2)	returns   [4,4]
+   find([4,1,3,2,7,4], 6.5, 3)	returns   [4,7,4]
+   find([5,3,4,1,6,3], 3.5, 2)	returns   [3,4]
+
+
+   Filename: closest_unsorted.py
+   Must run in O(n) time. 
+   The elements in the returned list must be in the original order.
+   In case two numbers are equally close to x, choose the earlier one.
+
+
+2. [WILL BE GRADED]
+   Now what if the input array is sorted? Can you do it faster?
+
+   find([1,2,3,4,4,7], 5.2, 2) returns   [4,4]
+   find([1,2,3,4,4,7], 6.5, 3) returns   [4,4,7]
+
+   Filename: closest_sorted.py
+   Must run in O(logn + k) time.
+   The elements in the returned list must be in the original order.
+
+   Note: in case two numbers are equally close to x, choose the smaller one:
+   find([1,2,3,4,4,6,6], 5, 3) returns   [4,4,6]
+   find([1,2,3,4,4,5,6], 4, 5) returns   [2,3,4,4,5]
+
+   Hint: you can use Python's bisect.bisect for binary search.
+
+
+3. For a given array A of n *distinct* numbers, find all triples (x,y,z) 
+   s.t. x + y = z. (x, y, z are distinct numbers)
+
+   e.g.,
+   
+   find([1, 4, 2, 3, 5]) returns [(1,3,4), (1,2,3), (1,4,5), (2,3,5)]
+
+   Note that:
+   1) no duplicates in the input array
+   2) you can choose any arbitrary order for triples in the returned list.
+
+   Filename: xyz.py
+   Must run in O(n^2) time.
+
+   Hint: you can use any built-in sort in Python.
+
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+   Note you are encouraged to discuss with your classmates, 
+   but each students should submit his/her own code.
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+
+5. Which part(s) of the course you like the most so far?
+6. Which part(s) of the course you dislike the most so far?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+

code/cs325-langs/hws/hw4.txt

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+CS 325-001, Algorithms, Fall 2019
+HW4 - Priority Queue and Heaps
+
+Due via the submit program on Monday Oct 21, 11:59pm.
+No late submission will be accepted.
+
+Need to submit: report.txt, nbest.py, kmergesort.py, datastream.py.
+datastream.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw4 report.txt {nbest,kmergesort,datastream}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw4
+
+
+Textbooks for References:
+[1] CLRS Ch. 6
+[2] KT slides for binary heaps (only read the first 20 pages!): 
+    https://www.cs.princeton.edu/~wayne/kleinberg-tardos/pdf/BinomialHeaps.pdf
+[3] Python heapq module 
+
+0. There are two methods for building a heap from an unsorted array:
+   (1) insert each element into the heap  --- O(nlogn) -- heapq.heappush()
+   (2) heapify (top-down)                 --- O(n)     -- heapq.heapify()
+
+   (a) Derive these time complexities.
+   (b) Use a long list of random numbers to show the difference in time. (Hint: random.shuffle or random.sample)
+   (c) What about sorted or reversely-sorted numbers?
+
+1. Given two lists A and B, each with n integers, return
+   a sorted list C that contains the smallest n elements from AxB:
+
+     AxB = { (x, y) | x in A, y in B }
+
+   i.e., AxB is the Cartesian Product of A and B.
+
+   ordering:  (x,y) < (x',y') iff. x+y < x'+y' or (x+y==x'+y' and y<y')
+
+   You need to implement three algorithms and compare:
+
+   (a) enumerate all n^2 pairs, sort, and take top n.
+   (b) enumerate all n^2 pairs, but use qselect from hw1.
+   (c) Dijkstra-style best-first, only enumerate O(n) (at most 2n) pairs.
+       Hint: you can use Python's heapq module for priority queue.
+
+   Q: What are the time complexities of these algorithms? 
+
+   >>> a, b = [4, 1, 5, 3], [2, 6, 3, 4]
+   >>> nbesta(a, b)   # algorithm (a), slowest
+   [(1, 2), (1, 3), (3, 2), (1, 4)]
+   >>> nbestb(a, b)   # algorithm (b), slow
+   [(1, 2), (1, 3), (3, 2), (1, 4)]
+   >>> nbestc(a, b)   # algorithm (c), fast
+   [(1, 2), (1, 3), (3, 2), (1, 4)]
+
+   Filename: nbest.py
+
+2. k-way mergesort (the classical mergesort is a special case where k=2).
+
+   >>> kmergesort([4,1,5,2,6,3,7,0], 3)  # k=3
+   [0,1,2,3,4,5,6,7]
+
+   Q: What is the complexity? Write down the detailed analysis in report.txt.
+
+   Filename: kmergesort.py
+
+3. [WILL BE GRADED]
+   
+   Find the k smallest numbers in a data stream of length n (k<<n),
+   using only O(k) space (the stream itself might be too big to fit in memory).
+
+   >>> ksmallest(4, [10, 2, 9, 3, 7, 8, 11, 5, 7])
+   [2, 3, 5, 7]
+   >>> ksmallest(3, range(1000000, 0, -1))
+   [1, 2, 3]
+
+   Note: 
+   a) it should work with both lists and lazy lists
+   b) the output list should be sorted
+
+   Q: What is your complexity? Write down the detailed analysis in report.txt.
+   
+   Filename: datastream.py
+
+   [UPDATE] The built-in function heapq.nsmallest() is _not_ allowed for this problem.
+   	    The whole point is to implement it yourself. :)
+
+
+4. (optional) Summarize the time complexities of the basic operations (push, pop-min, peak, heapify) for these implementations of priority queue:
+   
+   (a) unsorted array
+   (b) sorted array (highest priority first)
+   (c) reversly sorted array (lowest priority first)
+   (d) linked list
+   (e) binary heap
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+   Note you are encouraged to discuss with your classmates, 
+   but each students should submit his/her own code.
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Which part(s) of the course you like the most so far?
+6. Which part(s) of the course you dislike the most so far?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.
+

code/cs325-langs/hws/hw5.txt

@@ -0,0 +1,130 @@
+CS 532-001, Algorithms, Fall 2019
+HW5 - DP (part 1: simple)
+
+HWs 5-7 are all on DPs.
+
+Due Monday Oct 28, 11:59pm.
+No late submission will be accepted.
+
+Need to submit report.txt, mis.py, bsts.py, bitstrings.py.
+mis.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw5 report.txt {mis,bsts,bitstrings}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw5
+
+
+Textbooks for References:
+[1] CLRS Ch. 15
+[2] KT Ch. 6
+    or Ch. 5 in a previous version:
+    http://cs.furman.edu/~chealy/cs361/kleinbergbook.pdf   
+
+Hint: Among the three coding questions, p3 is the easiest, and p1 is similar to p3.
+      You'll realize that both are very similar to p0 (Fibonacci).
+      p2 is slightly different from these, but still very easy.
+
+0. (Optional) Is Fibonacci REALLY O(n)?
+   Hint: the value of f(n) itself grows exponentially.	    
+
+1. [WILL BE GRADED]
+   Maximum Weighted Independent Set 
+
+   [HINT] independent set is a set where no two numbers are neighbors in the original list.
+   	  see also https://en.wikipedia.org/wiki/Independent_set_(graph_theory)
+
+   input:  a list of numbers (could be negative)
+   output: a pair of the max sum and the list of numbers chosen
+
+   >>> max_wis([7,8,5])
+   (12, [7,5])
+
+   >>> max_wis([-1,8,10])
+   (10, [10])
+
+   >>> max_wis([])
+   (0, [])
+
+   [HINT] if all numbers are negative, the optimal solution is 0,
+          since [] is an independent set according to the definition above.
+
+   >>> max_wis([-5, -1, -4])
+   (0, [])
+
+   Q: What's the complexity?
+   
+   Include both top-down (max_wis()) and bottom-up (max_wis2()) solutions, 
+   and make sure they produce exact same results. 
+   We'll only grade the top-down version.
+
+   Tie-breaking: any best solution is considered correct.
+
+   Filename: mis.py
+
+   [HINT] you can also use the naive O(2^n) exhaustive search method to verify your answer.
+   
+
+2. Number of n-node BSTs
+
+   input: n
+   output: number of n-node BSTs
+
+   >>> bsts(2)
+   2
+   >>> bsts(3)
+   5
+   >>> bsts(5)
+   42
+
+   [HINT] There are two 2-node BSTs:
+      2    1
+     /      \
+    1        2
+   Note that all other 2-node BSTs are *isomorphic* to either one.
+      
+   Qa: What's the complexity of this DP?
+   
+   Qb: What's the name of this famous number series?
+
+   Feel free to use any implementation style.
+   
+   Filename: bsts.py
+
+3. Number of bit strings of length n that has
+
+   1) no two consecutive 0s.
+   2) two consecutive 0s.
+   
+   >>> num_no(3)
+   5
+   >>> num_yes(3)
+   3
+
+   [HINT] There are three 3-bit 0/1-strings that have two consecutive 0s.
+            001  100  000
+          The other five 3-bit 0/1-strings have no two consecutive 0s:
+	    010  011  101  110  111
+
+   Feel free to choose any implementation style.
+
+   Filename: bitstrings.py
+
+   [HINT] Like problem 1, you can also use the O(2^n) exhaustive search method to verify your answer.
+
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Which part(s) of the course you like the most so far?
+6. Which part(s) of the course you dislike the most so far?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.

code/cs325-langs/hws/hw6.txt

@@ -0,0 +1,114 @@
+CS 325-001, Algorithms, Fall 2019
+HW6 - DP (part 2)
+
+Due on Monday Nov 4, 11:59pm.
+No late submission will be accepted.
+
+Need to submit: report.txt, knapsack_unbounded.py, knapsack_bounded.py.
+knapsack_bounded.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw6 report.txt knapsack*.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw6
+
+Textbooks for References:
+[1] KT Ch. 6.4
+    or Ch. 5.3 in a previous version:
+    http://cs.furman.edu/~chealy/cs361/kleinbergbook.pdf   
+[2] KT slides for DP (pages 1-37):
+    https://www.cs.princeton.edu/~wayne/kleinberg-tardos/pdf/06DynamicProgrammingI.pdf
+[3] Wikipedia: Knapsack (unbounded and 0/1)
+[4] CLRS Ch. 15
+
+Please answer time/space complexities for each problem in report.txt.
+
+0. For each of the coding problems below:
+   (a) Describe a greedy solution.
+   (b) Show a counterexample to the greedy solution.
+   (c) Define the DP subproblem 
+   (d) Write the recurrence relations
+   (e) Do not forget base cases
+   (f) Analyze the space and time complexities
+
+1. Unbounded Knapsack
+
+   You have n items, each with weight w_i and value v_i, and each has infinite copies.
+   **All numbers are positive integers.**
+   What's the best value for a bag of W?
+
+   >>> best(3, [(2, 4), (3, 5)])
+   (5, [0, 1])
+
+   the input to the best() function is W and a list of pairs (w_i, v_i).
+   this output means to take 0 copies of item 1 and 1 copy of item 2.
+
+   tie-breaking: *reverse* lexicographical: i.e., [1, 0] is better than [0, 1]:
+   (i.e., take as many copies from the first item as possible, etc.)
+
+   >>> best(3, [(1, 5), (1, 5)])
+   (15, [3, 0])
+
+   >>> best(3, [(1, 2), (1, 5)])
+   (15, [0, 3])
+
+   >>> best(3, [(1, 2), (2, 5)])
+   (7, [1, 1])
+
+   >>> best(58, [(5, 9), (9, 18), (6, 12)])
+   (114, [2, 4, 2])
+
+   >>> best(92, [(8, 9), (9, 10), (10, 12), (5, 6)])
+   (109, [1, 1, 7, 1])
+
+   Q: What are the time and space complexities?
+
+   filename: knapsack_unbounded.py
+
+2. [WILL BE GRADED] 
+   Bounded Knapsack
+
+   You have n items, each with weight w_i and value v_i, and has c_i copies.
+   **All numbers are positive integers.**
+   What's the best value for a bag of W?
+
+   >>> best(3, [(2, 4, 2), (3, 5, 3)])
+   (5, [0, 1])
+
+   the input to the best() function is W and a list of triples (w_i, v_i, c_i).
+
+   tie-breaking: same as in p1:
+
+   >>> best(3, [(1, 5, 2), (1, 5, 3)])
+   (15, [2, 1])
+
+   >>> best(3, [(1, 5, 1), (1, 5, 3)])
+   (15, [1, 2])
+
+   >>> best(20, [(1, 10, 6), (3, 15, 4), (2, 10, 3)])
+   (130, [6, 4, 1])
+
+   >>> best(92, [(1, 6, 6), (6, 15, 7), (8, 9, 8), (2, 4, 7), (2, 20, 2)])
+   (236, [6, 7, 3, 7, 2])
+
+   Q: What are the time and space complexities?
+
+   filename: knapsack_bounded.py
+
+   You are encouraged to come up with a few other testcases yourself to test your code!
+   
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Which part(s) of the course you like the most so far?
+6. Which part(s) of the course you dislike the most so far?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.

code/cs325-langs/hws/hw8.txt

@@ -0,0 +1,147 @@
+CS 325-001, Algorithms, Fall 2019
+HW8 - Graphs (part I); DP (part III)
+
+Due on Monday November 18, 11:59pm.
+No late submission will be accepted.
+
+Include in your submission: report.txt, topol.py, viterbi.py.
+viterbi.py will be graded for correctness (1%).
+
+To submit:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/submit hw8 report.txt {topol,viterbi}.py
+(You can submit each file separately, or submit them together.)
+
+To see your best results so far:
+flip $ /nfs/farm/classes/eecs/fall2019/cs325-001/query hw8
+
+Textbooks for References:
+[1] CLRS Ch. 23 (Elementary Graph Algorithms)
+[2] KT Ch. 3 (graphs), or Ch. 2 in this earlier version:
+    http://cs.furman.edu/~chealy/cs361/kleinbergbook.pdf
+[3] KT slides (highly recommend!):
+    https://www.cs.princeton.edu/~wayne/kleinberg-tardos/pdf/03Graphs.pdf
+[4] Jeff Erickson: Ch. 5 (Basic Graph Algorithms):
+    http://jeffe.cs.illinois.edu/teaching/algorithms/book/05-graphs.pdf
+[5] DPV Ch. 3, 4.2, 4.4, 4.7 (Dasgupta, Papadimitriou, Vazirani)
+    https://www.cs.berkeley.edu/~vazirani/algorithms/chap3.pdf (decomposition of graphs)
+    https://www.cs.berkeley.edu/~vazirani/algorithms/chap4.pdf (paths, shortest paths)
+[6] my advanced DP tutorial (up to page 16):
+    http://web.engr.oregonstate.edu/~huanlian/slides/COLING-tutorial-anim.pdf
+
+Please answer non-coding questions in report.txt.
+
+0. For the following graphs, decide whether they are
+   (1) directed or undirected, (2) dense or sparse, and (3) cyclic or acyclic:
+
+   (a) Facebook
+   (b) Twitter
+   (c) a family
+   (d) V=airports, E=direct_flights
+   (e) a mesh
+   (f) V=courses, E=prerequisites
+   (g) a tree
+   (h) V=linux_software_packages, E=dependencies
+   (i) DP subproblems for 0-1 knapsack
+
+   Can you name a very big dense graph?
+
+1. Topological Sort
+   
+   For a given directed graph, output a topological order if it exists.
+   
+   Tie-breaking: ARBITRARY tie-breaking. This will make the code 
+   and time complexity analysis a lot easier. 
+
+   e.g., for the following example:
+
+     0 --> 2 --> 3 --> 5 --> 6
+        /    \   |  /    \
+       /      \  v /      \
+     1         > 4         > 7
+
+   >>> order(8, [(0,2), (1,2), (2,3), (2,4), (3,4), (3,5), (4,5), (5,6), (5,7)])
+   [0, 1, 2, 3, 4, 5, 6, 7]
+
+   Note that order() takes two arguments, n and list_of_edges, 
+   where n specifies that the nodes are named 0..(n-1).
+
+   If we flip the (3,4) edge:
+
+   >>> order(8, [(0,2), (1,2), (2,3), (2,4), (4,3), (3,5), (4,5), (5,6), (5,7)])
+   [0, 1, 2, 4, 3, 5, 6, 7]
+
+   If there is a cycle, return None
+
+   >>> order(4, [(0,1), (1,2), (2,1), (2,3)])
+   None
+
+   Other cases:
+
+   >>> order(5, [(0,1), (1,2), (2,3), (3,4)])
+   [0, 1, 2, 3, 4]
+
+   >>> order(5, [])
+   [0, 1, 2, 3, 4]  # could be any order   
+
+   >>> order(3, [(1,2), (2,1)])
+   None
+
+   >>> order(1, [(0,0)]) # self-loop
+   None
+
+   Tie-breaking: arbitrary (any valid topological order is fine).
+   
+   filename: topol.py 
+
+   questions: 
+   (a) did you realize that bottom-up implementations of DP use (implicit) topological orderings?
+       e.g., what is the topological ordering in your (or my) bottom-up bounded knapsack code?
+   (b) what about top-down implementations? what order do they use to traverse the graph?
+   (c) does that suggest there is a top-down solution for topological sort as well? 
+
+2. [WILL BE GRADED]
+   Viterbi Algorithm For Longest Path in DAG (see DPV 4.7, [2], CLRS problem 15-1)
+   
+   Recall that the Viterbi algorithm has just two steps:
+   a) get a topological order (use problem 1 above)
+   b) follow that order, and do either forward or backward updates
+
+   This algorithm captures all DP problems on DAGs, for example,
+   longest path, shortest path, number of paths, etc.
+
+   In this problem, given a DAG (guaranteed acyclic!), output a pair (l, p) 
+   where l is the length of the longest path (number of edges), and p is the path. (you can think of each edge being unit cost)
+
+   e.g., for the above example:
+
+   >>> longest(8, [(0,2), (1,2), (2,3), (2,4), (3,4), (3,5), (4,5), (5,6), (5,7)])
+   (5, [0, 2, 3, 4, 5, 6])
+
+   >>> longest(8, [(0,2), (1,2), (2,3), (2,4), (4,3), (3,5), (4,5), (5,6), (5,7)])
+   (5, [0, 2, 4, 3, 5, 6]) 
+
+   >>> longest(8, [(0,1), (0,2), (1,2), (2,3), (2,4), (4,3), (3,5), (4,5), (5,6), (5,7), (6,7)])
+   (7, [0, 1, 2, 4, 3, 5, 6, 7])  # unique answer
+
+   Note that longest() takes two arguments, n and list_of_edges, 
+   where n specifies that the nodes are named 0..(n-1).
+
+   Tie-breaking: arbitrary. any longest path is fine.   
+
+   Filename: viterbi.py
+
+   Note: you can use this program to solve MIS, knapsacks, coins, etc.
+
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Any other comments?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.

code/cs325-langs/hws/hw9.txt

@@ -0,0 +1,166 @@
+CS 325, Algorithms, Fall 2019
+HW9 - Graphs (part 2), DP (part 4)
+
+Due Monday Nov 25, 11:59pm. 
+No late submission will be accepted.
+
+Include in your submission: report.txt, dijkstra.py, nbest.py.
+dijkstra.py will be graded for correctness (1%).
+
+Textbooks for References:
+[1] CLRS Ch. 22 (graph)
+[2] my DP tutorial (up to page 16):
+    http://web.engr.oregonstate.edu/~huanlian/slides/COLING-tutorial-anim.pdf
+[3] DPV Ch. 3, 4.2, 4.4, 4.7, 6 (Dasgupta, Papadimitriou, Vazirani)
+    https://www.cs.berkeley.edu/~vazirani/algorithms/chap3.pdf
+    https://www.cs.berkeley.edu/~vazirani/algorithms/chap4.pdf
+    https://www.cs.berkeley.edu/~vazirani/algorithms/chap6.pdf
+[4] KT Ch. 6 (DP)
+    http://www.aw-bc.com/info/kleinberg/assets/downloads/ch6.pdf
+[5] KT slides: Greedy II (Dijkstra)
+    http://www.cs.princeton.edu/~wayne/kleinberg-tardos/
+
+***Please answer time/space complexities for each problem in report.txt.
+
+1. [WILL BE GRADED]
+   Dijkstra (see CLRS 24.3 and DPV 4.4)
+   
+   Given an undirected graph, find the shortest path from source (node 0)
+   to target (node n-1). 
+   
+   Edge weights are guaranteed to be non-negative, since Dijkstra doesn't work
+   with negative weights, e.g.
+ 
+       3
+   0 ------ 1   
+     \    /
+    2 \  / -2
+       \/
+       2
+   
+   in this example, Dijkstra would return length 2 (path 0-2), 
+   but path 0-1-2 is better (length 1).
+
+   For example (return a pair of shortest-distance and shortest-path):
+   
+       1
+   0 ------ 1   
+     \    /  \
+    5 \  /1   \6
+       \/   2  \
+       2 ------ 3
+            
+   >>> shortest(4, [(0,1,1), (0,2,5), (1,2,1), (2,3,2), (1,3,6)])
+   (4, [0,1,2,3])
+
+   If the target node (n-1) is unreachable from the source (0),
+   return None:
+
+   >>> shortest(5, [(0,1,1), (0,2,5), (1,2,1), (2,3,2), (1,3,6)])
+   None
+
+   Another example:
+
+      1          1
+   0-----1    2-----3
+
+   >>> shortest(4, [(0,1,1), (2,3,1)])
+   None
+
+   Tiebreaking: arbitrary. Any shortest path would do.
+
+   Filename: dijkstra.py
+
+   Hint: please use heapdict from here:
+   https://raw.githubusercontent.com/DanielStutzbach/heapdict/master/heapdict.py
+
+   >>> from heapdict import heapdict
+   >>> h = heapdict()
+   >>> h['a'] = 3
+   >>> h['b'] = 1
+   >>> h.peekitem()
+   ('b', 1)
+   >>> h['a'] = 0
+   >>> h.peekitem()
+   ('a', 0)
+   >>> h.popitem()
+   ('a', 0)
+   >>> len(h)
+   1
+   >>> 'a' in h
+   False
+   >>> 'b' in h 
+   True
+
+   You don't need to submit heapdict.py; we have it in our grader.
+
+
+2. [Redo the nbest question from Midterm, preparing for HW10 part 3]
+
+   Given k pairs of lists A_i and B_i (0 <= i < k), each with n sorted numbers,
+   find the n smallest pairs in all the (k n^2) pairs.
+   We say (x,y) < (x', y') if and only if x+y < x'+y'.
+   Tie-breaking: lexicographical (i.e., prefer smaller x).
+
+   You can base your code on the skeleton from the Midterm:
+
+    from heapq import heappush, heappop
+    def nbest(ABs):    # no need to pass in k or n
+        k = len(ABs)
+        n = len(ABs[0][0])
+        def trypush(i, p, q):  # push pair (A_i,p, B_i,q) if possible
+            A, B = ABs[i] # A_i, B_i
+            if p < n and q < n and ______________________________:
+                heappush(h, (________________, i, p, q, (A[p],B[q])))
+                used.add((i, p, q))
+        h, used = ___________________                 # initialize
+        for i in range(k):  # NEED TO OPTIMIZE
+            trypush(______________)
+        for _ in range(n): 
+            _, i, p, q, pair = ________________
+            yield pair     # return the next pair (in a lazy list)
+            _______________________
+            _______________________
+
+
+    But recall we had two optimizations to speed up the first for-loop (queue initialization):
+
+    (1) using heapify instead of k initial pushes. You need to implement this (very easy).
+
+    (2) using qselect to choose top n out of the k bests. This one is OPTIONAL.
+
+    Analyze the time complexity for the version you implemented.
+ 
+    >>> list(nbest([([1,2,4], [2,3,5]), ([0,2,4], [3,4,5])])) 
+
+    [(0, 3), (1, 2), (0, 4)]
+
+    >>> list(nbest([([-1,2],[1,4]), ([0,2],[3,4]), ([0,1],[4,6]), ([-1,2],[1,5])])) 
+    [(-1, 1), (-1, 1)]
+
+    >>> list(nbest([([5,6,10,14],[3,5,10,14]),([2,7,9,11],[3,8,12,16]),([1,3,8,10],[5,9,10,11]),([1,2,3,5],[3,4,9,10]),([4,5,9,10],[2,4,6,11]),([4,6,10,13],[2,3,5,9]),([3,7,10,12],[1,2,5,10]),([5,9,14,15],[4,8,13,14])]))
+
+    [(1, 3), (3, 1), (1, 4), (2, 3)]
+
+    >>> list(nbest([([1,6,8,13],[5,8,11,12]),([1,2,3,5],[5,9,11,13]),([3,5,7,10],[4,6,7,11]),([1,4,7,8],[4,9,11,15]),([4,8,10,13],[4,6,10,11]),([4,8,12,15],[5,10,11,13]),([2,3,4,8],[4,7,11,15]),([4,5,10,15],[5,6,7,8])]))
+
+    [(1, 4), (1, 5), (1, 5), (2, 4)]
+
+    This problem prepares you for the hardest question in HW10 (part 3).
+
+    Filename: nbest.py
+       
+
+
+Debriefing (required!): --------------------------
+
+0. What's your name?
+1. Approximately how many hours did you spend on this assignment?
+2. Would you rate it as easy, moderate, or difficult?
+3. Did you work on it mostly alone, or mostly with other people?
+4. How deeply do you feel you understand the material it covers (0%-100%)? 
+5. Any other comments?
+
+This section is intended to help us calibrate the homework assignments. 
+Your answers to this section will *not* affect your grade; however, skipping it
+will certainly do.

code/cs325-langs/sols/hw1.lang

@@ -0,0 +1,19 @@
+qselect(xs,k) =
+    ~xs -> {
+        pivot <- xs[0]!
+        left <- xs[#0 <= pivot]
+        right <- xs[#0 > pivot]
+    } ->
+        if k > |left| + 1 then qselect(right, k - |left| - 1)
+        else if k == |left| + 1 then [pivot]
+        else qselect(left, k);
+
+_search(xs, k) =
+    if xs[1] == k then xs
+    else if xs[1] > k then _search(xs[0], k)
+    else _search(xs[2], k);
+
+sorted(xs) = sorted(xs[0]) ++ [xs[1]] ++ sorted(xs[2]);
+search(xs, k) = |_search(xs, k)| != 0;
+insert(xs, k) = _insert(k, _search(xs, k));
+_insert(k, xs) = if |xs| == 0 then xs << [] << k << [] else xs

code/cs325-langs/src/Common.hs

@@ -0,0 +1,15 @@
+module Common where
+import PythonAst
+import PythonGen
+import Text.Parsec
+
+compile :: (String -> String -> Either ParseError p) -> (p -> [PyStmt]) -> String -> IO ()
+compile p t f = do
+    let inputName = f ++ ".lang"
+    let outputName = f ++ ".py"
+    file <- readFile inputName
+    let either = p inputName file
+    case either of
+        Right prog -> writeFile outputName (translate $ t prog)
+        Left e -> print e
+

code/cs325-langs/src/LanguageOne.hs

@@ -0,0 +1,432 @@
+module LanguageOne where
+import qualified PythonAst as Py
+import Data.Bifunctor
+import Data.Char
+import Data.Functor
+import qualified Data.Map as Map
+import Data.Maybe
+import qualified Data.Set as Set
+import Text.Parsec
+import Text.Parsec.Char
+import Text.Parsec.Combinator
+import Control.Monad.State
+
+{- Data Types -}
+data PossibleType = List | Any deriving Eq
+
+data SelectorMarker = None | Remove
+
+data Op
+    = Add
+    | Subtract
+    | Multiply
+    | Divide
+    | Insert
+    | Concat
+    | LessThan
+    | LessThanEq
+    | GreaterThan
+    | GreaterThanEq 
+    | Equal
+    | NotEqual
+    | And
+    | Or
+
+data Selector = Selector String Expr
+
+data Expr
+    = Var String
+    | IntLiteral Int
+    | ListLiteral [Expr]
+    | Split Expr [Selector] Expr
+    | IfElse Expr Expr Expr
+    | BinOp Op Expr Expr
+    | FunctionCall Expr [Expr]
+    | LengthOf Expr
+    | Random
+    | Access Expr Expr SelectorMarker
+    | Parameter Int
+
+data Function = Function String [String] Expr
+
+data Prog = Prog [Function]
+
+{- Parser -}
+type Parser = Parsec String (Maybe Int)
+
+parseInt :: Parser Int
+parseInt = read <$> (many1 digit <* spaces)
+
+parseVar :: Parser String
+parseVar =
+    do
+        c <- satisfy (\c -> (isLetter c && isLower c) || c == '_')
+        cs <- many (satisfy isLetter <|> digit)
+        spaces
+        let var = c:cs
+        if var `elem` ["if", "then", "else", "rand"]
+        then fail "reserved"
+        else return var
+
+parseKwIf :: Parser ()
+parseKwIf = string "if" $> ()
+
+parseKwThen :: Parser ()
+parseKwThen = string "then" $> ()
+
+parseKwElse :: Parser ()
+parseKwElse = string "else" $> ()
+
+parseKwRand :: Parser Expr
+parseKwRand = string "rand" $> Random
+
+parseThis :: Parser Expr
+parseThis =
+    do
+        char '&'
+        contextNum <- getState
+        spaces
+        return (Var $ "context_" ++ show contextNum)
+
+parseList :: Parser Expr
+parseList = ListLiteral <$>
+    do
+        char '[' >> spaces
+        es <- sepBy parseExpr (char ',' >> spaces)
+        spaces >> char ']' >> spaces
+        return es
+
+parseSplit :: Parser Expr
+parseSplit =
+    do
+        char '~' >> spaces
+        e <- parseExpr
+        spaces >> string "->"
+        spaces >> char '{'
+        contextNum <- getState
+        putState $ return $ 1 + fromMaybe (-1) contextNum
+        es <- many1 (spaces >> parseSelector)
+        putState contextNum
+        spaces >> char '}' >> spaces >> string "->" >> spaces
+        e' <- parseExpr
+        spaces
+        return $ Split e es e'
+
+parseSelectorMarker :: Parser SelectorMarker
+parseSelectorMarker = (char '!' >> return Remove) <|> return None
+
+parseSelector :: Parser Selector
+parseSelector =
+    do
+        name <- parseVar
+        spaces >> string "<-" >> spaces
+        expr <- parseExpr
+        spaces
+        return $ Selector name expr
+
+parseIfElse :: Parser Expr
+parseIfElse =
+    do
+        parseKwIf >> spaces
+        ec <- parseExpr
+        spaces >> parseKwThen >> spaces
+        et <- parseExpr
+        spaces >> parseKwElse >> spaces
+        ee <- parseExpr
+        spaces
+        return $ IfElse ec et ee
+
+parseLength :: Parser Expr
+parseLength =
+    do
+        char '|' >> spaces
+        e <- parseExpr
+        spaces >> char '|' >> spaces
+        return $ LengthOf e
+
+parseParameter :: Parser Expr
+parseParameter =
+    do
+        char '#'
+        d <- digit
+        spaces
+        return $ Parameter $ read [d]
+
+parseParenthesized :: Parser Expr
+parseParenthesized =
+    do
+        char '(' >> spaces
+        e <- parseExpr
+        spaces >> char ')' >> spaces
+        return e
+
+parseBasicExpr :: Parser Expr
+parseBasicExpr = choice
+    [ IntLiteral <$> parseInt
+    , parseThis
+    , parseList
+    , parseSplit
+    , parseLength
+    , parseParameter
+    , parseParenthesized
+    , Var <$> try parseVar
+    , parseKwRand
+    , parseIfElse
+    ] 
+
+parsePostfix :: Parser (Expr -> Expr)
+parsePostfix = parsePostfixAccess <|> parsePostfixCall
+
+parsePostfixAccess :: Parser (Expr -> Expr)
+parsePostfixAccess =
+    do
+        char '[' >> spaces
+        e <- parseExpr
+        spaces >> char ']' >> spaces
+        marker <- parseSelectorMarker
+        spaces
+        return $ \e' -> Access e' e marker
+
+parsePostfixCall :: Parser (Expr -> Expr)
+parsePostfixCall =
+    do
+        char '(' >> spaces
+        es <- sepBy parseExpr (char ',' >> spaces)
+        char ')' >> spaces
+        return $ flip FunctionCall es
+
+parsePostfixedExpr :: Parser Expr
+parsePostfixedExpr =
+    do
+        eb <- parseBasicExpr
+        spaces
+        ps <- many parsePostfix
+        return $ foldl (flip ($)) eb ps
+
+parseOp :: String -> Op -> Parser Op
+parseOp s o = try (string s) >> return o
+
+parseLevel :: Parser Expr -> Parser Op -> Parser Expr
+parseLevel pe po =
+    do
+        start <- pe
+        spaces
+        ops <- many $ try $ do
+            op <- po
+            spaces
+            val <- pe
+            spaces
+            return (op, val)
+        spaces
+        return $ foldl (\l (o, r) -> BinOp o l r) start ops
+
+parseExpr :: Parser Expr
+parseExpr = foldl parseLevel parsePostfixedExpr
+    [ parseOp "*" Multiply, parseOp "/" Divide
+    , parseOp "+" Add, parseOp "-" Subtract
+    , parseOp "<<" Insert
+    , parseOp "++" Concat
+    , parseOp "<=" LessThanEq <|> parseOp ">=" GreaterThanEq <|>
+        parseOp "<" LessThan <|> parseOp ">" GreaterThan <|>
+        parseOp "==" Equal <|> parseOp "!=" NotEqual
+    , parseOp "&&" And <|> parseOp "||" Or
+    ]
+
+parseFunction :: Parser Function
+parseFunction =
+    do
+        name <- parseVar
+        spaces >> char '(' >> spaces
+        vs <- sepBy parseVar (char ',' >> spaces)
+        spaces >> char ')' >> spaces >> char '=' >> spaces
+        body <- parseExpr
+        spaces
+        return $ Function name vs body
+
+parseProg :: Parser Prog
+parseProg = Prog <$> sepBy1 parseFunction (char ';' >> spaces)
+
+parse :: SourceName -> String -> Either ParseError Prog
+parse = runParser parseProg Nothing 
+
+{- "Type" checker -}
+mergePossibleType :: PossibleType -> PossibleType -> PossibleType
+mergePossibleType List _ = List
+mergePossibleType _ List = List
+mergePossibleType _ _ = Any
+
+getPossibleType :: String -> Expr -> PossibleType
+getPossibleType s (Var s') = if s == s' then List else Any
+getPossibleType _ (ListLiteral _) = List
+getPossibleType s (Split _ _ e) = getPossibleType s e
+getPossibleType s (IfElse i t e) =
+    foldl1 mergePossibleType $ map (getPossibleType s) [i, t, e]
+getPossibleType _ (BinOp Insert _ _) = List
+getPossibleType _ (BinOp Concat _ _) = List
+getPossibleType _ _ = Any
+
+{- Translator -}
+type Translator = Control.Monad.State.State (Map.Map String [String], Int)
+
+currentTemp :: Translator String
+currentTemp = do
+    t <- gets snd
+    return $ "temp" ++ show t
+
+incrementTemp :: Translator String
+incrementTemp = do
+    modify (second (+1))
+    currentTemp
+
+hasLambda :: Expr -> Bool
+hasLambda (ListLiteral es) = any hasLambda es
+hasLambda (Split e ss r) =
+    hasLambda e || any (\(Selector _ e') -> hasLambda e') ss || hasLambda r
+hasLambda (IfElse i t e) = hasLambda i || hasLambda t || hasLambda e
+hasLambda (BinOp o l r) = hasLambda l || hasLambda r
+hasLambda (FunctionCall e es) = any hasLambda $ e : es
+hasLambda (LengthOf e) = hasLambda e
+hasLambda (Access e _ _) = hasLambda e
+hasLambda Parameter{} = True
+hasLambda _ = False
+
+translate :: Prog -> [Py.PyStmt]
+translate p = fst $ runState (translateProg p) (Map.empty, 0)
+
+translateProg :: Prog -> Translator [Py.PyStmt]
+translateProg (Prog fs) = concat <$> traverse translateFunction fs
+
+translateFunction :: Function -> Translator [Py.PyStmt]
+translateFunction (Function n ps ex) = do
+    let createIf p = Py.BinOp Py.Equal (Py.Var p) (Py.ListLiteral [])
+    let createReturn p = Py.IfElse (createIf p) [Py.Return (Py.Var p)] [] Nothing
+    let fastReturn = [createReturn p | p <- take 1 ps, getPossibleType p ex == List]
+    (ss, e) <- translateExpr ex
+    return $ return $ Py.FunctionDef n ps $ fastReturn ++ ss ++ [Py.Return e]
+
+translateSelector :: Selector -> Translator Py.PyStmt
+translateSelector (Selector n e) =
+    let
+        cacheCheck = Py.NotIn (Py.StrLiteral n) (Py.Var "cache")
+        cacheAccess = Py.Access (Py.Var "cache") [Py.StrLiteral n]
+        cacheSet = Py.Assign (Py.AccessPat (Py.Var "cache") [Py.StrLiteral n])
+        body e' = [ Py.IfElse cacheCheck [cacheSet e'] [] Nothing, Py.Return cacheAccess]
+    in
+        do
+            (ss, e') <- translateExpr e
+            vs <- gets fst
+            let callPrereq p = Py.Standalone $ Py.FunctionCall (Py.Var p) []
+            let prereqs = maybe [] (map callPrereq) $ Map.lookup n vs
+            return $ Py.FunctionDef n [] $ ss ++ prereqs ++ body e'
+
+translateExpr :: Expr -> Translator ([Py.PyStmt], Py.PyExpr)
+translateExpr (Var s) = do
+    vs <- gets fst
+    let sVar = Py.Var s
+    let expr = if Map.member s vs then Py.FunctionCall sVar [] else sVar
+    return ([], expr) 
+translateExpr (IntLiteral i) = return ([], Py.IntLiteral i)
+translateExpr (ListLiteral l) = do
+    tl <- mapM translateExpr l
+    return (concatMap fst tl, Py.ListLiteral $ map snd tl)
+translateExpr (Split e ss e') = do
+    vs <- gets fst
+    let cacheAssign = Py.Assign (Py.VarPat "cache") (Py.DictLiteral [])
+    let cacheStmt = [ cacheAssign | Map.size vs == 0 ]
+    let vnames = map (\(Selector n es) -> n) ss
+    let prereqs = snd $ foldl (\(ds, m) (Selector n es) -> (n:ds, Map.insert n ds m)) ([], Map.empty) ss
+    modify $ first $ Map.union prereqs
+    fs <- mapM translateSelector ss
+    (sts, te) <- translateExpr e'
+    modify $ first $ const vs
+    return (cacheStmt ++ fs ++ sts, te)
+translateExpr (IfElse i t e) = do
+    temp <- incrementTemp
+    let tempPat = Py.VarPat temp
+    (ists, ie) <- translateExpr i
+    (tsts, te) <- translateExpr t
+    (ests, ee) <- translateExpr e
+    let thenSts = tsts ++ [Py.Assign tempPat te]
+    let elseSts = ests ++ [Py.Assign tempPat ee]
+    let newIf = Py.IfElse ie thenSts [] $ Just elseSts
+    return (ists ++ [newIf], Py.Var temp)
+translateExpr (BinOp o l r) = do
+    (lsts, le) <- translateExpr l
+    (rsts, re) <- translateExpr r
+    (opsts, oe) <- translateOp o le re
+    return (lsts ++ rsts ++ opsts, oe)
+translateExpr (FunctionCall f ps) = do
+    (fsts, fe) <- translateExpr f
+    tps <- mapM translateExpr ps
+    return (fsts ++ concatMap fst tps, Py.FunctionCall fe $ map snd tps)
+translateExpr (LengthOf e) =
+    second (Py.FunctionCall (Py.Var "len") . return) <$> translateExpr e
+translateExpr (Access e Random m) = do
+    temp <- incrementTemp
+    (sts, ce) <- translateExpr e
+    let lenExpr = Py.FunctionCall (Py.Var "len") [Py.Var temp]
+    let randExpr = Py.FunctionCall (Py.Var "randint") [ Py.IntLiteral 0,  lenExpr ]
+    return (sts, singleAccess ce randExpr m)
+translateExpr (Access c i m) = do
+    (csts, ce) <- translateExpr c
+    (ists, ie) <- translateExpr i
+    temp <- incrementTemp
+    if hasLambda i
+    then return (csts ++ ists ++ [createFilterLambda temp ie m], Py.FunctionCall (Py.Var temp) [ce])
+    else return (csts ++ ists, singleAccess ce ie m)
+translateExpr (Parameter i) = return $ ([], Py.Var $ "arg" ++ show i)
+translateExpr _ = fail "Invalid expression"
+
+singleAccess :: Py.PyExpr -> Py.PyExpr -> SelectorMarker -> Py.PyExpr
+singleAccess c i None = Py.Access c [i]
+singleAccess c i Remove = Py.FunctionCall (Py.Member c "pop") [i]
+
+createFilterLambda :: String -> Py.PyExpr -> SelectorMarker -> Py.PyStmt
+createFilterLambda s e None = Py.FunctionDef s ["arg"]
+    [ Py.Assign (Py.VarPat "out") (Py.ListLiteral [])
+    , Py.For (Py.VarPat "arg0") (Py.Var "arg")
+        [ Py.IfElse e
+            [ Py.Standalone $ Py.FunctionCall (Py.Member (Py.Var "out") "append")
+                [ Py.Var "arg0" ]
+            ]
+            []
+            Nothing
+        ]
+    , Py.Return $ Py.Var "out"
+    ]
+createFilterLambda s e Remove = Py.FunctionDef s ["arg"]
+    [ Py.Assign (Py.VarPat "i") $ Py.IntLiteral 0
+    , Py.Assign (Py.VarPat "out") (Py.ListLiteral [])
+    , Py.While (Py.BinOp Py.LessThan (Py.Var "i") $ Py.FunctionCall (Py.Var "len") [Py.Var "arg"])
+        [ Py.IfElse e
+            [ Py.Standalone $ Py.FunctionCall (Py.Member (Py.Var "out") "append")
+                [ singleAccess (Py.Var "arg") (Py.Var "i") Remove
+                ]
+            ]
+            []
+            Nothing
+        , Py.Assign (Py.VarPat "i") (Py.BinOp Py.Add (Py.Var "i") (Py.IntLiteral 1))
+        ]
+    , Py.Return $ Py.Var "out"
+    ]
+
+translateOp :: Op -> Py.PyExpr -> Py.PyExpr -> Translator ([Py.PyStmt], Py.PyExpr)
+translateOp Add l r = return ([], Py.BinOp Py.Add l r)
+translateOp Subtract l r = return ([], Py.BinOp Py.Subtract l r)
+translateOp Multiply l r = return ([], Py.BinOp Py.Multiply l r)
+translateOp Divide l r = return ([], Py.BinOp Py.Divide l r)
+translateOp LessThan l r = return ([], Py.BinOp Py.LessThan l r)
+translateOp LessThanEq l r = return ([], Py.BinOp Py.LessThanEq l r)
+translateOp GreaterThan l r = return ([], Py.BinOp Py.GreaterThan l r)
+translateOp GreaterThanEq  l r = return ([], Py.BinOp Py.GreaterThanEq  l r)
+translateOp Equal l r = return ([], Py.BinOp Py.Equal l r)
+translateOp NotEqual l r = return ([], Py.BinOp Py.NotEqual l r)
+translateOp And l r = return ([], Py.BinOp Py.And l r)
+translateOp Or l r = return ([], Py.BinOp Py.Or l r)
+translateOp Concat l r = return ([], Py.BinOp Py.Add l r)
+translateOp Insert l r = do
+    temp <- incrementTemp
+    let assignStmt = Py.Assign (Py.VarPat temp) l
+    let appendFunc = Py.Member (Py.Var temp) "append"
+    let insertStmt = Py.Standalone $ Py.FunctionCall appendFunc [r]
+    return ([assignStmt, insertStmt], Py.Var temp)

code/cs325-langs/src/PythonAst.hs

@@ -0,0 +1,47 @@
+module PythonAst where
+
+data PyBinOp
+    = Add
+    | Subtract
+    | Multiply
+    | Divide
+    | LessThan
+    | LessThanEq
+    | GreaterThan
+    | GreaterThanEq 
+    | Equal
+    | NotEqual
+    | And
+    | Or
+
+data PyExpr
+    = BinOp PyBinOp PyExpr PyExpr
+    | IntLiteral Int
+    | StrLiteral String
+    | BoolLiteral Bool
+    | ListLiteral [PyExpr]
+    | DictLiteral [(PyExpr, PyExpr)]
+    | Lambda [PyPat] PyExpr
+    | Var String
+    | Tuple [PyExpr]
+    | FunctionCall PyExpr [PyExpr]
+    | Access PyExpr [PyExpr]
+    | Ternary PyExpr PyExpr PyExpr
+    | Member PyExpr String
+    | In PyExpr PyExpr
+    | NotIn PyExpr PyExpr
+
+data PyPat
+    = VarPat String
+    | IgnorePat
+    | TuplePat [PyPat]
+    | AccessPat PyExpr [PyExpr]
+
+data PyStmt
+    = Assign PyPat PyExpr
+    | IfElse PyExpr [PyStmt] [(PyExpr, [PyStmt])] (Maybe [PyStmt])
+    | While PyExpr [PyStmt]
+    | For PyPat PyExpr [PyStmt]
+    | FunctionDef String [String] [PyStmt]
+    | Return PyExpr
+    | Standalone PyExpr

code/cs325-langs/src/PythonGen.hs

@@ -0,0 +1,132 @@
+module PythonGen where
+import PythonAst
+import Data.List
+import Data.Bifunctor
+import Data.Maybe
+
+indent :: String -> String
+indent = ("    " ++)
+
+stmtBlock :: [PyStmt] -> [String]
+stmtBlock = concatMap translateStmt
+
+block :: String -> [String] -> [String]
+block s ss = (s ++ ":") : map indent ss
+
+prefix :: String -> PyExpr -> [PyStmt] -> [String]
+prefix s e sts = block (s ++ " " ++ translateExpr e) $ stmtBlock sts
+
+if_ :: PyExpr -> [PyStmt] -> [String]
+if_ = prefix "if"
+
+elif :: PyExpr -> [PyStmt] -> [String]
+elif = prefix "elif"
+
+else_ :: [PyStmt] -> [String]
+else_ = block "else" . stmtBlock
+
+while :: PyExpr -> [PyStmt] -> [String]
+while = prefix "while"
+
+parenth :: String -> String
+parenth s = "(" ++ s ++ ")"
+
+translateStmt :: PyStmt -> [String]
+translateStmt (Assign p e) = [translatePat p ++ " = " ++ translateExpr e]
+translateStmt (IfElse i t es e) =
+    if_ i t ++ concatMap (uncurry elif) es ++ maybe [] else_ e
+translateStmt (While c t) = while c t
+translateStmt (For x in_ b) = block head body
+    where
+        head = "for " ++ translatePat x ++ " in " ++ translateExpr in_
+        body = stmtBlock b
+translateStmt (FunctionDef s ps b) = block head body
+    where
+        head = "def " ++ s ++ "(" ++ intercalate "," ps ++ ")"
+        body = stmtBlock b
+translateStmt (Return e) = ["return " ++ translateExpr e]
+translateStmt (Standalone e) = [translateExpr e]
+
+precedence :: PyBinOp -> Int
+precedence Add = 3
+precedence Subtract = 3
+precedence Multiply = 4
+precedence Divide = 4
+precedence LessThan = 2
+precedence LessThanEq = 2
+precedence GreaterThan = 2
+precedence GreaterThanEq = 2
+precedence Equal = 2
+precedence And = 1
+precedence Or = 0
+
+opString :: PyBinOp -> String
+opString Add = "+"
+opString Subtract = "-"
+opString Multiply = "*"
+opString Divide = "/"
+opString LessThan = "<"
+opString LessThanEq = "<="
+opString GreaterThan = ">"
+opString GreaterThanEq = ">="
+opString Equal = "=="
+opString NotEqual = "!="
+opString And = "and"
+opString Or = "or"
+
+translateOp :: PyBinOp -> PyBinOp -> PyExpr -> String
+translateOp o o' =
+    if precedence o < precedence o'
+    then parenth . translateExpr
+    else translateExpr
+
+dictMapping :: PyExpr -> PyExpr -> String
+dictMapping f t = translateExpr f ++ ": " ++ translateExpr t
+
+list :: String -> String -> [PyExpr] -> String
+list o c es = o ++ intercalate ", " (map translateExpr es) ++ c
+
+translateExpr :: PyExpr -> String
+translateExpr (BinOp o l@(BinOp o1 _ _) r@(BinOp o2 _ _)) =
+    translateOp o o1 l ++ opString o ++ translateOp o o2 r
+translateExpr (BinOp o l@(BinOp o1 _ _) r) =
+    translateOp o o1 l ++ opString o ++ translateExpr r
+translateExpr (BinOp o l r@(BinOp o2 _ _)) =
+    translateExpr l ++ opString o ++ translateOp o o2 r
+translateExpr (BinOp o l r) =
+    translateExpr l ++ opString o ++ translateExpr r
+translateExpr (IntLiteral i) = show i
+translateExpr (StrLiteral s) = "\"" ++ s ++ "\""
+translateExpr (BoolLiteral b) = if b then "true" else "false"
+translateExpr (ListLiteral l) = list "[" "]" l
+translateExpr (DictLiteral l) =
+    "{" ++ intercalate ", " (map (uncurry dictMapping) l) ++ "}"
+translateExpr (Lambda ps e) = parenth (head ++ ": " ++ body)
+    where
+        head = "lambda " ++ intercalate ", " (map translatePat ps)
+        body = translateExpr e
+translateExpr (Var s) = s
+translateExpr (Tuple es) = list "(" ")" es
+translateExpr (FunctionCall f ps) = translateExpr f ++ list "(" ")" ps
+translateExpr (Access (Var s) e) = s ++ list "[" "]" e
+translateExpr (Access e@Access{} i) = translateExpr e ++ list "[" "]" i
+translateExpr (Access e i) = "(" ++ translateExpr e ++ ")" ++ list "[" "]" i
+translateExpr (Ternary c t e) =
+    translateExpr t ++ " if " ++ translateExpr c ++ " else " ++ translateExpr e
+translateExpr (Member (Var s) m) = s ++ "." ++ m
+translateExpr (Member e@Member{} m) = translateExpr e ++ "." ++ m
+translateExpr (Member e m) = "(" ++ translateExpr e ++ ")." ++ m
+translateExpr (In m c) =
+    "(" ++ translateExpr m ++ ") in (" ++ translateExpr c ++ ")"
+translateExpr (NotIn m c) =
+    "(" ++ translateExpr m ++ ") not in (" ++ translateExpr c ++ ")"
+
+translatePat :: PyPat -> String
+translatePat (VarPat s) = s
+translatePat IgnorePat = "_"
+translatePat (TuplePat ps) =
+    "(" ++ intercalate "," (map translatePat ps) ++ ")"
+translatePat (AccessPat e es) = translateExpr (Access e es)
+
+translate :: [PyStmt] -> String
+translate = intercalate "\n" . concatMap translateStmt

content/blog/00_cs325_languages_hw1.md

@@ -0,0 +1,509 @@
+---
+title: A Language for an Assignment - Homework 1
+date: 2019-12-27T23:27:09-08:00
+tags: ["Haskell", "Python", "Algorithms"]
+---
+
+On a rainy Oregon day, I was walking between classes with a group of friends.
+We were discussing the various ways to obfuscate solutions to the weekly
+homework assignments in our Algorithms course: replace every `if` with
+a ternary expression, use single variable names, put everything on one line.
+I said:
+
+> The
+{{< sidenote "right" "chad-note" "chad" >}}
+This is in reference to a meme, <a href="https://knowyourmeme.com/memes/virgin-vs-chad">Virgin vs Chad</a>.
+A "chad" characteristic is masculine or "alpha" to the point of absurdity.
+{{< /sidenote >}} move would be to make your own, different language for every homework assignment.
+
+It was required of us to use
+{{< sidenote "left" "python-note" "Python" >}}
+A friend suggested making a Haskell program
+that generates Python-based interpreters for languages. While that would be truly
+absurd, I'll leave <em>this</em> challenge for another day.
+{{< /sidenote >}} for our solutions, so that was the first limitation on this challenge.
+Someone suggested to write the languages in Haskell, since that's what we used
+in our Programming Languages class. So the final goal ended up:
+
+* For each of the 10 homework assignments in CS325 - Analysis of Algorithms,
+* Create a Haskell program that translates a language into,
+* A valid Python program that works (nearly) out of the box and passes all the test cases.
+
+It may not be worth it to create a whole
+{{< sidenote "right" "general-purpose-note" "general-purpose" >}}
+A general purpose language is one that's designed to be used in various
+domains. For instance, C++ is a general-purpose language because it can
+be used for embedded systems, GUI programs, and pretty much anything else.
+This is in contrast to a domain-specific language, such as Game Maker Language,
+which is aimed at a much narrower set of uses.
+{{< /sidenote >}} language for each problem,
+but nowhere in the challenge did we say that it had to be general-purpose. In
+fact, some interesting design thinking can go into designing a domain-specific
+language for a particular assignment. So let's jump right into it, and make
+a language for the first homework assignment.
+
+### Homework 1
+There are two problems in Homework 1. Here they are, verbatim:
+
+{{< codelines "text" "cs325-langs/hws/hw1.txt" 32 38 >}}
+
+And the second:
+
+{{< codelines "text" "cs325-langs/hws/hw1.txt" 47 68 >}}
+
+We want to make a language __specifically__ for these two tasks (one of which
+is split into many tasks). What common things can we isolate? I see two:
+
+First, __all the problems deal with lists__. This may seem like a trivial observation,
+but these two problems are the __only__ thing we use our language for. We have
+list access,
+{{< sidenote "right" "filterting-note" "list filtering" >}}
+Quickselect is a variation on quicksort, which itself
+finds all the "lesser" and "greater" elements in the input array.
+{{< /sidenote >}} and list creation. That should serve as a good base!
+
+If you squint a little bit, __all the problems are recursive with the same base case__.
+Consider the first few lines of `search`, implemented naively:
+
+```Python
+def search(xs, k):
+    if xs == []:
+        return false
+```
+
+How about `sorted`? Take a look:
+
+```Python
+def sorted(xs):
+    if xs == []:
+        return []
+```
+
+I'm sure you see the picture. But it will take some real mental gymnastics to twist the
+rest of the problems into this shape. What about `qselect`, for instance? There's two
+cases for what it may return:
+
+* `None` or equivalent if the index is out of bounds (we give it `4` an a list `[1, 2]`).
+* A number if `qselect` worked.
+
+The test cases never provide a concrete example of what should be returned from
+`qselect` in the first case, so we'll interpret it like
+{{< sidenote "right" "undefined-note" "undefined behavior" >}}
+For a quick sidenote about undefined behavior, check out how
+C++ optimizes the <a href="https://godbolt.org/z/3skK9j">Collatz Conjecture function</a>.
+Clang doesn't know whether or not the function will terminate (whether the Collatz Conjecture
+function terminates is an <a href="https://en.wikipedia.org/wiki/Collatz_conjecture">unsolved problem</a>),
+but functions that don't terminate are undefined behavior. There's only one other way the function
+returns, and that's with "1". Thus, clang optimizes the entire function to a single "return 1" call.
+{{< /sidenote >}} in C++:
+we can do whatever we want. So, let's allow it to return `[]` in the `None` case.
+This makes this base case valid:
+
+```Python
+def qselect(xs, k):
+    if xs == []:
+        return []
+```
+
+"Oh yeah, now it's all coming together." With one more observation (which will come
+from a piece I haven't yet shown you!), we'll be able to generalize this base case.
+
+The observation is this section in the assignment:
+
+{{< codelines "text" "cs325-langs/hws/hw1.txt" 83 98 >}}
+
+The real key is the part about "returning the `[]` where x should be inserted". It so
+happens that when the list given to the function is empty, the number should be inserted
+precisely into that list. Thus:
+
+```Python
+def _search(xs, k):
+    if xs == []:
+        return xs
+```
+
+The same works for `qselect`:
+
+```Python
+def qselect(xs, k):
+    if xs == []:
+        return xs
+```
+
+And for sorted, too:
+
+```Python
+def sorted(xs):
+    if xs == []:
+        return xs
+```
+
+There are some functions that are exceptions, though:
+
+```Python
+def insert(xs, k):
+    # We can't return early here!
+    # If we do, we'll never insert anything.
+```
+
+Also:
+
+```Python
+def search(xs, k):
+    # We have to return true or false, never
+    # an empty list.
+```
+
+So, whenever we __don't__ return a list, we don't want to add a special case.
+We arrive at the following common base case: __whenever a function returns a list, if its first argument
+is the empty list, the first argument is immediately returned__.
+
+We've largely exhasuted the conclusiosn we can draw from these problems. Let's get to designing a language.
+
+### A Silly Language
+Let's start by visualizing our goals. Without base cases, the solution to `_search`
+would be something like this:
+
+{{< codelines "text" "cs325-langs/sols/hw1.lang" 11 14 >}}
+
+Here we have an __`if`-expression__. It has to have an `else`, and evaluates to the value
+of the chosen branch. That is, `if true then 0 else 1` evaluates to `0`, while
+`if false then 0 else 1` evaluates to `1`. Otherwise, we follow the binary tree search
+algorithm faithfully.
+
+Using this definition of `_search`, we can define `search` pretty easily:
+
+{{< codelines "text" "cs325-langs/sols/hw1.lang" 17 17 >}}
+
+Let's use Haskell's `(++)` operator for concatentation. This will help us understand
+when the user is operating on lists, and when they're not. With this, `sorted` becomes:
+
+{{< codelines "text" "cs325-langs/sols/hw1.lang" 16 16 >}}
+
+Let's go for `qselect` now. We'll introduce a very silly language feature for this
+problem:
+{{< sidenote "right" "selector-note" "list selectors" >}}
+You've probably never heard of list selectors, and for a good reason:
+this is a <em>terrible</em> language feature. I'll go in more detail
+later, but I wanted to make this clear right away.
+{{< /sidenote >}}. We observe that `qselect` aims to partition the list into
+other lists. We thus add the following pieces of syntax:
+
+```
+~xs -> {
+    pivot <- xs[rand]!
+    left <- xs[#0 <= pivot]
+    ...
+} -> ...
+```
+
+There are three new things here.
+
+1. The actual "list selector": `~xs -> { .. } -> ...`. Between the curly braces
+are branches which select parts of the list and assign them to new variables.
+Thus, `pivot <- xs[rand]!` assigns the element at a random index to the variable `pivot`.
+the `!` at the end means "after taking this out of `xs`, delete it from `xs`". The
+syntax {{< sidenote "right" "curly-note" "starts with \"~\"" >}}
+An observant reader will note that there's no need for the "xs" after the "~".
+The idea was to add a special case syntax to reference the "selected list", but
+I ended up not bothering. So in fact, this part of the syntax is useless.
+{{< /sidenote >}} to make it easier to parse.
+2. The `rand` list access syntax. `xs[rand]` is a special case that picks a random
+element from `xs`.
+3. The `xs[#0 <= pivot]` syntax. This is another special case that selects all elements
+from `xs` that match the given predicate (where `#0` is replaced with each element in `xs`).
+
+The big part of qselect is to not evaluate `right` unless you have to. So, we shouldn't
+eagerly evaluate the list selector. We also don't want something like `right[|right|-1]` to evaluate
+`right` twice. So we settle on
+{{< sidenote "right" "lazy-note" "lazy evaluation" >}}
+Lazy evaluation means only evaluating an expression when we need to. Thus,
+although we might encounter the expression for <code>right</code>, we
+only evaluate it when the time comes. Lazy evaluation, at least
+the way that Haskell has it, is more specific: an expression is evaluated only
+once, or not at all.
+{{</ sidenote >}}.
+Ah, but the `!` marker introduces
+{{< sidenote "left" "side-effect-note" "side effects" >}}
+A side effect is a term frequently used when talking about functional programming.
+Evaluating the expression <code>xs[rand]!</code> doesn't just get a random element,
+it also changes <em>something else</em>. In this case, that something else is 
+the <code>xs</code> list.
+{{< /sidenote >}}. So we can't just evaluate these things all willy-nilly.
+So, let's make it so that each expression in the selector list requires the ones above it. Thus,
+`left` will require `pivot`, and `right` will require `left` and `pivot`. So,
+lazily evaluated, ordered expressions. The whole `qselect` becomes:
+
+{{< codelines "text" "cs325-langs/sols/hw1.lang" 1 9 >}}
+
+We've now figured out all the language constructs. Let's start working on
+some implementation!
+
+#### Implementation
+It would be silly of me to explain every detail of creating a language in Haskell
+in this post; this is neither the purpose of the post, nor is it plausible
+to do this without covering monads, parser combinators, grammars, abstract syntax
+trees, and more. So, instead, I'll discuss the _interesting_ parts of the
+implementation. 
+
+##### Temporary Variables
+Our language is expression-based, yes. A function is a single,
+arbitrarily complex expression (involving `if/else`, list
+selectors, and more). So it would make sense to translate
+a function to a single, arbitrarily complex Python expression.
+However, the way we've designed our language makes it
+not-so-suitable for converting to a single expression! For
+instance, consider `xs[rand]`. We need to compute the list,
+get its length, generate a random number, and then access
+the corresponding element in the list. We use the list
+here twice, and simply repeating the expression would not
+be very smart: we'd be evaluating twice. So instead,
+we'll use a variable, assign the list to that variable,
+and then access that variable multiple times.
+
+To be extra safe, let's use a fresh temporary variable
+every time we need to store something. The simplest
+way is to simply maintain a counter of how many temporary
+variables we've already used, and generate a new variable
+by prepending the word "temp" to that number. We start
+with `temp0`, then `temp1`, and so on. To keep a counter,
+we can use a state monad:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 269 269 >}}
+
+Don't worry about the `Map.Map String [String]`, we'll get to that in a bit.
+For now, all we have to worry about is the second element of the tuple,
+the integer counting how many temporary variables we've used. We can
+get the current temporary variable as follows:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 271 274 >}}
+
+We can also get a fresh temporary variable like this:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 276 279 >}}
+
+Now, the
+{{< sidenote "left" "" "code" >}}
+Since we are translating an expression, we must have the result of
+the translation yield an Python expression we can use in generating
+larger Python expressions. However, as we've seen, we occasionally
+have to use statements. Thus, the <code>translateExpr</code> function
+returns a <code>Translator ([Py.PyStmt], Py.PyExpr)</code>.
+{{< /sidenote >}}for generating a random list access looks like
+{{< sidenote "right" "ast-note" "this:" >}}
+The <code>Py.*</code> constructors are a part of a Python AST module I quickly
+threw together. I won't showcase it here, but you can always look at the
+source code for the blog (which includes this project)
+<a href="https://dev.danilafe.com/Web-Projects/blog-static">here</a>.
+{{< /sidenote >}}
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 364 369 >}}
+
+##### Implementing "lazy evaluation"
+Lazy evaluation in functional programs usually arises from
+{{< sidenote "right" "graph-note" "graph reduction" >}}
+Graph reduction, more specifically the <em>Spineless,
+Tagless G-machine</em> is at the core of the Glasgow Haskell
+Compiler (GHC). Simon Peyton Jones' earlier book,
+<em>Implementing Functional Languages: a tutorial</em>
+details an earlier version of the G-machine.
+{{< /sidenote >}}. However, Python is neither
+functional nor graph-based, and we only lazily
+evaluate list selectors. Thus, we'll have to do
+some work to get our lazy evaluation to work as we desire.
+Here's what I came up with:
+
+1. It's difficult to insert Python statements where they are
+needed: we'd have to figure out in which scope each variable
+has already been declared, and in which scope it's yet
+to be assigned. 
+2. Instead, we can use a Python dictionary, called `cache`,
+and store computed versions of each variable in the cache.
+3. It's pretty difficult to check if a variable
+is in the cache, compute it if not, and then return the
+result of the computation, in one expression. This is
+true, unless that single expression is a function call, and we have a dedicated
+function that takes no arguments, computes the expression if needed,
+and uses the cache otherwise. We choose this route.
+4. We have already promised that we'd evaluate all the selected
+variables above a given variable before evaluating the variable
+itself. So, each function will first call (and therefore
+{{< sidenote "right" "force-note" "force" >}}
+{{< todo >}}Explain forcing{{< /todo >}}
+{{< /sidenote >}}) the functions
+generated for variables declared above the function's own variable.
+5. To keep track of all of this, we use the already-existing state monad
+as a reader monad (that is, we clear the changes we make to the monad
+after we're done translating the list selector). This is where the `Map.Map String [String]`
+comes from.
+
+The `Map.Map String [String]` keeps track of variables that will be lazily computed,
+and also of the dependencies of each variable (the variables that need
+to be access before the variable itself). We compute such a map for
+each selector as follows: 
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 337 337 >}}
+
+We update the existing map using `Map.union`:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 338 338 >}}
+
+And, after we're done generating expressions in the body of this selector,
+we clear it to its previous value `vs`:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 341 341 >}}
+
+We generate a single selector as follows:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 307 320 >}}
+
+This generates a function definition statement, which we will examine in
+generated Python code later on.
+
+Solving the problem this way also introduces another gotcha: sometimes,
+a variable is produced by a function call, and other times the variable
+is just a Python variable. We write this as follows:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 322 327 >}}
+
+##### Special Case Insertion
+This is a silly language for a single homework assignment. I'm not
+planning to implement Hindley-Milner type inference, or anything
+of that sort. For the purpose of this language, things will be
+either a list, or not a list. And as long as a function __can__ return
+a list, it can also return the list from its base case. Thus,
+that's all we will try to figure out. The checking code is so
+short that we can include the whole snippet at once:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 258 266 >}}
+
+`mergePossibleType`
+{{< sidenote "right" "bool-identity-note" "figures out" >}}
+An observant reader will note that this is just a logical
+OR function. It's not, however, good practice to use
+booleans for types that have two constructors with no arguments.
+Check out this <a href="https://programming-elm.com/blog/2019-05-20-solving-the-boolean-identity-crisis-part-1/">
+Elm-based article</a> about this, which the author calls the
+Boolean Identity Crisis.
+{{< /sidenote >}}, given two possible types for an
+expression, the final type for the expression.
+
+There's only one real trick to this. Sometimes, like in
+`_search`, the only time we return something _known_ to be a list, that
+something is `xs`. Since we're making a list manipulation language,
+let's __assume the first argument to the function is a list__, and
+__use this information to determine expression types__. We guess
+types in a very basic manner otherwise: If you use the concatenation
+operator, or a list literal, then obviously we're working on a list.
+If you're returning the first argument of the function, that's also
+a list. Otherwise, it could be anything.
+
+My Haskell linter actually suggested a pretty clever way of writing
+the whole "add a base case if this function returns a list" code.
+Check it out:
+
+{{< codelines "Haskell" "cs325-langs/src/LanguageOne.hs" 299 305 >}}
+
+Specifically, look at the line with `let fastReturn = ...`. It
+uses a list comprehension: we take a parameter `p` from the list of
+parameter `ps`, but only produce the statements for the base case
+if the possible type computed using `p` is `List`.
+
+### The Output
+What kind of beast have we created? Take a look for yourself:
+```Python
+def qselect(xs,k):
+    if xs==[]:
+        return xs
+    cache = {}
+    def pivot():
+        if ("pivot") not in (cache):
+            cache["pivot"] = xs.pop(0)
+        return cache["pivot"]
+    def left():
+        def temp2(arg):
+            out = []
+            for arg0 in arg:
+                if arg0<=pivot():
+                    out.append(arg0)
+            return out
+        pivot()
+        if ("left") not in (cache):
+            cache["left"] = temp2(xs)
+        return cache["left"]
+    def right():
+        def temp3(arg):
+            out = []
+            for arg0 in arg:
+                if arg0>pivot():
+                    out.append(arg0)
+            return out
+        left()
+        pivot()
+        if ("right") not in (cache):
+            cache["right"] = temp3(xs)
+        return cache["right"]
+    if k>(len(left())+1):
+        temp4 = qselect(right(), k-len(left())-1)
+    else:
+        if k==(len(left())+1):
+            temp5 = [pivot()]
+        else:
+            temp5 = qselect(left(), k)
+        temp4 = temp5
+    return temp4
+def _search(xs,k):
+    if xs==[]:
+        return xs
+    if xs[1]==k:
+        temp6 = xs
+    else:
+        if xs[1]>k:
+            temp8 = _search(xs[0], k)
+        else:
+            temp8 = _search(xs[2], k)
+        temp6 = temp8
+    return temp6
+def sorted(xs):
+    if xs==[]:
+        return xs
+    return sorted(xs[0])+[xs[1]]+sorted(xs[2])
+def search(xs,k):
+    return len(_search(xs, k))!=0
+def insert(xs,k):
+    return _insert(k, _search(xs, k))
+def _insert(k,xs):
+    if k==[]:
+        return k
+    if len(xs)==0:
+        temp16 = xs
+        temp16.append([])
+        temp17 = temp16
+        temp17.append(k)
+        temp18 = temp17
+        temp18.append([])
+        temp15 = temp18
+    else:
+        temp15 = xs
+    return temp15
+```
+It's...horrible! All the `tempX` variables, __three layers of nested function declarations__, hardcoded cache access. This is not something you'd ever want to write.
+Even to get this code, I had to come up with hacks __in a language I created__.
+The first is the hack is to make the `qselect` function use the `xs == []` base
+case. This doesn't happen by default, because `qselect` doesn't return a list!
+To "fix" this, I made `qselect` return the number it found, wrapped in a
+list literal. This is not up to spec, and would require another function
+to unwrap this list.
+
+While `qselect` was struggling with not having the base case, `insert` had
+a base case it didn't need: `insert` shouldn't return the list itself
+when it's empty, it should insert into it! However, when we use the `<<`
+list insertion operator, the language infers `insert` to be a list-returning
+function itself, inserting into an empty list will always fail. So, we
+make a function `_insert`, which __takes the arguments in reverse__.
+The base case will still be generated, but the first argument (against
+which the base case is checked) will be a number, so the `k == []` check
+will always fail.
+
+That concludes this post. I'll be working on more solutions to homework
+assignments in self-made languages, so keep an eye out!

content/blog/09_compiler_polymorphism.md

@@ -0,0 +1,65 @@
+---
+title: Compiling a Functional Language Using C++, Part 9 - Polymorphism
+date: 2019-12-09T23:26:46-08:00
+tags: ["C and C++", "Functional Languages", "Compilers"]
+draft: true
+---
+
+Last time, we wrote some pretty interesting programs in our little language.
+We successfully expressed arithmetic and recursion. But there's one thing
+that we cannot express in our language without further changes: an `if` statement.
+
+Suppose we didn't want to add a special `if/else` expression into our language.
+Thanks to lazy evaluation, we can express it using a function:
+
+```
+defn if c t e = {
+    case c of {
+        True -> { t }
+        False -> { e }
+    }
+}
+```
+
+But an issue still remains: so far, our compiler remains __monomorphic__. That
+is, a particular function can only have one possible type for each one of its
+arguments. With our current setup, something like this
+{{< sidenote "right" "if-note" "would not work:" >}}
+In a polymorphically typed language, the inner <code>if</code> would just evaluate to
+<code>False</code>, and the whole expression to 3.
+{{< /sidenote >}}
+
+```
+if (if True False True) 11 3
+```
+
+This is because, for this to work, both of the following would need to hold (borrowing
+some of our notation from the [typechecking]({{< relref "03_compiler_typechecking.md" >}}) post):
+
+$$
+\\text{if} : \\text{Int} \\rightarrow \\text{Int}
+$$
+$$
+\\text{if} : \\text{Bool} \\rightarrow \\text{Bool}
+$$
+
+But using our rules so far, such a thing is impossible, since there is no way for
+\\(\text{Int}\\) to be unified with \\(\text{Bool}\\). We need a more powerful
+set of rules to describe our program's types. One such set of rules is
+the [Hindley-Milner type system](https://en.wikipedia.org/wiki/Hindley%E2%80%93Milner_type_system),
+which we have previously alluded to. In fact, the rules we came up
+with were already very close to Hindley-Milner, with the exception of two:
+__generalization__ and __instantiation__. Instantiation first:
+
+$$
+\frac
+{\\Gamma \\vdash e : \\sigma \\quad \\sigma' \\sqsubseteq \\sigma}
+{\\Gamma \\vdash e : \\sigma'}
+$$
+
+Next, generalization:
+$$
+\frac
+{\\Gamma \\vdash e : \\sigma \\quad \\alpha \\not \\in \\text{free}(\\Gamma)}
+{\\Gamma \\vdash e : \\forall a . \\sigma}
+$$

themes/vanilla/assets/scss/sidenotes.scss

@@ -1,7 +1,9 @@
 @import "style.scss";
 
-$sidenote-width: 350px;
-$sidenote-offset: 15px;
+$sidenote-width: 30rem;
+$sidenote-offset: 1.5rem;
+$sidenote-padding: 1rem;
+$sidenote-highlight-border-width: .2rem;
 
 .sidenote {
     &:hover {
@@ -11,15 +13,16 @@ $sidenote-offset: 15px;
         }
 
         .sidenote-content {
-            border: 2px dashed;
-            padding: 9px;
+            border: $sidenote-highlight-border-width dashed;
+            padding: $sidenote-padding -
+                ($sidenote-highlight-border-width - $standard-border-width);
             border-color: $primary-color;
         }
     }
 }
 
 .sidenote-label {
-    border-bottom: 2px solid $primary-color;
+    border-bottom: .2rem solid $primary-color;
 }
 
 .sidenote-checkbox {
@@ -30,7 +33,7 @@ $sidenote-offset: 15px;
     display: block;
     position: absolute;
     width: $sidenote-width;
-    margin-top: -1.5em;
+    margin-top: -1.5rem;
 
     &.sidenote-right {
         right: 0;
@@ -45,8 +48,8 @@ $sidenote-offset: 15px;
     @media screen and
         (max-width: $container-width + 2 * ($sidenote-width + 2 * $sidenote-offset)) {
         position: static;
-        margin-top: 10px;
-        margin-bottom: 10px;
+        margin-top: 1rem;
+        margin-bottom: 1rem;
         width: 100%;
         display: none;
 
@@ -55,16 +58,16 @@ $sidenote-offset: 15px;
         }
 
         &.sidenote-left {
-            margin-left: 0px;
+            margin-left: 0rem;
         }
 
         &.sidenote-right {
-            margin-right: 0px;
+            margin-right: 0rem;
         }
     }
 
     @include bordered-block;
-    padding: 10px;
+    padding: $sidenote-padding;
     box-sizing: border-box;
     text-align: left;
 }

themes/vanilla/assets/scss/style.scss

@@ -1,24 +1,28 @@
-$container-width: 800px;
+$container-width: 50rem;
+$standard-border-width: .075rem;
+
 $primary-color: #36e281;
 $primary-color-dark: darken($primary-color, 10%);
 $code-color: #f0f0f0;
 $code-color-dark: darken($code-color, 10%);
 $border-color: #bfbfbf;
+
 $font-heading: "Lora", serif;
 $font-body: "Raleway", serif;
 $font-code: "Inconsolata", monospace;
-$standard-border: 1px solid $border-color;
+
+$standard-border: $standard-border-width solid $border-color;
 
 @mixin bordered-block {
     border: $standard-border;
-    border-radius: 2px;
+    border-radius: .2rem;
 }
 
 body {
   font-family: $font-body;
-  font-size: 1.0em;
+  font-size: 1.0rem;
   line-height: 1.5;
-  margin-bottom: 1em;
+  margin-bottom: 1rem;
   text-align: justify;
 }
 
@@ -27,8 +31,8 @@ main {
 }
 
 h1, h2, h3, h4, h5, h6 {
-  margin-bottom: .1em;
-  margin-top: .5em;
+  margin-bottom: .1rem;
+  margin-top: .5rem;
   font-family: $font-heading;
   font-weight: normal;
   text-align: left;
@@ -49,7 +53,7 @@ code {
 
 pre code {
     display: block;
-    padding: 0.5em;
+    padding: 0.5rem;
     overflow-x: auto;
     background-color: $code-color;
 }
@@ -61,12 +65,12 @@ pre code {
   box-sizing: border-box;
 
   @media screen and (max-width: $container-width){
-    padding: 0em 1em 0em 1em;
+    padding: 0rem 1rem 0rem 1rem;
   }
 }
 
 .button, input[type="submit"] {
-  padding: 0.5em;
+  padding: 0.5rem;
   background-color: $primary-color;
   border: none;
   color: white;
@@ -87,7 +91,7 @@ pre code {
 nav {
   background-color: $primary-color;
   width: 100%;
-  margin: 1em 0px 1em 0px;
+  margin: 1rem 0rem 1rem 0rem;
 }
 
 nav a {
@@ -110,7 +114,7 @@ nav a {
 }
 
 .post-content {
-  margin-top: .5em;
+  margin-top: .5rem;
 }
 
 h1 {