• Due: Friday, Dec 02.
  • Notes:
    • This pset contains two solo problems worth 25 points.
    • This pset has 100 total points.
    • The problems needn’t be done in order. Feel free to jump around.
  • Submission:
    • In your yourFullName CS251 Fall 2016 Folder, create a Google Doc named yourFullName CS251 PS7.
    • At the top of your yourFullName CS251 PS7 doc, include your name, problem set number, date of submission, and an approximation of how long each problem part took.
    • For all parts of all problems, include all answers (including SML code) in your PS7 google doc. Format code using a fixed-width font, like Consolas or Courier New. You can use a small font size if that helps.
    • For Problem 1 (first solo problem), include the English answers to parts 1a and 1b (including any Racket code examples) in your PS7 google doc.
    • In Problems 2 through 5, you will create the following code files from starter files populating your ~wx/cs251/sml/ps7 directory on your wx Virtual Machine:
      • Problem 2: yourAccountName-marbles.sml
      • Problem 3: yourAccountName-TTTreeFuns.sml
      • Problem 4: yourAccountName-FunSet.sml
      • Problem 5: yourAccountName-OperationTreeSet.sml
        Drop copies of the above four files as well as TTTree.sml into in your ~/cs251/drop/ps07 drop folder on cs.wellesley.edu.
    • For Problems 2 through 5 you should include all functions from the four files named yourAccountName... in your Google Doc (so that I can comment on them).
    • For Problem 4b, don’t forget to include your English answers in your Google Doc.

Starting this Problem Set

Problems 2 through 5 involve starter files in the ~wx/cs251/sml/ps7 directory in your wx Virtual Machine.

To create this directory, execute the following two commands in a wx VM shell:

cd ~/cs251/sml
git pull origin master

1. Solo Problem: Conjunction Junction (10 points)

This is a solo problem. This means you must complete it entirely on your own without help from any other person and without consulting resources other than course materials or online documentation. You may ask Lyn for clarification, but not for help.

We have seen that Racket’s and is not a function, but syntactic sugar. For example, if exp1 and exp2 are expressions, (and exp1 exp2 ) desugars to (if exp1 exp2 #f).

Suppose we define a function and-fun as follows:

(define (and-fun a b) (if a b #f))

Although and and and-fun seem similar, there are some subtle but important differences between them.

  1. (8 points) For each of the following three function definitions using and, explain whether the defined functions would or would not have exactly the same behavior if and were replaced by and-fun. In this problem ``behavior’’ not only means the input/output behavior of the function, but also how much work it does (i.e., how many operations does it perform?) Behavior also includes errors; are there situations in which one of and or and-fun gives an error, but the other does not?

    Explain each answer. In cases where behaviors are different, give one or more concrete examples in which the two versions behave differently, and explain why they behave differently.

    (define (between x lo hi)
      (and (<= lo x) (<= x hi)))
    
    (define (first-positive? nums)
      (and (not (null? nums))
           (> (first nums) 0)))
    
    (define (all-negative? nums)
      (foldr and #t (map (λ (n) (< n 0)) nums)))

    Note: The all-negative? function above has a syntax error, but that is intentional. Understanding this error is part of the problem. Hint: is there still an error if and is replaced by and-fun in all-negative?.

  2. (2 points) Is Java’s && construct more like (1) Racket’s and or (2) the and-fun function defined above? Briefly explain your answer, using examples as appropriate.

2. Solo Problem: Losing Your Marbles (15 points)

This is a solo problem. This means you must complete it entirely on your own without help from any other person and without consulting resources other than course materials or online documentation. You may ask Lyn for clarification, but not for help.

Put all your definitions for this problem in the starter file ~/cs251/sml/ps7/marbles.sml. When you finish this problem, rename the file to yourAccountName-ps7-marbles.sml before you submit it.

In this problem, you will define an SML function satisfying the following specification:

val marbles: int -> int -> int list list

Assume that m is a non-negative integer and that c is a positive integer. Given m marbles and a row of c cups, marbles m c returns a sorted list of all configurations whereby all m marbles are distributed among the c cups. Each configuration should be a list of length c whose elements are integers between 0 and m and the sum of whose elements is m. The returned list should be ordered lexicographically (i.e., in dictionary order).

At the end of this problem description are numerous sample invocations of the marbles function.

Your task is to define the marbles function in SML so that it satisfies the above specification and has the same behavior as the sample invocations below.

Notes:

  • As usual, you should use divide/conquer/glue as your problem-solving strategy. Strive to make your solution as simple as possible. For example, do not use more base cases than are strictly necessary.

  • Don’t forget the very powerful notion of “wishful” thinking, in which you blindly apply a recursive function to smaller versions of the same problem and combine their results. Study the examples carefully to see how the result of a call to marbles is stitched together from the results of calls to “smaller” versions of marbles.

  • Your marbles function should generate the elements in sorted order without calling any kind of sorting function.

  • You are expected to use higher-order list functions where they can simplify your definition.

  • The stater file begins with the following helper functions, which you might find useful:

    fun cons x ys = x :: ys (* curried list consing operator *)
                          
    fun range lo hi = (* list all ints from lo up to (but not including) hi *)
      List.tabulate(hi - lo, fn i => i + lo)

    Reminder: these and other helper functions must be defined above your definition of marbles, because definition order matters in SML.

  • Feel free to define any additional auxiliary functions you find helpful.

  • To display elements beyond the default cutoff length for lists, use Control.Print.printLength := 100;

- Control.Print.printLength := 100;
val it = () : unit

- marbles 0 1;
val it = [[0]] : int list list

- marbles 0 2;
val it = [[0,0]] : int list list

- marbles 0 3;
val it = [[0,0,0]] : int list list

- marbles 0 4;
val it = [[0,0,0,0]] : int list list

- marbles 1 1;
val it = [[1]] : int list list

- marbles 1 2;
val it = [[0,1],[1,0]] : int list list

- marbles 1 3;
val it = [[0,0,1],[0,1,0],[1,0,0]] : int list list

- marbles 1 4;
val it = [[0,0,0,1],[0,0,1,0],[0,1,0,0],[1,0,0,0]] : int list list

- marbles 2 1;
val it = [[2]] : int list list

- marbles 2 2;
val it = [[0,2],[1,1],[2,0]] : int list list

- marbles 2 3;
val it = [[0,0,2],[0,1,1],[0,2,0],[1,0,1],[1,1,0],[2,0,0]] : int list list

- marbles 2 4;
val it =
  [[0,0,0,2],[0,0,1,1],[0,0,2,0],[0,1,0,1],[0,1,1,0],[0,2,0,0],[1,0,0,1],
   [1,0,1,0],[1,1,0,0],[2,0,0,0]] : int list list

- marbles 3 1;
val it = [[3]] : int list list

- marbles 3 2;
val it = [[0,3],[1,2],[2,1],[3,0]] : int list list

- marbles 3 3;
val it =
  [[0,0,3],[0,1,2],[0,2,1],[0,3,0],[1,0,2],[1,1,1],[1,2,0],[2,0,1],[2,1,0],
   [3,0,0]] : int list list

- marbles 3 4;
val it =
  [[0,0,0,3],[0,0,1,2],[0,0,2,1],[0,0,3,0],[0,1,0,2],[0,1,1,1],[0,1,2,0],
   [0,2,0,1],[0,2,1,0],[0,3,0,0],[1,0,0,2],[1,0,1,1],[1,0,2,0],[1,1,0,1],
   [1,1,1,0],[1,2,0,0],[2,0,0,1],[2,0,1,0],[2,1,0,0],[3,0,0,0]]
  : int list list

- marbles 4 1;
val it = [[4]] : int list list

- marbles 4 2;
val it = [[0,4],[1,3],[2,2],[3,1],[4,0]] : int list list

- marbles 4 3;
val it =
  [[0,0,4],[0,1,3],[0,2,2],[0,3,1],[0,4,0],[1,0,3],[1,1,2],[1,2,1],[1,3,0],
   [2,0,2],[2,1,1],[2,2,0],[3,0,1],[3,1,0],[4,0,0]] : int list list

- marbles 4 4;
val it =
  [[0,0,0,4],[0,0,1,3],[0,0,2,2],[0,0,3,1],[0,0,4,0],[0,1,0,3],[0,1,1,2],
   [0,1,2,1],[0,1,3,0],[0,2,0,2],[0,2,1,1],[0,2,2,0],[0,3,0,1],[0,3,1,0],
   [0,4,0,0],[1,0,0,3],[1,0,1,2],[1,0,2,1],[1,0,3,0],[1,1,0,2],[1,1,1,1],
   [1,1,2,0],[1,2,0,1],[1,2,1,0],[1,3,0,0],[2,0,0,2],[2,0,1,1],[2,0,2,0],
   [2,1,0,1],[2,1,1,0],[2,2,0,0],[3,0,0,1],[3,0,1,0],[3,1,0,0],[4,0,0,0]]
  : int list list

- marbles 5 1;
val it = [[5]] : int list list

- marbles 5 2;
val it = [[0,5],[1,4],[2,3],[3,2],[4,1],[5,0]] : int list list

- marbles 5 3;
val it =
  [[0,0,5],[0,1,4],[0,2,3],[0,3,2],[0,4,1],[0,5,0],[1,0,4],[1,1,3],[1,2,2],
   [1,3,1],[1,4,0],[2,0,3],[2,1,2],[2,2,1],[2,3,0],[3,0,2],[3,1,1],[3,2,0],
   [4,0,1],[4,1,0],[5,0,0]] : int list list

- marbles 5 4;
val it =
  [[0,0,0,5],[0,0,1,4],[0,0,2,3],[0,0,3,2],[0,0,4,1],[0,0,5,0],[0,1,0,4],
   [0,1,1,3],[0,1,2,2],[0,1,3,1],[0,1,4,0],[0,2,0,3],[0,2,1,2],[0,2,2,1],
   [0,2,3,0],[0,3,0,2],[0,3,1,1],[0,3,2,0],[0,4,0,1],[0,4,1,0],[0,5,0,0],
   [1,0,0,4],[1,0,1,3],[1,0,2,2],[1,0,3,1],[1,0,4,0],[1,1,0,3],[1,1,1,2],
   [1,1,2,1],[1,1,3,0],[1,2,0,2],[1,2,1,1],[1,2,2,0],[1,3,0,1],[1,3,1,0],
   [1,4,0,0],[2,0,0,3],[2,0,1,2],[2,0,2,1],[2,0,3,0],[2,1,0,2],[2,1,1,1],
   [2,1,2,0],[2,2,0,1],[2,2,1,0],[2,3,0,0],[3,0,0,2],[3,0,1,1],[3,0,2,0],
   [3,1,0,1],[3,1,1,0],[3,2,0,0],[4,0,0,1],[4,0,1,0],[4,1,0,0],[5,0,0,0]]
  : int list list

3. 2-3 Trees (25 points)

In this problem you will use SML to implement aspects of 2-3 trees, a particular search tree data structure that is guaranteed to be balanced.

Begin by skimming pages 1 through 7 of this handout on 2-3 trees. (I create this handout for CS230 in Fall, 2004, but we no longer teach 2-3 trees in that course).

In a 2-3 tree, there are three kinds of nodes: leaves, 2-nodes, and 3-nodes. Together, these can be expressed in SML as follows:

datatype TTTree = (* 2-3 tree of ints *)
    L (* Leaf *)
  | W of TTTree * int * TTTree (* tWo node *)
  | H of TTTree * int * TTTree * int * TTTree (* tHree node *)

For simplicity, we will only consider 2-3 trees of integers, though they can be generalized to handle any type of value.

For conciseness in constructing and displaying large trees, the three constructors have single-letter names. For example, below are the pictures of four sample 2-3 trees from the handout and how they would be expressed with these constructors:

pictures of four 2-3 trees

val t1 = W( W(W(L,1,L), 2, W(L,3,L)), 4, W(W(L,5,L), 6, W(L,7,L)))
val t2 = H( W(L,1,L), 2, H(L,3,L,4,L), 5, H(L,6,L,7,L))
val t3 = H( H(L,1,L,2,L), 3, W(L,4,L), 5, H(L,6,L,7,L))
val t4 = H( H(L,1,L,2,L), 3, H(L,4,L,5,L), 6, W(L,7,L))

As explained in the handout on 2-3 trees, a 2-3 tree is only valid it it satisfies two additional properties:

  1. The ordering property:
    • In a 2-node with left subtree l, value X, and right subtree r, (all values in l) ≤ X ≤ (all values in r).
    • In a 3-node with left subtree l, left value X, middle subtree l, right value Y, and right subtree r, (all values in l) ≤ X ≤ (all values in m) ≤ Y ≤ (all values in r).
  2. The height property (called path length invariant in the handout): in a 2-node or 3-node, the height of all subtrees must be exactly the same.

The height property guarantees that a valid 2-3 tree is balanced. Together, these two properties guarantee that a 2-3 tree is efficiently searchable.

Your ~wx/cs251/sml/ps7 folder includes the file TTTree.sml, which contains the TTTree dataytype defined above as well as numerous examples of valid and invalid 2-3 trees that are instances of this datatype. Note that t and vt are used for valid trees, io is used for invalidly ordered trees, and ih is used for invalid height trees.

tree name elements ordered? satisfies the height property?
t1 [1,…,7] Yes Yes, with height 3
t2 [1,…,7] Yes Yes, with height 2
t3 [1,…,7] Yes Yes, with height 2
t4 [1,…,7] Yes Yes, with height 2
vt0 [] Yes Yes, with height 0
vt2 [1,2] Yes Yes, with height 1
vt17 [1,…,17] Yes Yes, with height 3
vt20 [1,…,20] Yes Yes, with height 4
vt44 [1,…,44] Yes Yes, with height 5
vt92 [1,…,92] Yes Yes, with height 6
io2 [1,2] No Yes, with height 1
io7 [1,…,7] No Yes, with height 2
io17 [1,…,17] No Yes, with height 3
io20 [1,…,20] No Yes, with height 4
io44 [1,…,44] No Yes, with height 5
io92 [1,…,92] No Yes, with height 6
ih2 [1,2] Yes No
ih7 [1,…,7] Yes No
ih17 [1,…,17] Yes No
ih20 [1,…,20] Yes No
ih44 [1,…,44] Yes No
ih92 [1,…,92] Yes No

These trees are used to define two lists:

val validTrees = [vt0, vt2, t2, t3, t4, t1, vt17, vt20, vt44, vt92]

val invalidTrees = [io2, io7, io17, io20, io44, io92, 
                    ih2, ih9, ih17, ih20, ih44, ih92]

In this problem you will (1) implement a validity test for 2-3 trees and (2) implement the effcient 2-3 insertion algorithm from the handout on 2-3 trees.

Your ~wx/cs251/sml/ps7 folder also includes the starter file TTTreeFuns.sml. In this file, flesh out the missing definitions as specified below. When you finish this problem, rename the file to yourAccountName-TTTreeFuns.sml before you submit it.

  1. satisfiesOrderingProperty (7 points)

    In this part, you will implement a function satisfiesOrderingProperty: TTTree -> bool that takes an instance of the TTTree datatype and returns true if it satisfies the 2-3 tree ordering property and false if it does not. An easy way to do this is to define two helper functions:

    • elts: TTTree -> int list returns a list of all the elements of the tree in in-order — i.e.,
      • In a 2-node with left subtree l, value X, and right subtree r, all values in l are listed before X, which is listed before all elements in r.
      • In a 3-node with left subtree l, left value X, middle subtree l, right value Y, and right subtree r, all values in l are listed before X, which is listed before all values in m, which are listed before Y , which is listed before all values in r.
    • isSorted: int list -> bool returns true if the list of integers is in sorted order and false otherwise.

    For example:

    - elts vt17;
    val it = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17] : int list
    
    - elts io17;
    val it = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,17,16] : int list
    
    - isSorted(elts vt17);
    val it = true : bool
    
    - isSorted(elts io17);
    val it = false : bool

    Using these two helper functions, satisfiesOrderingProperty can be implemented as:

    fun satisfiesOrderingProperty t = isSorted(elts t)

    For example:

    - map satisfiesOrderingProperty validTrees;
    val it = [true,true,true,true,true,true,true,true,true,true] : bool list
    
    - map satisfiesOrderingProperty invalidTrees;
    val it = [false,false,false,false,false,false,true,true,true,true,true,true] : bool list

    Notes:

    • Once (and only once) execute

      use "TTTree.sml";

      to load the TTTree datatype and example trees. Then every time you change the file TTTreeFuns.sml, execute

      use "TTTreeFuns.sml"
    • If you haven’t done so already, read these notes on SML/NJ and Emacs SML Mode and follow the advice there. In particular, it is strongly recommended that you create an SML interpreter within a *sml* buffer in Emacs. Then you can use M-p and M-n to avoid retyping your test expressions.

    • You may need to execute Control.Print.printLength := 100; in order to see all the list elements.

    • Implement isSorted using the same zipping approach you used in PS3. You do zipping in SML via ListPair.zip from the ListPair module. List.all from the List module is also helpful.

  2. satisfiesHeightProperty (6 points)

    In this part, you will implement a function satisfiesHeightProperty: TTTree -> bool that takes an instance of the TTTree datatype and returns true if it satisfies the 2-3 tree height property and false if it does not. An easy way to do this is to define satisfiesHeightProperty as

    fun satisfiesHeightProperty t = Option.isSome (height t)

    where Option.isSome is a function from the Option module that determines if an option value is a SOME (vs. a NONE) and height is a function with type TTTree -> option int such that height t returns SOME h if t satisfies the height property with height h and otherwise returns NONE.

    Implement the height function by fleshing out this skeleton:

    (* height: TTTree -> int option *)
    fun height L = (* return an appropriate option value here *)
      | height (W(l, _, r)) =
        (case (height(l), height(r)) of (* put appropriate pattern clauses here *))
      | (* handle the H case here, similarly to the W case *)

    For example:

    - map height validTrees;
    val it = [SOME 0,SOME 1,SOME 2,SOME 2,SOME 2,SOME 3,SOME 3,SOME 4,SOME 5,SOME 6]
    : int option list
    
    - map height invalidTrees;
    val it = [SOME 1,SOME 2,SOME 3,SOME 4,SOME 5,SOME 6,NONE,NONE,NONE,NONE,NONE,NONE]
    : int option list

    Notes:

    • It’s important to enclose the case expressions within height in parens to distinguish the pattern clauses of the case expression from those of the height function definition.

    • Once height is defined, satisfiesHeightProperty is defined:

      - map satisfiesHeightProperty validTrees;
      val it = [true,true,true,true,true,true,true,true,true,true] : bool list
        
      - map satisfiesHeightProperty invalidTrees;
      val it = [true,true,true,true,true,true,
                false,false,false,false,false,false] : bool list
    • Once both satisfiesOrderingProperty and satisfiesHeightProperty are defined, it is trivial to define a function isValid: TTTree -> bool that returns true if a given 2-3 tree is valid and false otherwise.

      fun isValid t = satisfiesOrderingProperty t andalso satisfiesHeightProperty t
      
      - map isValid validTrees;
      val it = [true,true,true,true,true,true,true,true,true,true] : bool list
      
      - map isValid invalidTrees;
      val it = [false,false,false,false,false,false,
                false,false,false,false,false,false] : bool list
  3. insert (12 points) In this part, you will implement the insertion algorithm for 2-3 trees as described on pages 3 to 5 of the handout on 2-3 trees. You will not implement the special cases described on page 6 .

    The insertion algorithm is a recursive algorithm that uses the notion of a pseudo 2-node that is “kicked up” in certain cases and handled specially in the upward phase of the recursion. To distinguish an insertion result that is a regular 2-3 tree from a pseudo 2-node that is “kicked up”, we use the following datatype:

    datatype InsResult =
          Tree of TTTree
        | KickedUp of TTTree * int * TTTree (* pseudo 2-node "kicked up" from below *)

    You will implement 2-3 tree insertion via a pair of functions:

    • (insert v t) returns the new TTTree that results from inserting a given int v into a given tree t. insert has type int -> TTTree -> TTTree.

    • (ins v t) is a helper function that returns the instance of InsResult that results from inserting a given int v into a given tree t. ins has type int -> TTTree -> InsResult.

    Your implementation should flesh out the following code skeleton by turning the pictures on pages 3 to 5 from the handout on 2-3 trees into SML code.

    (* insert: int -> TTTree -> TTTree *)
    fun insert v t =
      case ins v t of
          Tree t => t
        | KickedUp(l, w, r) => W(l, w, r)
    and (* "and" glues together mutually recursive functions *)
    (* ins: int -> TTTree -> InsResult *)
        ins v L = KickedUp (L, v, L) 
      | ins v (W(l, X, r)) =
        if v <= X
        then (case ins v l of
                    Tree l' => Tree(W(l', X, r))
                  | KickedUp (l', w, m)  => Tree(H(l', w, m, X, r)))
        else (* flesh this out *)
      | (* handle an H node similarly to the W node based on rules from the handout *)

    Notes:

    • The ins function should only call ins recursively and should not call insert.

    • An easy way to test insert is to call the following listToTTTree function on a list of numbers generated by range. (These are already defined in your starter file.) Note that you may need to increase the print depth (via Control.Print.printDepth := 100) in order to see all the details of the printed trees:

      fun listToTTTree xs =
        foldl (fn (x,t) => insert x t) L xs
      
      fun range lo hi =
        if lo >= hi then [] else lo :: (range (lo + 1) hi)
      
      - listToTTTree (range 1 8);
      val it = W (W (W #,2,W #),4,W (W #,6,W #)) : TTTree
      
      - listToTTTree (range 1 17);
      val it = W (W (W #,4,W #),8,W (W #,12,W #)) : TTTree
      
      - Control.Print.printDepth := 100;
      val it = () : unit
      
      - listToTTTree (range 1 7);
      val it = H (W (L,1,L),2,W (L,3,L),4,H (L,5,L,6,L)) : TTTree
      
      - listToTTTree (range 1 18);
      val it =
        W
          (W (W (W (L,1,L),2,W (L,3,L)),4,W (W (L,5,L),6,W (L,7,L))),8,
           W
             (W (W (L,9,L),10,W (L,11,L)),12,
              H (W (L,13,L),14,W (L,15,L),16,W (L,17,L)))) : TTTree
      
      - listToTTTree (range 1 45);
      val it =
        W
          (W
             (W (W (W (L,1,L),2,W (L,3,L)),4,W (W (L,5,L),6,W (L,7,L))),8,
              W (W (W (L,9,L),10,W (L,11,L)),12,W (W (L,13,L),14,W (L,15,L)))),16,
           H
             (W (W (W (L,17,L),18,W (L,19,L)),20,W (W (L,21,L),22,W (L,23,L))),24,
              W (W (W (L,25,L),26,W (L,27,L)),28,W (W (L,29,L),30,W (L,31,L))),32,
              H
                (W (W (L,33,L),34,W (L,35,L)),36,W (W (L,37,L),38,W (L,39,L)),40,
                 W (W (L,41,L),42,H (L,43,L,44,L))))) : TTTree
    • Unfortunately, inserting elements in sequential order as above tends to create 2-3 trees with almost all 2-nodes and very few 3-nodes. It turns out a better way is to mix up the order of insertion as is done in the following code for makeTTTree. This results in trees that have a good mix of 2-nodes and 3-nodes:

      (* Return list that has all ints in nums, but those not divisible by 3
         come before those divisible by three *)
      fun arrangeMod3 nums =
        let val (zeroMod3, notZeroMod3) = 
                  List.partition (fn n => (n mod 3) = 0) nums
        in notZeroMod3 @ zeroMod3
        end
      
      (* Make a 2-3 tree with elements from 1 up to and including size. 
         Use arrangeMod3 to mix up numbers and lead to more 3-nodes
         than we'd get with sorted integers lists *)
      fun makeTTTree size =
        listToTTTree (arrangeMod3 (range 1 (size + 1)))
      
      - makeTTTree 17;
      val it =
        H
          (W (W (L,1,L),2,H (L,3,L,4,L)),5,W (H (L,6,L,7,L),8,H (L,9,L,10,L)),11,
           H (H (L,12,L,13,L),14,W (L,15,L),16,W (L,17,L))) : TTTree
      
      - makeTTTree 44;
      val it =
        W
          (W
             (W (W (W (L,1,L),2,H (L,3,L,4,L)),5,W (H (L,6,L,7,L),8,H (L,9,L,10,L))),
              11,
              W
                (W (H (L,12,L,13,L),14,H (L,15,L,16,L)),17,
                 W (H (L,18,L,19,L),20,H (L,21,L,22,L)))),23,
           W
             (W
                (W (H (L,24,L,25,L),26,H (L,27,L,28,L)),29,
                 W (H (L,30,L,31,L),32,H (L,33,L,34,L))),35,
              W
                (W (H (L,36,L,37,L),38,H (L,39,L,40,L)),41,
                 W (W (L,42,L),43,W (L,44,L))))) : TTTree
    • Finally, to test your insertion implementation more extensively, try (testInsert 1000) with the following function, which will use makeTTTree to create 2-3 trees containing 0 elements to 1000 elements and warn you of any invalid trees.

      fun testInsert upToSize =
        let val pairs = map (fn n => (n, makeTTTree n)) (range 0 (upToSize + 1))
            val (validPairs, invalidPairs) = List.partition (fn (_,t) => isValid t) 
                                                            pairs
            val wrongElts = List.filter (fn (n,t) => (elts t) <> (range 1 (n + 1))) 
                                        validPairs
        in if (null invalidPairs) andalso (null wrongElts) 
           then (print "Passed all test cases\n"; [])
           else if (not (null invalidPairs))
                then (print "There are invalid trees in the following cases\n"; 
                      invalidPairs)
                else (print "The elements or element order is wrong in the following cases\n"; 
                      wrongElts)
        end
      
      - testInsert 1000;
      Passed all test cases
      val it = [] : (int * TTTree) list

4. Fun Sets (25 points)

In SML, we can implement abstract data types in terms of familiar structures like lists and trees. But we can also use functions to implement data types. In this problem, you will investigate a compelling example of using functions to implement sets.

Your ~wx/cs251/sml/ps7 folder contains the starter file FunSet.sml. This includes the same SET signature we studied in class:

signature SET =
sig
    (* The type of sets *)
    type ''a t 

    (* An empty set *)
    val empty : ''a t

    (* Construct a single-element set from that element. *)
    val singleton : ''a -> ''a t

    (* Check if a set is empty. *)
    val isEmpty : ''a t -> bool

    (* Return the number of elements in the set. *)
    val size : ''a t -> int

    (* Check if a given element is a member of the given set. *)
    val member : ''a -> ''a t -> bool

    (* Construct a set containing the given element and all elements
       of the given set. *)
    val insert : ''a -> ''a t -> ''a t

    (* Construct a set containing all elements of the given set
       except for the given element. *)
    val delete : ''a -> ''a t -> ''a t

    (* Construct the union of two sets. *)
    val union : ''a t -> ''a t -> ''a t

    (* Construct the intersection of two sets. *)
    val intersection : ''a t -> ''a t -> ''a t

    (* Construct the difference of two sets
       (all elements in the first set but not in the second.) *)
    val difference : ''a t -> ''a t -> ''a t

    (* Construct a set from a list of elements.
       Do not assume the list elements are unique. *)
    val fromList : ''a list -> ''a t 

    (* Convert a set to a list without duplicates. 
       The elements in the resulting list may be in any order. *)
    val toList : ''a t -> ''a list

    (* Construct a set from a predicate function:
       the resulting set should contain all elements for which
       this predicate function returns true.

       This acts like math notation for sets.  For example:
         { x | x mod 3 = 0 }
       would be written:
         fromPred (fn x => x mod 3 = 0)
    *)
    val fromPred : (''a -> bool) -> ''a t

    (* Convert a set to a predicate function. *)
    val toPred : ''a t -> ''a -> bool

    (* Convert a set to a string representation, given a function
       that converts a set element into a string representation. *)
    val toString : (''a -> string) -> ''a t -> string

    (* Convert a set to a list without duplicates. 
       The elements in the resulting list may be in any order. *)
    val toList : ''a t -> ''a list

    (* Construct a set from a predicate function:
       the resulting set should contain all elements for which
       this predicate function returns true.

       This acts like math notation for sets.  For example:
         { x | x mod 3 = 0 }
       would be written:
         fromPred (fn x => x mod 3 = 0)
    *)
    val fromPred : (''a -> bool) -> ''a t

    (* Convert a set to a predicate function. *)
    val toPred : ''a t -> ''a -> bool

    (* Convert a set to a string representation, given a function
       that converts a set element into a string representation. *)
    val toString : (''a -> string) -> ''a t -> string

end

In this problem, you will flesh out the skeleton of the FunSet structure below. When you finish this probelm, you should rename this file to yourAccountName-FunSet.sml before you submit it.

exception Unimplemented (* Placeholder during development. *)
exception Unimplementable (* Impossible to implement *)

(* Implement a SET ADT using predicates to represent sets. *)
structure FunSet :> SET = struct

    (* Sets are represented by predicates. *)
    type ''a t = ''a -> bool 

    (* The empty set is a predicate that always returns false. *)
    val empty = fn _ => false

    (* The singleton set is a predicate that returns true for exactly one element *)
    val singleton x = fn y => x=y

    (* Determining membership is trivial with a predicate *)
    val member x pred = pred x

    (* complete this structure by replacing "raise Unimplemented"
       with implementations of each function. Many of the functions
       *cannot* be implemented; for those, use raise Unimplementable
       as there implementation *)
    fun isEmpty _ = raise Unimplemented
    fun size _ = raise Unimplemented
    fun member _ = raise Unimplemented
    fun insert _ = raise Unimplemented
    fun delete _ = raise Unimplemented
    fun union _ = raise Unimplemented
    fun intersection _ = raise Unimplemented
    fun difference _ = raise Unimplemented
    fun fromList _ = raise Unimplemented
    fun toList _ = raise Unimplemented
    fun fromPred _ = raise Unimplemented
    fun toPred _ = raise Unimplemented
    fun toString _ = raise Unimplemented

end

The fromPred and toPred operations are based on the observation that a membership predicate describes exactly which elements are in the set and which are not. Consider the following example:

- val s235 = fromPred (fn x => (x = 2) orelse (x = 3) orelse (x = 5));
val s235 = - : int t
- member 2 s235;
val it = true : bool
- member 3 s235;
val it = true : bool
- member 5 s235;
val it = true : bool
- member 4 s235;
val it = false : bool
- member 100 s235;
val it = false : bool

The set s235 consists of exactly those elements satisfying the predicate passed to fromPred – in this case, the integers 2, 3, and 5.

Defining sets in terms of predicates has many benefits. Most important, it is easy to specify sets that have infinite numbers of elements! For example, the set of all even integers can be expressed as:

fromPred (fn x => (x mod 2) = 0)

This predicate is true of even integers, but is false for all other integers. The set of all values of a given type is expressed as fromPred (fn x => true). Many large finite sets are also easy to specify. For example, the set of all integers between 251 and 6821 (inclusive) can be expressed as

fromPred (fn x => (x >= 251) && (x <= 6821))

Although defining sets in terms of membership predicates is elegant and has many benefits, it has some big downsides. The biggest one is that several functions in the SET signature simply cannot be implemented. You will explore this downside in this problem.

  1. (17 points) Flesh out the code skeleton for the FunSet structure in FunSet.sml. Some value bindings cannot be implement; for these, use raise Unimplementable as the implementation.

    At the end of the starter file are the following commented out test cases. Uncomment these test cases to test your implementation. Feel free to add additional tests.

    open FunSet
    
    (* range helper function *)                           
    fun range lo hi = if lo >= hi then [] else lo::(range (lo + 1) hi)
    
    (* Test an int pred set on numbers from 0 to 100, inclusive *)
    fun intPredSetToList predSet = List.filter (toPred predSet) (range 0 101)
    
    val mod2Set = fromPred (fn x => x mod 2 = 0)
    val mod3Set = fromPred (fn x => x mod 3 = 0)
    val lowSet = fromList (range 0 61)
    val highSet = fromList (range 40 101)
    val smallSet = insert 17 (insert 19 (insert 23 (singleton 42)))
    val smallerSet = delete 23 (delete 19 (delete 57 smallSet))
    
    (* Be sure to print all details *)                      
    val _ = Control.Print.printLength := 101;                
    
    val smallSetTest = intPredSetToList(smallSet)
    val smallerSetTest = intPredSetToList(smallerSet)
    val mod3SetTest = intPredSetToList(mod3Set)
    val mod2SetUnionMod3SetTest = intPredSetToList(union mod2Set mod3Set)
    val mod2SetIntersectionMod3SetTest = intPredSetToList(intersection mod2Set mod3Set)
    val mod2SetDifferenceMod3SetTest = intPredSetToList(difference mod2Set mod3Set)
    val mod3SetDifferenceMod2SetTest = intPredSetToList(difference mod3Set mod2Set)
    val bigIntersection = intPredSetToList(intersection (intersection lowSet highSet)
                                                        (intersection mod2Set mod3Set))
    val bigDifference = intPredSetToList(difference (difference lowSet highSet)
                                                    (difference mod2Set mod3Set))

    For the test expressions generating lists, the results are as follows:

    val smallSetTest = [17,19,23,42] : int list
    val smallerSetTest = [17,42] : int list
    val mod3SetTest =
      [0,3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,51,54,57,60,63,66,69,72,75,
       78,81,84,87,90,93,96,99] : int list
    val mod2SetUnionMod3SetTest =
      [0,2,3,4,6,8,9,10,12,14,15,16,18,20,21,22,24,26,27,28,30,32,33,34,36,38,39,
       40,42,44,45,46,48,50,51,52,54,56,57,58,60,62,63,64,66,68,69,70,72,74,75,76,
       78,80,81,82,84,86,87,88,90,92,93,94,96,98,99,100] : int list
    val mod2SetIntersectionMod3SetTest =
      [0,6,12,18,24,30,36,42,48,54,60,66,72,78,84,90,96] : int list
    val mod2SetDifferenceMod3SetTest =
      [2,4,8,10,14,16,20,22,26,28,32,34,38,40,44,46,50,52,56,58,62,64,68,70,74,76,
       80,82,86,88,92,94,98,100] : int list
    val mod3SetDifferenceMod2SetTest =
      [3,9,15,21,27,33,39,45,51,57,63,69,75,81,87,93,99] : int list
    val bigIntersection = [42,48,54,60] : int list
    val bigDifference =
      [0,1,3,5,6,7,9,11,12,13,15,17,18,19,21,23,24,25,27,29,30,31,33,35,36,37,39]
      : int list
  2. (8 points) For each function that you declared being unimplementable, explain in English why it is unimplementable. Give concrete examples where appropriate.

5. Operation Tree Sets (25 points)

A very different way of representing a set as a tree is to remember the structure of the set operations empty, insert, delete, union, intersection, and difference used to create the set. For example, consider the set t created as follows:

val s = (delete 4 (difference (union (union (insert 1 empty)
                                            (insert 4 empty))
                              (union (insert 7 empty)
                                     (insert 4 empty)))
                  (intersection (insert 1 empty)
                                (union (insert 1 empty)
                                       (insert 6 empty)))))

Abstractly, s is the singleton set {7}. But one concrete representation of s is the following operation tree:

picture of an sample operation tree

One advantage of using such operation trees to represent sets is that the empty, insert, delete, union, difference, and intersection operations are extremely cheap — they just create a new tree node with the operands as subtrees, and thus take constant time and space! But other operations, such as member and toList, can be more expensive than in other implementations.

In this problem, you are asked to flesh out the missing operations in the skeleton of the OperationTreeSet structure shown below. Your ~wx/cs251/sml/ps7 folder contains the starter file OperationTreeSet.sml. When you finish this problem, rename the file to yourAccountName-OperationTreeSet.sml before you submit it.

structure OperationTreeSet :> SET = struct

    datatype ''a t = Empty
                   | Insert of ''a * ''a t
                   | Delete of ''a * ''a t
                   | Union of ''a t * ''a t
                   | Intersection of ''a t * ''a t
                   | Difference of ''a t * ''a t
                                                               
    val empty = Empty
    fun insert x s = Insert(x,s)
    fun singleton x = Insert(x, Empty)
    fun delete x s = Delete(x, s)
    fun union s1 s2 = Union(s1,s2)
    fun intersection s1 s2 = Intersection(s1,s2)
    fun difference s1 s2 = Difference(s1,s2)

    fun member _ _ = raise Unimplemented  
    fun toList _ = raise Unimplemented
    fun isEmpty _ = raise Unimplemented
    fun size _  = raise Unimplemented
    fun toPred _ = raise Unimplemented
    fun toString eltToString _ = raise Unimplemented
    fun fromList _ = raise Unimplemented

    fun fromPred _ = raise Unimplementable

end

In the OperationTreeSet structure, the set datatype t is create by constructors Empty, Insert, Delete, Union, Intersection, and Difference. The empty, singleton, insert, delete, union, intersection, difference operations are easy and have been implemented for you. You are responsible for fleshing out the definitions of the member, toList, size, isEmpty, toPred, toString, and fromList operations.

Notes:

  • Your implementation of member should not use the toList function. Instead, it should be defined by case analysis on the structure of the operation tree.

  • Your toList function should also be defined by case analysis on the structure of the operation tree. The member function should not be used in the implementation of toList (because it can be very inefficient). Keep in mind that sets are unordered, and your toList function may return lists of elements in any order, but it should not have any duplicates.

  • In your toList definition, be very careful with including toList inside functional arguments, because this can often cause the same list to be calculated a tremendous number of times, leading to tests that take a very long time for large sets. If some of the test cases for large sets don’t return in a reasonable time, this is probably the cause.

  • Your implementation of size and isEmpty should use the toList function. Indeed, it is difficult to implement these functions by a direct case analysis on the operation tree. Note that size will only work correcty if the output of toList does not contain duplicates.

  • In the implementation of toString, the function String.concatWith is particularly useful.

  • In the implementation of fromList, for lists with >= 2 elements, you should first split the list into two (nearly) equal-length sublists using List.take and List.drop and union the results of turning the sublists into sets. This yields a height-balanced operation tree.

  • OperationTreeSet.sml ends with two collections of test cases. The first collection involves “small” sets that are defined without using fromList. The second collection involves “big” sets that are defined using fromList. The expected outputs to these tests can be found in this transcript file. Because of the way the testing functions are written, the integer elements in the outputs for member and toPred will be in sorted order from low to high, but the integers in the outputs for toList and toString may be in any order.

  • The testing code for most functions (all except for member and assumes that toList works correctly. So you must implement toList for for most of the tests to work.

Extra Credit: 2-3 Tree Deletion (20 points)

In SML, implement and test the 2-3 tree deletion algorithm presented in pages 8 through 11 of the handout on 2-3 trees.

Extra Credit: 2-3 Trees in Java (35 points)

Implement and test 2-3 tree insertion and deletion in Java. Compare the SML and Java implementations. Which features of which languages make the implementation easier and why?