1. cs784(Prasad)L34ADT1 Specification and Implementation of Abstract Data Types

2. cs784(Prasad)L34ADT2 Data Abstraction Clients –Interested in WHAT services a module provides, not HOW they are carried out. So, ignore details irrelevant to the overall behavior, for clarity. Implementors –Reserve the right to change the code, to improve performance. So, ensure that clients do not make unwarranted assumptions.

3. cs784(Prasad)L34ADT3 Specification of Data Types Type : Values + Operations Specify Syntax Semantics Signature of Ops Meaning of Ops Model-based Axiomatic( Algebraic ) Description in terms of Give axioms satisfied standard “primitive” data types by the operations

4. cs784(Prasad)L34ADT4 Syntax of LISP S-expr operations: nil, cons, car, cdr, null signatures: nil: S-expr cons: S-expr  S-expr  S-expr car: S-expr  S-expr cdr: S-expr  S-expr null: S-expr  boolean for every atom a: a : S-expr

5. cs784(Prasad)L34ADT5 Signature tells us how to form complex terms from primitive operations. Legal nil null(cons(nil,nil)) cons(car(nil),nil) Illegal nil(cons) null(null) cons(nil)

6. cs784(Prasad)L34ADT6 Semantics of +: What to expect? + : N x N  N 1 + 2 = 3 zero + succ(succ(zero)) = succ(succ(zero)) x + 0 = x 2 * (3 + 4) = 2 * 7 = 14 = 6 + 8 x * ( y + z) = y * x + x * z

7. cs784(Prasad)L34ADT7 Semantics of S-Expr : What to expect? null(nil) = true car(cons(nil,nil)) = nil null(cdr(cons(nil,cons(nil,nil)))) = false for all E,F in S-Expr car(cons( E, F )) = E null(cons( E, F )) = false

8. cs784(Prasad)L34ADT8 Formal Spec. of ADTs Characteristics of an “Adequate” Specification –Completeness ( No “undefinedness” ) –Consistency/Soundness ( No conflicting definitions ) MinimalityMinimality GOAL: Learn to write sound and complete algebraic(axiomatic) specifications of ADTs

9. cs784(Prasad)L34ADT9 Classification of Operations Observers –generate a value outside the type E.g., null in ADT S-expr Constructors –required for representing values in the type E.g., nil, cons, atoms a in ADT S-expr Non-constructors –remaining operations E.g., car, cdr in ADT S-expr

10. cs784(Prasad)L34ADT10 S-Expr in LISP a : S-Expr nil : S-Expr cons : S-Expr x S-Expr  S-Expr car : S-Expr  S-Expr cdr : S-Expr  S-Expr null : S-Expr  boolean Observers : null Constructors : a, nil, cons Non-constructors : car, cdr

11. cs784(Prasad)L34ADT11 Algebraic Spec Write axioms (equations) that characterize the meaning of all the operations. Describe the meaning of the observers and the non-constructors on all possible constructor patterns. Note the use of typed variables to abbreviate the definition. (“Finite Spec.”)

12. cs784(Prasad)L34ADT12 for all S, T in S-expr cdr(nil) = ?error? cdr(a) = ?error? cdr(cons(S,T)) = T car(nil) = ?error?car(a) = ?error? car(cons(S,T)) = S null(nil) = true null(a) = false null(cons(S,T)) = false acceptableOmitting the equation for “nil” implies that implementations that differ in the interpretation of “nil” are all equally acceptable.

13. cs784(Prasad)L34ADT13 S-Exprs car(a) cons(a,nil) car(cons(a,nil)) = a cons( car(cons(a,nil)), cdr(cons(a,a)) ) = cons( a, a )

14. cs784(Prasad)L34ADT14 If car and cdr are also regarded as constructors (as they generate values in the type), then the spec. must consider other cases to guarantee completeness (or provide sufficient justification for their omission). for all S in S-expr: null(car(S)) =... null(cdr(S)) =... Motivation for Classification : Minimality

15. cs784(Prasad)L34ADT15 ADT Table ( symbol table/directory ) empty : Table update : Key x Info x Table  Table lookUp: Key x Table  nfo lookUp(K,empty) = error lookUp(K,update(Ki, I, T)) = if K = Ki then I else lookUp(K,T) (“last update overrides the others”)

16. cs784(Prasad)L34ADT16 Table Tables empty update(5, “abc”, empty) update(10, “xyz”, update(5, “abc”, empty)) update(5, “xyz”, update(5, “abc”, empty)) (Search ) lookup (5, update(5, “xyz”, update(5, “abc”, empty)) ) lookup (5, update(5, “xyz”, update(5, “xyz”, empty)) ) lookup (5, update(5, “xyz”, empty) ) “xyz”

17. cs784(Prasad)L34ADT17 Implementations –Array-based –Linear List - based –Tree - based Binary Search Trees, AVL Trees, B-Trees etc –Hash Table - based These exhibit a common Table behavior, but differ in performance aspects (search time). Correctness of a program is assured even when the implementation is changed as long as the spec is satisfied.

18. cs784(Prasad)L34ADT18 (cont’d) Accounts for various other differences ( Data Invariants ) in implementation such as –Eliminating duplicates. –Retaining only the final binding. –Maintaining the records sorted on the key. –Maintaining the records sorted in terms of the frequency of use (a la caching).

19. cs784(Prasad)L34ADT19 A-list in LISP a : A nil : A-list cons : A x A-list  A-list car : A-list  A cdr : A-list  A-list null : A-list  boolean Observers : null, car Constructors : nil, cons Non-constructors : cdr

20. cs784(Prasad)L34ADT20 for all L in A-list cdr(cons(a,L)) = L car(cons(a,L)) = a null(nil) = true null(cons(a,L)) = false Consciously silent about nil-list.

21. cs784(Prasad)L34ADT21 Natural Numbers zero :  succ :   add :  x   iszero :   boolean observers : iszero constructors : zero, succ non-constructors : add Each number has a unique representation in terms of its constructors.

22. cs784(Prasad)L34ADT22 for all I,J in  add(I,J) = ? add(zero,I) = I add(succ(J), I) = succ(add(J,I)) iszero(I) = ? iszero(zero) = true iszero(succ(I)) = false

23. cs784(Prasad)L34ADT23 (cont’d) add(succ(succ(zero)), succ(zero)) = succ(succ(succ(zero)))  The first rule eliminates add from an expression, while the second rule simplifies the first argument to add.  Associativity, commutativity, and identity properties of add can be deduced from this definition through purely mechanical means.

24. cs784(Prasad)L34ADT24 A-list Revisted a : A nil : A-list list : A  A-list append : A-list x A-list  A-list null : A-list  boolean values – nil, list(a), append(nil, list(a)),...

25. cs784(Prasad)L34ADT25 Algebraic Spec constructors –nil, list, append observer isnull(nil) = true isnull(list(a)) = false isnull(append(L1,L2)) = isnull(L1) /\ isnull(L2)

26. cs784(Prasad)L34ADT26 Problem : Same value has multiple representation in terms of constructors. Solution : Add axioms for constructors. –Identity Rule append(L,nil) = L append(nil,L) = L –Associativity Rule append(append(L1,L2),L3) = append(L1, append(L2,L3))

27. cs784(Prasad)L34ADT27 Intuitive understanding of constructors The constructor patterns correspond to distinct memory/data patterns required to store/represent values in the type. The constructor axioms can be viewed operationally as rewrite rules to simplify constructor patterns. Specifically, constructor axioms correspond to computations necessary for equality checking and aid in defining a normal form. Cf. == vs equal in Java

28. cs784(Prasad)L34ADT28 Writing ADT Specs Idea: Specify “sufficient” axioms such that syntactically distinct terms (patterns) that denote the same value can be proven so. –Completeness Define non-constructors and observers on all possible constructor patterns –Consistency Check for conflicting reductions Note: A term essentially records the detailed history of construction of the value.

29. cs784(Prasad)L34ADT29 General Strategy for ADT Specs Syntax –Specify signatures and classify operations. Constructors –Write axioms to ensure that two constructor terms that represent the same value can be proven so. E.g., identity, associativity, commutativity rules.

30. cs784(Prasad)L34ADT30 Non-constructors –Provide axioms to collapse a non-constructor term into a term involving only constructors. Observers –Define the meaning of an observer on all constructor terms, checking for consistency. Implementation of a type An interpretation of the operations of the ADT that satisfies all the axioms.

31. cs784(Prasad)L34ADT31 Declarative Specification Let *: N x N  N denote integer multiplication. Equation: n * n = n Solution: n = 0 \/ n = 1. Let f : N x N  N denote a binary integer function. Equation: 0 f 0 = 0 Solution: f = “ multiplication ” \/ f = “ addition ” \/ f = “ subtraction ” \/...

32. cs784(Prasad)L34ADT32 Setfor all n, m in N, s in Set delete(n,empty) = empty delete(n,insert(m,s)) = if (n=m) then delete(n,s) ( invalid : s) else insert(m,delete(n,s)) delete(5, insert(5,insert(5,empty)) ) {5,5} == empty {} =/= insert(5,empty) [] [5,5] Set delete : Set [5]

33. cs784(Prasad)L34ADT33 Previous axioms capture “remove all occurrences” semantics. For “remove last occurrence” semantics: List for all n, m in N, s in List delete(n,empty) = empty delete(n,insert(m,s)) = if (n=m) then s else insert(m,delete(n,s)) delete(5, insert(5,insert(5,empty)) ) [5,5] == insert(5,empty) [5] List delete : List

34. cs784(Prasad)L34ADT34 Previous axioms capture “remove all / last occurrences” semantics. For “remove first occurrence” semantics: List for all n, m in N, s in List delete(n,empty) = empty delete(n,insert(m,s)) = if (n=m) and not (n in s) then s else insert(m,delete(n,s)) delete(1, insert(1,insert(2,insert(1,insert(5,empty)))) ) [5,1,2,1] == insert(1,insert(2,insert(5,empty))) [5,2,1] List delete : List

35. cs784(Prasad)L34ADT35 size: List vs Set size(insert(m,l)) = 1 + size(l) –E.g., size([2,2,2]) = 1 + size([2,2]) size(insert(m,s)) = if (m in s) then size(s) else 1 + size(s) –E.g., size({2,2,2}) = size({2,2}) = size ({2}) = 1

36. cs784(Prasad)L34ADT36 Model-based vs Algebraic A model-based specification of a type satisfies the corresponding axiomatic specification. Hence, algebraic spec. is “more abstract” than the model-based spec. Algebraic spec captures the least common- denominator (behavior) of all possible implementations.

37. cs784(Prasad)L34ADT37 Axiomatization: Algebraic Structures A set G with operation * forms a group if Closure: a,b  G implies a*b  G. Associativity: a,b,c  G implies a*(b *c) = (a*b)*c. Identity: There exists i  G such that i*a = a*i = a for all a  G. Inverses: For every a  G there exists an element ~a  G such that a * ~a = ~a * a = i. Examples: (Integers, +), but not ( N, +) (Reals  {0}, *), but not (Integers, *) (Permutation functions, Function composition)

38. cs784(Prasad)L34ADT38 Example car( cons( X, Y) ) = X cdr( cons (X, Y) ) = Y (define ( cons x y) (lambda (m) (cond ((eq? m ’first) x) (eq? m ’second) y) ) )) ; “closure” (define ( car z) (z ’first)) (define ( cdr z) (z ’second))

39. cs784(Prasad)L34ADT39 Applications of ADT spec Least common denominator of all possible implementations. –Focus on the essential behavior. An implementation is a refinement of ADT spec. – IMPL. = Behavior SPEC + Rep “impurities” –To prove equivalence of two implementations, show that they satisfy the same spec. –In the context of OOP, a class implements an ADT, and the spec. is a class invariant.

40. cs784(Prasad)L34ADT40 (Cont’d) Indirectly, ADT spec. gives us the ability to vary or substitute an implementation. – E.g., In the context of interpreter/compiler, a function definition and the corresponding calls (ADT FuncValues) together must achieve a fixed goal. However, there is freedom in the precise apportioning of workload between the two separate tasks: How to represent the function? How to carry out the call?

41. cs784(Prasad)L34ADT41 (Cont’d) ADT spec. are absolutely necessary to automate formal reasoning about programs. Theorem provers such as Boyer-Moore prover (NQTHM), LARCH, PVS, HOL, etc routinely use such axiomatization of types. Provides a theory of equivalence of values that enables design of a suitable canonical form. Identity  delete Associativity  remove parenthesis Commutativity  sort

42. cs784(Prasad)L34ADT42 Spec vs Impl The reason to focus on the behavioral aspects, ignoring efficiency details initially, is that the notion of a “best implementation” requires application specific issues and trade-offs. In other words, the distribution of work among the various operations is based on a chosen representation, which in turn, is dictated by the pragmatics of an application. However, in each potential implementation, there is always some operations that will be efficient while others will pay the price for this comfort.

43. cs784(Prasad)L34ADT43 Ordered Integer Lists null : oil  boolean nil : oil hd : oil  int tl : oil  oil ins : int x oil  oil order : int_list  oil Constructors: nil, ins Non-constructors: tl, order Observers: null, hd

44. cs784(Prasad)L34ADT44 Problem: –syntactically different, but semantically equivalent constructor terms ins(2,ins(5,nil)) = ins(5,ins(2,nil)) ins(2,ins(2,nil)) = ins(2,nil) –hd should return the smallest element. It is not the case that for all I in int, L in oil, hd(ins(I,L)) = I. This holds iff I is the minimum in ins(I,L). –Similarly for tl.

45. cs784(Prasad)L34ADT45 Axioms for Constructors Idempotence –for all ordered integer lists L; for all I in int ins(I, ins(I,L)) = ins(I,L) Commutativity –for all ordered integer lists L; for all I, J in int ins(I, ins(J,L)) = ins(J, ins(I,L)) Completeness : Any permutation can be generated by exchanging adjacent elements.

46. cs784(Prasad)L34ADT46 Axioms for Non-constructors tl(nil) = error tl(ins(I,L)) = ? tl(ins(I,nil)) = nil tl(ins(I,ins(J,L))) = I ins( J, tl(ins(I,L)) ) I > J => ins( I, tl(ins(J,L)) ) I = J => tl( ins( I,L ) ) (cf. constructor axioms for duplicate elimination ) order(nil) =nil order(cons(I,L))=ins(I,order(L))

47. cs784(Prasad)L34ADT47 Axioms for Observers hd(nil) = error hd(ins(I,nil)) = I hd(ins(I,ins(J,L))) = I hd( ins(I,L) ) I > J => hd( ins(J,L) ) I = J => hd( ins(I,L) ) null(nil) = true null(ins(I,L))= false

48. Scheme Implementation (define null null?) (define nil ’()) (define ins cons) (define (hd ol) *min* ) (define (tl ol) *list sans min* ) (define (order lis) *sorted list* ) cs784(Prasad)L34ADT48

49. Possible Implementations Representation Choice 1: –List of integers with duplicates ins is cons but hd and tl require linear-time search Representation Choice 2: –Sorted list of integers without duplicates ins requires search but hd and tl can be made more efficient Representation Choice 3: –Balanced-tree : Heap cs784(Prasad)L34ADT49