Lecture 7

1. Lecture 7 Data Abstraction. Pairs and Lists. (Sections 2.1.1 – 2.2.1) מבוא מורחב שיעור 7

2. Export only what is needed. Interface Implementation Procedural abstraction • Publish: name, number and type of arguments • (and conditions they must satisfy) • type of procedure’s return value • Guarantee: the behavior of the procedure • Hide: local variables and procedures, • way of implementation, • internal details, etc. מבוא מורחב שיעור 7

3. Export only what is needed. Interface Implementation Data-object abstraction • Publish:constructors, selectors • Guarantee: the behavior • Hide: local variables and procedures, • way of implementation, • internal details, etc. מבוא מורחב שיעור 7

4. An example: Rational numbers We would like to represent rational numbers. A rational number is a quotient a/b of two integers. Constructor: (make-rat a b) Selectors: (numer r) (denom r) Guarantee:(numer (make-rat a b)) = a (denom (make-rat a b)) = b מבוא מורחב שיעור 7

5. An example: Rational numbers We would like to represent rational numbers. A rational number is a quotient a/b of two integers. Constructor: (make-rat a b) Selectors: (numer r) (denom r) A betterGuarantee: (numer (make-rat a b)) a = b (denom (make-rat a b)) A weaker condition, but still sufficient! מבוא מורחב שיעור 7

6. We can now use the constructors and selectors to implement operations on rational numbers: (add-rat x y) (sub-rat x y) (mul-rat x y) (div-rat x y) (equal-rat? x y) (print-rat x) A form of wishful thinking: we don’t know how make-ratnumer anddenom are implemented, but we use them. מבוא מורחב שיעור 7

7. Implementing the operations (define (add-rat x y);n1/d1 + n2/d2 = (n1.d2 + n2.d1) / (d1.d2) (make-rat (+ (* (numer x) (denom y)) (* (numer y) (denom x))) (* (denom x) (denom y)))) (define (sub-rat x y) … (define (mul-rat x y) (make-rat (* (numer x) (numer y)) (* (denom x) (denom y)))) (define (div-rat x y) (make-rat (* (numer x) (denom y)) (* (denom x) (numer y)))) (define (equal-rat? x y) (= (* (numer x) (denom y))(* (numer y) (denom x)))) מבוא מורחב שיעור 7

8. Using the rational package (define (print-rat x) (newline) (display (numer x)) (display ”/”) (display (denom x))) (define one-half (make-rat 1 2)) (print-rat one-half)  1/2 (define one-third (make-rat 1 3)) (print-rat (add-rat one-half one-third))  5/6 (print-rat (add-rat one-third one-third))  6/9 מבוא מורחב שיעור 7

9. Programs that use rational numbers add-rat sub-rat mul-rat… make-rat numer denom Abstraction barriers rational numbers in problem domain rational numbers as numerators and denumerators מבוא מורחב שיעור 7

10. Gluing things together We still have to implement numer, denom, and make-rat We need a way to glue things together… A pair: (define x (cons 1 2)) (car x)  1 (cdr x)  2 מבוא מורחב שיעור 7

11. Pair: A primitive data type. Constructor: (cons a b) Selectors: (car p) (cdr p) Guarantee:(car (cons a b)) = a (cdr (cons a b)) = b Abstraction barrier: We say nothing about the representation or implementation of pairs. מבוא מורחב שיעור 7

12. Pairs (define x (cons 1 2)) (define y (cons 3 4)) (define z (cons x y)) (car (car z))  1 ;(caar z) (car (cdr z))  3 ;(cadr z) מבוא מורחב שיעור 7

13. Implementing make-rat, numer, denom (define (make-rat n d) (cons n d)) (define (numer x) (car x)) (define (denom x) (cdr x)) מבוא מורחב שיעור 7

14. Programs that use rational numbers add-rat sub-rat mul-rat... make-rat numer denom cons car cdr Abstraction barriers rational numbers in problem domain rational numbers as numerators and denumerators rational numbers as pairs מבוא מורחב שיעור 7

15. Abstraction Violation Alternative implementation for add-rat (define (add-rat x y) (cons (+ (* (car x) (cdr y)) (* (car y) (cdr x))) (* (cdr x) (cdr y)))) If we bypass an abstraction barrier, changes to one level may affect many levels above it. Maintenance becomes more difficult. מבוא מורחב שיעור 7

16. Rationals - Alternative Implementation • In our current implementation we keep 10000/20000 • as such and not as 1/2. • This: • Makes the computation more expensive. • Prints out clumsy results. A solution: change the constructor (define (make-rat a b) (let ((g (gcd a b))) (cons (/ a g) (/ b g)))) No other changes are required! מבוא מורחב שיעור 7

17. Reducing to lowest terms, another way (define (make-rat n d) (cons n d)) (define (numer x) (let ((g (gcd (car x) (cdr x)))) (/ (car x) g))) (define (denom x) (let ((g (gcd (car x) (cdr x)))) (/ (cdr x) g))) מבוא מורחב שיעור 7

18. How can we implement pairs? (first solution) (define (cons x y) (lambda (f) (f x y))) (define (car z) (z (lambda (x y) x))) (define (cdr z) (z (lambda (x y) y))) מבוא מורחב שיעור 7

19. Name Value p (lambda(f) (f 1 2)) ( (lambda(f) (f 1 2)) (lambda (x y) x)) ( (lambda(x y) x) 1 2 ) > 1 How can we implement pairs? (first solution, cont’) > (define p (cons 1 2)) > (car p) (define (cons x y) (lambda (f) (f x y))) (define (car z) (z (lambda (x y) x))) (define (cdr z) (z (lambda (x y) y))) מבוא מורחב שיעור 7

20. How can we implement pairs?(Second solution: message passing) (define (cons x y) (lambda (m) (cond ((= m 0) x) ((= m 1) y) (else (error "Argument not 0 or 1 -- CONS" m)))))) (define (car z) (z 0)) (define (cdr z) (z 1)) מבוא מורחב שיעור 7

21. ((lambda(m) (cond ..)) 0) (cond ((= 0 0) 3) ((= 0 1) 4) (else ...))) > 3 Implementing pairs (second solution, cont’) Name Value > (define p (cons 3 4)) p (lambda(m) (cond ((= m 0) 3) ((= m 1) 4) (else ..))) > (car p) (define (cons x y) (lambda (m) (cond ((= m 0) x) ((= m 1) y) (else ...))) (define (car z) (z 0)) (define (cdr z) (z 1)) מבוא מורחב שיעור 7

22. Implementation of Pairs -The way it is really done • Scheme provides an implementation of pairs, so we do not need to use these “clever” implementations. • The natural implementation is by using storage. • The two solutions we presented show that the distinction between storage and computation is not always clear. • Sometimes we can trade data for computation. • The solutions we showed have their own significance: • The first is used to show that lambda calculus can simulate other models of computation (theoretical importance). • The second – message passing – is the basis for Object Oriented Programming. We will return to it later. מבוא מורחב שיעור 7

23. a 2 1 Box and Pointer Diagram • (define a (cons 1 2)) • A pair can be implemented directly using two “pointers”. • Originally on IBM 704: • (car a)Contents of Address part of Register • (cdr a)Contents of Decrement part of Register מבוא מורחב שיעור 7

24. 4 3 1 2 Box and pointer diagrams (cont.) • (cons (cons 1 (cons 2 3)) 4) מבוא מורחב שיעור 7

25. Pairs have the closure property: • We can pair pairs, pairs of pairs etc. • (cons (cons 1 2) 3) 3 2 1 Compound Data A closure property: The result obtained by creating a compound data structure can itself be treated as a primitive object and thus be input to the creation of another compound object. מבוא מורחב שיעור 7

26. 3 1 2 Lists The empty list (a.k.a. null or nill) • (cons 1 (cons 3 (cons 2 ’()))) • Syntactic sugar:(list 1 3 2) מבוא מורחב שיעור 7

27. Formal Definition of a List A list is either • ’() -- The empty list • A pair whose cdr is a list. Lists are closed under the operations consand cdr: • If lst is a non-empty list, then (cdr lst) is a list. • If lst is a list and x is arbitrary, then (cons x lst) is a list. מבוא מורחב שיעור 7

28. … <x1> <x2> <xn> Lists (list <x1> <x2> ... <xn>) is syntactic sugar for (cons <x1> (cons <x2> ( … (cons <xn> ’() )))) מבוא מורחב שיעור 7

29. 1 3 2 2 3 Lists (examples) The following expressions all result in the same structure: (cdr (list 1 2 3)) (cdr (cons 1 (cons 2 (cons 3 ’() )))) (cons 2 (cons 3 ’() )) (list 2 3) (cons 3 (list 1 2)) (cons 3 (cons 1 (cons 2 ’() ))) (list 3 1 2) and similarly the following מבוא מורחב שיעור 7

30. 1 4 3 2 4 3 1 2 4 3 1 2 More Elaborate Lists (list 1 2 3 4) (cons (list 1 2) (list 3 4)) (list (list 1 2) (list 3 4)) • Prints as (1 2 3 4) • Prints as ((1 2) 3 4) • Prints as ((1 2) (3 4)) מבוא מורחב שיעור 7

31. p1 3 p 1 2 p2 Yet More Examples • (define p (cons 1 2)) • p2 ( (1 . 2) (1 . 2) ) • p (1 . 2) • (define p1 (cons 3 p) • p1 (3 1 . 2) • (define p2 (list p p)) מבוא מורחב שיעור 7

32. The Predicate Null? null? : anytype -> boolean (null? <z>) #t if <z> evaluates to empty list #f otherwise (null? 2)  #f (null? (list 1))  #f (null? (cdr (list 1)))  #t (null? ’())  #t (null? null)  #t מבוא מורחב שיעור 7

33. The Predicate Pair? pair? : anytype -> boolean (pair? <z>) #tif <z> evaluates to a pair #f otherwise. (pair? (cons 1 2))  #t (pair? (cons 1 (cons 1 2)))  #t (pair? (list 1))  #t (pair? ’())  #f (pair? 3)  #f (pair? pair?)  #f מבוא מורחב שיעור 7

34. The Predicate Atom? atom? : anytype -> boolean (define (atom? z) (and (not (pair? z)) (not (null? z)))) (define (square x) (* x x)) (atom? square)  #t (atom? 3)  #t (atom? (cons 1 2))  #f מבוא מורחב שיעור 7

35. (define digits1 (cons 0 digits)) • digits1 • (define l (list 0 digits)) • l ? More examples • (define digits (list 1 2 3 4 5 6 7 8 9)) ? (0 1 2 3 4 5 6 7 8 9) (0 (1 2 3 4 5 6 7 8 9)) מבוא מורחב שיעור 7

36. The procedurelength • (define digits (list 1 2 3 4 5 6 7 8 9)) • (length digits) 9 • (define l null) • (length l) 0 • (define l (cons 1 l)) • (length l) 1 (define (length l) (if (null? l) 0 (+ 1 (length (cdr l))))) מבוא מורחב שיעור 7