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Functional Programming

Functional Programming

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Functional Programming

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  1. Functional Programming Element of Functional Programming

  2. Functional Programming • Functional Programming began as computing with expressions. • The following are examples: 2 An integer constant X A variable log n Function log applied to n 2+3 Function + applied to 2 and 3

  3. Functional Programming • Expressions can also include conditionals and function definitions. Example: The value of following condition expression is the maximum of x and y: if (x > y) then x else y

  4. Functional Programming • For concreteness, specific ML examples will be written in a typewriter-like font; • For example: • Computing with expressions will be introduced by designing a little language of expressions. 2 + 2; val it = 4 : int

  5. A LITTLE LANGUAGE OF EXPRESSIONS • Basic Values • Constants: Names for Basic Values • Operations • Expressions • Convenient Extensions • Local Declarations

  6. A LITTLE LANGUAGE OF EXPRESSIONS • Expressions are formed by giving names to values and to operations on them • The little language manipulates just one type of value: geometric objects called quilts.

  7. Example : Quilt What is Quilt?

  8. Little Quilt • Little Quilt manipulates geometric objects with • Height • Width • Texture

  9. Basic Values • Given two primitive objects in the language are the square pieces: • Each quilt has • A fixed direction or orientation • A height • A width • A texture

  10. turn turn turn turn sew Operations • Quilt can be turned and can be sewn together

  11. Rules Quilts and the operations on them are specified by the following rules: • A quilt is one of the primitive pieces, or • It is formed by turning a guilt clockwise 90, or • It is formed by sewing a quilt to the right of another quilt of equal height • Nothing else is a quilt

  12. Constants: Names for Basic Values • The first step in construction a language to specify quilts is to give names to the primitive pieces and to the operations on quilts • Operation called • turn • sew Name “a” Name “b”

  13. Expressions • The syntax of expressions mirrors the definition of quilts: • Complex expressions are built up from simpler ones, <exp> ::= a | b | turn(<exp>) | sew(<exp>,<exp>)

  14. Expressions Sew(turn(turn(b)),a) No expression quilt 1 b 2 turn(b) 3 turn(turn(b)) 4 a 5 sew(turn(turn(b)),a)

  15. Convenient Extensions • Expressions will now be extended by allowing functions from quilts to quilts. • It would be convenient to give names to the operations. • Once defined, functions like unturn and pile can used as if they were built in Fun unturn(x) = turn(turn(turn(x))) Fun pile(x,y) = unturn(sew(turn(y),turn(x)))

  16. Local Declarations • Let-expressions or let-bindings allow declarations to appear within expressions. • Let-expression Form Let <declaration> in <expression> end For example let fun unturn(x) = turn(turn(turn(x))) fun pile(x,y) = unturn(sew(turn(y),turn(x))) in pile(unturn(b),turn(b)) end

  17. User-Defined Names for Values • The final extension is convenient for writing large expressions in terms of simpler ones. • A value declaration form: • Gives a name to a value val <name> = <expression>

  18. Value declarations are used together with let-bindings. • An expression of the form let val x=E1 in E2 end Rewrite Pile(unturn(b),turn(b)) let val bnw = unturn(b) in pile(bnw,turn(b)) end

  19. Review: Design of Little Quilt • The language Little Quilt was defined by starting with values and operations. • The values are quilts, built up from two square pieces; • The operations are for turning and sewing quilts. • The language began with the name a and b for the square pieces and • The names turn and sew for the operations

  20. Specification of a quilt Let fun unturn(x) = turn(turn(turn(x))) fun pile(x,y) = unturn(sew(turn(y),turn(x))) val aa = pile(a,turn(turn(a))) val bb = pile(unturn(b),turn(b)) val p = sew(bb,aa) val q = sew(aa,bb) In pile(p,q) end

  21. Summary of Little Quilt <exp> ::= a | b <exp> ::= turn(<exp>) | sew(<exp>,<exp>) <exp> ::= let <declarations> in <exp> end <decs> ::= <dec> | <dec> <decs> <dec> ::= fun <name> (<formals>) = <exp> <formals> ::= <name> | <name>, <formals> <exp> ::= <name> (<actuals>) <actuals> ::= <exp> | <exp>, <actuals> <dec> ::= val <name> = <exp> <exp> ::= <name>

  22. TYPEs:Values and Operations • A types consists of a set of elements called values together with a set of functions called operations. • We will consider methods for defining structured values such as products, lists, and functions.

  23. The syntax of type expressions <type-exp> ::= <type-name> | <type-exp>  <type-exp> | <type-exp> *<type-exp> | <type-exp> list

  24. Structured value • Structured values such as lists can be used as freely in functional languages as basic values like integers and strings • Value in a function language take advantage of the underlying machine, but are not tied to it.

  25. Operations for Constructing and Inspecting Values • The structuring methods will be presented by specifying a set of values together with a set of operations. • Concentrate on operations for constructing and inspecting the elements of the set. • For example • To Extend a list by adding a new first element • To test whether a list is empty

  26. Operations for Constructing and Inspecting Values • Basic Types • Operations on Basic Values • Products of Types • Operations on Pairs • List of Elements • Operations on Lists

  27. Basic Types • A type is basic if its values are atomic • If the values are treated as whole elements, with no internal structure. For example The boolean values in the set {true,false}

  28. Operations on Basic Values • Basic values have no internal structure, so the only operation defined for all basic types is a comparison for equality; For example The equality 2 = 2 is true, The inequality 2!=2 is false

  29. Operations on Basic Values • Technically, an operation is a function • The equality test on integers is a function from pairs of integers to boolean. The type int*int  bool

  30. Products of Types • The product A*B of two types A and B consists of ordered pairs written as For Example (1,“one”) is a pair consisting of int:1 and string: “one” (a,b) ; where a is a value of type A and b is a value of type B

  31. Products of Types • A product of n types A*A*A*…*A consists of tuples written as (a1, a2 , a3 ,…, an ) ; where ai is a value of type A1

  32. Operations on Pairs • A pair is constructed from a and b by writing (a,b) • Associated with pairs are operations called projection functions to extract the first and second elements from a pair. • The first element of the pair (a,b) is a • The second element is b • Projection functions can be readily defined: funfirst(x,y) = x funsecond(x,y) = y

  33. Lists of Elements • A list is a finite-length sequence of elements. For Example int list ; consists of all lists of integers. The type A list consists of all lists of elements, where each element belongs to type A

  34. Lists of Elements • List elements will be written between brackets [ and ] • List elements will be separated by commas • The empty list is written equivalently as [ ] For Example [1, 2, 3] is a list of three integers [“red”, “white”, “blue”] is a list of three strings

  35. Operations on Lists • Lists-manipulation programs must be prepared to construct and inspect lists of any length. • The following operations on list are from ML: null(x) True is x is the empty list hd(x) The first or head element of list x. tl(x) The tail or rest of the list. a::x Construct a list with head a and tail x

  36. Operations on Lists For Example Given x is [1, 2, 3] Null(x) false Hd(x) 1 Tl(x) [2, 3] From the following equalities: [1, 2, 3] = 1::[2, 3] = 1::2::[3] = 1::2::3::[]

  37. Functions from a Domain to a Range • The type A  B is the set of all functions from A to B For Example If Q is the set of quilt then function turn from quilts to quilts is Q  Q function sew form pairs of quits to quilts is Q*Q  Q

  38. Functions from a Domain to a Range • A function f in A B is total • A function f in A B is partial If it associates an element of B with each element of A A is called the domain and B is called the range of f. It is possible for there to be no element of B associated with an element of A

  39. Function Application • The set A  B is application which takes a function f in A B and an element a in A and yields and element b of B. For Example • A function is applied in ML; f a is the application of f to a.

  40. APPOACHES TO EXPRESSION EVALUATION • The rules for expression are base on the structure of expressions E1 + E2 • Evaluate the subexpressions E1 and • Evaluate the subexpressions E2 and • Add two values

  41. Innermost Evaluation <name> <actual-parameter> • Evaluate the expression represented by <actual-parameter> • Substitute the result for the formal in the function body • Evaluate the body • Return its value as the answer

  42. Selection Evaluate If <condition> then <expression1> else <expression2> • <condition> is an expression that evaluates to either true or false. • True : <expression1> is evaluated • False : <expression2> is evaluated

  43. Evaluation of Recursive Functions • The actual parameters are evaluated and substituted into the function body. Length(X) ((cond (null X) 0 (+ 1 (length(cdrX))))) Length([“hello”, “world”]) = 1 + length([“world”]) = 1 + 1 + length([]) = 1 + 1 + 0 = 2

  44. Othermost Evaluation • Substitute the actual for the formal in the function body • Evaluate the body • Return its value as the answer.

  45. Example Function Fun f(x) = if x > 100 then x-10 else f(f(x+11))

  46. Innermost Evaluate F(100) = if 100>100 then 100-10 else f(f(100+11)) = f(f(100+11)) = f(f(111)) = f( if 111> 100 then 111-10 else f(f(111+11)) ) = f(111-10) = f(101) = if 101>100 then 101-10 else f(f(101+11)) = 101 – 10 = 91

  47. Outermost Evaluate F(100) = if 100>100 then 100-10 else f(f(100+11)) = f(f(100+11)) = if f(111> 100) then f(111+11)-10 else f(f(f(100+11)+11)) ) F(100+11) = if 100+11> 100 then 100+11-10 else f(f(100+11+11)) = if 111>100 then 100+11-10 else f(f(100+11+11)) = 100+11-10 = 111-10 = 101

  48. LEXICAL SCOPE • Renaming is made precide by introducing a notion of local or “bound” variables;bound occurrences of variables can be renamed without changing the meaning of a program fun successor(x) = x + 1 fun successor(n) = n + 1

  49. Val Bindings let val x=E1 in E2 end • Binding occurrence or simply binding of x • All occurrences of x in E2 are said to be within the scope of this binding • Occurrences of x in E1 are not in the scope of this binding of x let val x=2 in x+x end

  50. Fun Bindings let fun f(x)=E1 in E2 end • This binding of the formal parameter x is visible only to the occurrences of x in E1 • This binding of the function name f is visible to all occurrences of f in both E1 and E2 let fun f(x)=x+1 in 2*f(x) end