Practical Programming in Scheme

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Useful Programming. Online course reading: useful dialect is LISPLISt ProcessingThe rundown is the principal information structureDeveloped by John McCarthy in the 60\'sUsed for typical information processingExample applications: typical counts in necessary and differential analytics, circuit plan, rationale, diversion playing, AIAs we will see the sentence structure for the dialect is to a great degree simp

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Utilitarian Programming in Scheme CS331 Chapter 10

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Functional Programming Online course reading: useful dialect is LISP LISt Processing The rundown is the central information structure Developed by John McCarthy in the 60's Used for typical information preparing Example applications: typical figurings in fundamental and differential analytics, circuit plan, rationale, diversion playing, AI As we will see the sentence structure for the dialect is amazingly basic Scheme Descendant of LISP

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Functional Languages "Immaculate" useful dialect Computation saw as a scientific capacity mapping contributions to yields No thought of state, so no requirement for task articulations (reactions) Iteration achieved through recursion In reasonableness LISP, Scheme, other useful dialects additionally bolster cycle, task, and so forth. We will cover some of these "tainted" components yet accentuate the useful segment Equivalence Functional dialects equal to basic Core subset of C can be executed decently clearly in Scheme itself actualized in C Church-Turing Thesis

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Lambda Calculus Foundation of practical programming Developed by Alonzo Church, 1941 A lambda expression characterizes Function parameters Body Does NOT characterize a name; lambda is the anonymous capacity. Underneath x characterizes a parameter for the anonymous capacity:

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Lambda Calculus Given a lambda expression Application of lambda expression Identity Constant 2:

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Lambda Calculus Any identifier is a lambda expression If M and N are lambda expressions, then the utilization of M to N , (MN) is a lambda expression A deliberation, composed where x is an identifier and M is a lambda expression, is additionally a lambda expression

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Lambda Calculus Examples

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Lambda Calculus First Class Citizens Functions are top of the line natives Can be returned as an esteem Can be passed as a contention Can be put into an information structure as an esteem Can be the estimation of an expression (( λ x·( λ y·x+y)) 2 1) = (( λ y·2+y) 1) = 3

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Lambda Calculus Functional writing computer programs is basically a connected lambda math with inherent -steady values -capacities E.g. in Scheme, we have (* x) for x*x rather than λ x·x*x

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Functional Languages Two approaches to assess expressions Eager Evaluation or Call by Value Evaluate all expressions early Irrespective of in the event that it is required or not May bring about some runtime blunders Example (foo 1 (/1 x)) Problem; partition by 0

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Lambda Calculus Lazy Evaluation Evaluate all expressions just if necessary (foo 1 (/1 x)) ; (/1 x) not required, so never eval'd Some assessments might be copied Equivalent to call-by-name Allows a few sorts of calculations impractical in energetic assessment Example Infinite records E.g,. Unbounded stream of 1's, whole numbers, even numbers, and so on. Replaces tail recursion with sluggish assessment call Possible in Scheme utilizing (constrain/delay)

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Running Scheme for Class An adaptation of Scheme called Racket (in the past PLT/Dr Scheme) is accessible on the Windows machines in the CS Lab Download:, Mac forms likewise accessible if coveted

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Racket You can sort code specifically into the mediator and Scheme will come back with the outcomes:

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Make beyond any doubt right Language is chosen I jump at the chance to utilize the "Entirely Big" dialect decision

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Racket – Loading Code You can open code spared in a document. Racket utilizes the expansion ".rkt" so consider the accompanying document "factorial.rkt" made with a word processor or spared from Racket: 2: Run 1: Open (characterize factorial (lambda (n) (cond ((= n 1) 1) (else (* n (factorial (- n 1)))) ) 3: Invoke capacities

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Functional Programming Overview Pure utilitarian programming No certain thought of express No requirement for task proclamation No reaction Looping No state variable Use Recursion Most useful programming dialects have symptoms, including Scheme Assignments Input/Output

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Scheme Programming Overview Refreshingly basic Syntax is found out in around 10 seconds Surprisingly intense Recursion Functions as five star items (can be estimation of an expression, go as a contention, put in an information structure) Implicit stockpiling administration (refuse gathering) Lexical perusing Earlier LISPs did not do that (alterable) Interpreter Compiled variants accessible as well

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Expressions Syntax - Cambridge Prefix Parenthesized (* 3 4) (* (+ 2 3) 5) (f 3 4) when all is said in done: (functionName arg1 arg2 … ) Everything is an expression Sometimes called s-expr (typical expr)

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Expression Evaluation Replace images with their ties Constants assess to themselves 2, 44, #f No nil in Racket; utilize '() Nil = exhaust list, yet Racket has discharge Lists are assessed as capacity calls written in Cambridge Prefix documentation (+ 2 3) (* (+ 2 3) 5)

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Scheme Basics Atom Anything that can't be deteriorated encourage a series of characters starting with a letter, number or uncommon character other than ( or ) e.g. 2, #t, #f, "hi", foo, bar #t = genuine #f = false List A rundown of iotas or expressions encased in () (), empty,(1 2 3), (x (2 3)), (()()())

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Scheme Basics S-expressions Atom or rundown () or exhaust Both molecule and a rundown Length of a rundown Number at the top level

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Quote If we need to speak to the exacting rundown (a b c) Scheme will translate this as apply the contentions b and c to work a To speak to the strict rundown utilize "cite" (cite x)  x (cite (a b c))  (a b c) Shorthand: single quote 'a == (cite an) '(a b c) == (cite (a b c))

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Global Definitions Use characterize work (characterize f 20) (characterize levels '(0 2 4 6 8)) (characterize chances '(1 3 5 7 9)) (characterize shading 'red) (characterize shading blue) ; Error, blue vague (characterize num f) ; num = 20 (characterize num 'f) ; image f (characterize s "hi world") ; String

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Lambda capacities Anonymous capacities (lambda (<formals>) <expression>) (lambda (x) (* x)) ((lambda (x) (* x)) 5)  25 Motivation Can make works as required Temporary capacities : don't need to have names Can not utilize recursion

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Named Functions Use characterize to tie a name to a lambda expression (characterize square (lambda (x) (* x))) (square 5) Using lambda all the time gets dull; substitute language structure: (characterize (<function name> <formals>) <expression1> <expression2> … ) Last expression assessed is the one returned (characterize (square x) (* x)) (square 5)  25

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Conditionals (if <predicate> <expression1> <expresion2>) -Return esteem is either expr1 or expr2 (cond (P1 E1) (P2 E2) (P n E n ) (else E n+1 )) -Returns whichever expression is assessed

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Common Predicates Names of predicates end with ? Number? : checks if the contention is a number Symbol? : checks if the contention is an image Equal? : checks if the contentions are fundamentally equivalent Null? : checks if the contention is vacant Atom? : checks if the contention is an iota Appears vague in Racket yet can characterize ourselves List? : checks if the contention is a rundown

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Conditional Examples (if (break even with? 1 2) 'x 'y) ; y (if (rise to? 2) 'x 'y) ; x (if (invalid? '()) 1 2) ; 1 (cond ((equal? 1 2) 1) ((equal? 2 3) 2) (else 3)) ; 3 (cond ((number? 'x) 1) ((null? 'x) 2) ((list? '(a b c)) (+ 2 3)) ; 5 )

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Dissecting a List Car : gives back the principal contention (auto '(2 3 4)) (auto '((2) 4)) Defined just for non-invalid records Cdr : (articulated "could-er") gives back whatever is left of the rundown Racket: list must have no less than one component Always gives back a rundown (cdr '(2 3 4)) (cdr '(3)) (cdr '(((3)))) Compose (auto (cdr '(4 5))) (cdr (auto '((3 4))))

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Shorthand (cadr x) = (auto (cdr x)) (cdar x) = (cdr (auto x)) (caar x) = (auto x)) (cddr x) = (cdr x)) (cadar x) = (auto (cdr (auto x))) … and so on… up to 4 levels somewhere down in Racket (cddadr x) = ?

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Why Car and Cdr? Extra documentation from unique execution of Lisp on an IBM 704 CAR = Contents of Address some portion of Register Pointed to the principal thing in the present rundown CDR = Contents of Decrement some portion of Register Pointed to whatever remains of the rundown

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Building a rundown Cons Cons(truct) another rundown from first and rest Takes two contentions Second ought to be a rundown If it is not, the outcome is a "specked combine" which is commonly viewed as a contorted rundown First might possibly be a rundown Result is dependably a rundown

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Building a rundown X = 2 and Y = (3 4 5) : (cons x y)  (2 3 4 5) X = () and Y =(a b c) : (cons x y)  (() a b c) X = an and Y =() : (cons x y )  (a) What is (cons 'a (cons 'b (cons 'c '()))) (cons 'a (cons 'b '())) (cons 'c '()))

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Numbers Regular number-crunching administrators are accessible +, - , *,/May take variable contentions (+ 2 3 4), (* 4 5 9 11) (/9 2)  4.5 ; (remainder 9 2)  4 Regular examination administrators are accessible < > <= >= = E.g. (= 5 (+ 3 2))  #t = just takes a shot at numbers, generally utilize square with?

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Example Sum all numbers in a rundown (characterize (sumall list) (cond ((invalid? list) 0) (else (+ (auto list) (sumall (cdr list)))))) Sample summon: (sumall '(3 45 1))

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Example Make a rundown of n indistinguishable qualities (characterize (makelist n esteem) (cond ((= n 0) '()) (else (cons esteem (makelist (- n 1) esteem)) ) In longer projects, cautious coordinating enclosure.

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Example Determining if a thing is an individual from a rundown (characterize (part? thing list) (cond ((invalid? list) #f)