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Principles of Programming Languages Lecture 1 Slides by Yaron Gonen, based on slides by Daniel Deutch and lecture notes by Prof. Mira Balaban.

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Presentation on theme: "Principles of Programming Languages Lecture 1 Slides by Yaron Gonen, based on slides by Daniel Deutch and lecture notes by Prof. Mira Balaban."— Presentation transcript:

1 Principles of Programming Languages Lecture 1 Slides by Yaron Gonen, based on slides by Daniel Deutch and lecture notes by Prof. Mira Balaban

2 4 ٤ IV100

3 4 + 5 4 + “hello” +

4 So What have We Seen? Syntax Semantics Values Types

5 Introduction We will study Computational Processes Design Principles – Modularity, abstraction, contracts… Programming Languages Paradigms – Functional Programming E.g. Racket, Scheme, Python, JavaScript (partially), Java (Since Java 8) Functions are first-class objects – Logic Programming E.g. Prolog “Declarative Programming” – Imperative Programming E.g. C, Java Focuses on change of state – Not always a crisp distinction – for instance Scheme can be used for imperative programming.

6 More topics Types – Type Inference and Type Checking – Static and Dynamic Typing Different Semantics (e.g. Operational) Interpreters vs. Compilers – Lazy and applicative evaluation

7 Languages that will be studied Racket (dialect of Scheme) – Dynamically Typed – Functions are first-class citizens – Simple (though LOTS of parenthesis ) – Allows to show different programming styles Prolog – Declarative, Logic programming language Languages are important, but we will focus on the principles

8 Administrative Issues Websites prefix http://www.cs.bgu.ac.il/http://www.cs.bgu.ac.il/ – Course: /~ppl162 – My personal site (for presentations): /~yarongon Exercises: 6 Mid-term Exam Grade

9 Use of Slides Slides are teaching-aids, i.e. by nature incomplete Will be on my personal site Compulsory material: – Lecture notes (see course website) – Everything taught in class and practical sessions – Compulsory reading if mentioned

10 “Wax on, wax off”

11 Functional Programming What is a non-functional (imperative) programming? – Imperative computation is a sequence of states (remember automata?) – Statements or side effects can modify the state (e.g. changing value of variable, display output)

12 Functional Programming Expressions (no statements) No State (no mutable data) No side-effects (see next slide) Has variables, but denote values (no location) We learn as we go This is not a course in functional programming!!

13 Side Effects “an expression is said to have a side effect if it modifies some state or has an observable interaction with calling functions or the outside world” (Wikipedia) “affect some external state of the computation environment” (lecture notes)

14 Why Functional Programming? Small paradigm (but powerful) Excellent for learning PPL Is making a comeback in recent years (Java 8, Python, JS, NodeJS, MapReduce…) There’s FUN in Functional Programming…

15 The Power of Abstraction

16 16 Racket (Scheme) LISP = LISt Processing – Invented in 1959 by John McCarthy – Scheme is a dialect of LISP – invented by Gerry Sussman and Guy Steele – Racket is a dialect of Scheme – Technical stuff in PS and in course website (how to install etc.)

17 Why Scheme? 5 minutes to learn (but a semester to master) One of the most influential languages! (Google “Programming languages influence network”)

18 Scheme Expressions The building block of every Scheme program Each has: – Syntax – Type – Value (evaluation rules, semantics)

19 Scheme Expressions Atomic – Cannot be decomposed. – Example: 34, #f, + – Can be primitive or non-primitive (next slide) Composite – Composed of other expressions (atomic or composite) – Starts with ‘ ( ‘, ends with ‘ ) ’ – Leftmost expression is an operator. – Can be special-form or not – Example: (+ 4 3), (* (+ 4 5) 6)

20 Expressions 6 + (+ 6 5) (+ (+ 1 1) 8) (foo 1 2) (define x 5) ((lambda (x) x) +)

21 More on Atomic Expressions Primitive – Evaluation process and value are built in – Example: numbers, Booleans, primitive procedures: +, -, *… Non-primitive – All the rest…

22 Abstraction and Reference וַיִּקְרָא הָאָדָם שֵׁמוֹת, לְכָל-הַבְּהֵמָה וּלְעוֹף הַשָּׁמַיִם, וּלְכֹל, חַיַּת הַשָּׂדֶה (בראשית ב' 20) Binding – Binding a name to a value (like naming a value) – In Scheme: (define size 6) – And now we can use this name: (* size 1.5) – size is atomic but non-primitive Where do we keep those bindings? – The global environment (next slide)

23 The Global Environment In short: GE A place to keep bindings Kind like a function from names (variables) to values Name-value pair is called binding

24 Evaluating Expressions Atomic Primitive: – Numbers – Booleans – Procedures Variables (non primitive) – Look in the GE Composite Special forms: – Each has its own rules. E.g. define : evaluate only the expression Non-special forms: – Evaluate all sub-expressions – Apply the operator

25 25 Computing in Scheme > 23 23 > (+ 3 17 5) 25 > (+ 3 (* 5 6) 8 2) 43 > (define score 23) Name Value GE 23score Opening parenthesis Expression whose value is a procedure Other expressions Closing parenthesis

26 26 Computing in Scheme > score 23 > (define total 25) > (* 100 (/ score total)) 92 > (define percentage (* 100 (/ score total)) Name Value Environment 23score 25total 92percentage

27 27 Using Evaluation Rules > (define score 23) > (* (+ 5 6 ) (- score (* 2 3 2 ))) Special Form (second sub- expression is not evaluated) *+56 11 -23*322 12 11 121

28 28 User Defined Procedures (compound procedures) How does one describe procedures? (lambda (x) (* x x)) To process something multiply it by itself formal parametersbody Internal representation Special form – creates a “procedure object” (also called closure) and returns it as a “value” Proc (x) (* x x)

29 29 More on lambdas The use of the word “lambda” is taken from lambda calculus. A lambda body can consist of a sequence of expressions The value returned is the value of the last one So why have multiple expressions at all? (next slide)

30 Lambdas with Multiple Expressions Side effects! Most useful for debugging > ((lambda (x) (display x) (* x x)) 3) 39 display is a primitive procedure.

31 31 Syntactic Sugar for naming procedures (define square (lambda (x) (* x x)) (define (square x) (* x x)) Instead of writing: We can write:

32 32 Evaluation of An Expression To Apply a compound procedure: (to a list of arguments) Evaluate the body of the procedure with the formal parameters replaced by the corresponding actual values ==> ((lambda(x)(* x x)) 5) Proc(x)(* x x) 5 (* 5 5) 25

33 33 Using Abstractions > (square 3) 9 > (+ (square 3) (square 4)) > (define square (lambda(x)(* x x))) (* 3 3) (* 4 4) 916+ 25 GE NameValue squareProc (x)(* x x)

34 34 Yet More Abstractions > (define f (lambda(a) (sum-of-two-squares (+ a 3) (* a 3)))) > (sum-of-two-squares 3 4) 25 > (define sum-of-two-squares (lambda(x y)(+ (square x) (square y)))) Try it out…compute (f 3) on your own

35 35 Booleans Two distinguished values denoted by the constants #t and #f The type of these values is boolean > (< 2 3) #t > (< 4 3) #f

36 36 Values and Types Values have types. For example: In scheme every expression has a value Examples: 1)The value of 23 is 23 2)The value of + is a primitive procedure for addition 3)The value of (lambda (x) (* x x)) is the compound procedure proc(x) (* x x) (also denoted 1)The type of 23 is numeral 2)The type of + is a primitive procedure 3)The type of proc (x) (* x x) is a compound procedure 4)The type of (> x 1) is a boolean (or logical)

37 Atomic and Compound Types Atomic types – Numbers, Booleans, Symbols (TBD) Composite types – Types composed of other types – So far: only procedures – We will see others later

38 Type Predicates We’ll discuss types in depth later, but in the meanwhile we have some predicates to help us: – number? – boolean? – procedure?

39 39 Void Example : what is the value of the expression (define x 8) And of (display x) In scheme, the value of a define, display expression is “void” of type Void. Never write code that relies on such value!

40 Dynamic Typing Note that we never specify explicitly types of variables However primitive functions expect values of a certain type! – E.g. “+” expects numeral values So will our procedures (To be discussed soon) The Scheme interpreter checks type correctness at run-time: dynamic typing – [As opposed to static typing verified by a compiler ]

41 (if ( 2 (if ( 41 The IF special form ERROR 2 (if ) If the value of is #t, Evaluate and return it Otherwise Evaluate and return it

42 42 IF is a special form In a general form, we first evaluate all arguments and then apply the function (if ) is different: determines whether we evaluate or. We evaluate only one of them !

43 Condition (lambda (a b) (cond ( (> a b) a) ( (< a b) b) (else -1 )))

44 cond is a Special Form (cond (... )... (else... ))

45 Example: sqrt

46 sqrt (define sqrt (lambda (x) (sqrt-iter 1 x))) (define sqrt-iter (lambda (guess x) (if (good-enough? guess x) guess (sqrt-iter (improve guess x) x)))) (define improve (lambda (guess x) (average guess (/ x guess)))) (define average (lambda (x y) (/ (+ x y) 2.0))) (define good-enough? (lambda (guess x) (< (abs (- (square guess) x)) 0.001))) (define square (lambda (n) (* n n)))

47 Expressions: Summary Atomic Primitives – Numbers – Booleans – Procedures Non-primitives – Variables – Special operators symbols Composite Specials forms – define, lambda, if, cond Forms

48 Evaluation: Summary Atomic Number Boolean Built-in Primitive Variable Composite Primitive operator Operator is a procedure (value of lambda) Special form (define, if, lambda, cond)

49 More on Types A procedure type is a composite type, as it is composed of the types of its inputs (domain) and output (range) In fact, the procedure type can be instantiated with any type for domain and range, resulting in a different type for the procedure (=data) Such types are called polymorphic – Another polymorphic type: arrays of values of type X (e.g. STL vectors in C++)

50 Type constructor Defines a composite type out of other types The type constructor for functions is denoted “->” Example: [Number * Number –> Number] is the type of all procedures that get as input two numbers, and return a number Note: there is nothing in the syntax for defining types! This is a convention we manually enforce (for now..).

51 Scheme Type Grammar Type -> ’Void’ | Non-void Non-Void -> Atomic | Composite | Type-variable Atomic -> ’Number’ | ’Boolean’ | ’Symbol’ Composite -> Procedure | Tuple Procedure -> ’[’ Tuple ’->’ Type ’]’ | ’[’ ’Empty’ ’->’ Type ’]’ Tuple -> (Non-void ’*’ )* Non-void Type-variable -> A symbol starting with an upper case letter

52 Value constructor Means of defining an instance of a particular type. The value constructors for procedures is lambda – Each lambda expression generates a new procedure


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