CS 242 Announcements Lisp � Exam dates • Midterm: Wednesday Oct 27, 7-9 PM • Final: Wednesday Dec 8, 8:30-11:30 AM • Conflicts – send email to cs242@cs now! � Homework graders - email to cs242@cs John Mitchell � Submit homework from far away (SCPD) • Fax (650) 736-1266 by 5PM the day it is due • We will return graded HW by courier � Reading • Will add reading assignment to slides, hw My office hours: will set next week after a trip Reading: Chapter 3 Homework 1: due Oct 6 Lisp, 1960 John McCarthy � Look at Historical Lisp � Pioneer in AI • Perspective • Formalize common- – Some old ideas seem old sense reasoning – Some old ideas seem new � Also • Example of elegant, minimalist language • Proposed timesharing • Not C, C++, Java: a chance to think differently • Mathematical theory • Illustrate general themes in language design • …. � Supplementary reading (optional) • McCarthy, Recursive functions of symbolic � Lisp expressions and their computation by machine, stems from interest in Communications of the ACM, Vol 3, No 4, 1960. symbolic computation (math, logic) Lisp summary Atoms and Pairs � Many different dialects � Atoms include numbers, indivisible “strings” <atom> ::= <smbl> | <number> • Lisp 1.5, Maclisp, …, Scheme, ... <smbl> ::= <char> | <smbl><char> | <smbl><digit> • CommonLisp has many additional features <num> ::= <digit> | <num><digit> • This course: a fragment of Lisp 1.5, approximately � Dotted pairs But ignore static/dynamic scope until later in course • Write (A . B) for pair � Simple syntax • Symbolic expressions, called S-expressions : (+ 1 2 3) <sexp> ::= <atom> | (<sexp> . <sexp>) (+ (* 2 3) (* 4 5)) (f x y) Easy to parse (Looking ahead: programs as data) 1
Basic Functions Evaluation of Expressions � Functions on atoms and pairs: � Read-eval-print loop cons car cdr eq atom � Function call (function arg 1 ... arg n ) � Declarations and control: • evaluate each of the arguments • pass list of argument values to function cond lambda define eval quote � Special forms do not eval all arguments � Example • Example (cond (p 1 e 1 ) ... (p n e n ) ) (lambda (x) (cond ((atom x) x) (T (cons ‘A x)))) – proceed from left to right function f(x) = if atom(x) then x else cons(“A”,x) – find the first p i with value true, eval this e i � Functions with side-effects • Example (quote A) does not evaluate A rplaca rplacd set setq Examples McCarthy’s 1960 Paper (+ 4 5) � Interesting paper with expression with value 9 • Good language ideas, succinct presentation (+ (+ 1 2) (+ 4 5)) • Some feel for historical context • Insight into language design process evaluate 1+2, then 4+5, then 3+9 to get value � Important concepts (cons (quote A) (quote B)) • Interest in symbolic computation influenced design pair of atoms A and B • Use of simple machine model (quote (+ 1 2)) • Attention to theoretical considerations evaluates to list (+ 1 2) Recursive function theory, Lambda calculus '(+ 1 2) • Various good ideas: Programs as data, garbage collection same as (quote (+ 1 2)) Motivation for Lisp Execution Model (Abstract Machine) � Advice Taker � Language semantics must be defined • Process sentences as input, perform logical reasoning • Too concrete � Symbolic integration, differentiation – Programs not portable, tied to specific architecture • expression for function --> expression for integral – Prohibit optimization (e.g., C eval order undefined in expn) (integral ‘(lambda (x) (times 3 (square x)))) • Too abstract � Motivating application part of good lang design – Cannot easily estimate running time, space � Lisp: IBM 704, but only certain ideas … • Keep focus on most important goals • Eliminate appealing but inessential ideas • Address, decrement registers -> cells with two parts Lisp symbolic computation, logic, experimental prog. • Garbage collection provides abstract view of memory C Unix operating system Simula simulation PL/1 “kitchen sink”, not successful in long run 2
Abstract Machine Theoretical Considerations � Concept of abstract machine: � “ … scheme for representing the partial • Idealized computer, executes programs directly recursive functions of a certain class of symbolic • Capture programmer’s mental image of execution expressions.” • Not too concrete, not too abstract � Lisp uses � Examples • Concept of computable (partial recursive) functions • Fortran – Want to express all computable functions – Flat register machine; memory arranged as linear array • Function expressions – No stacks, no recursion. – known from lambda calculus (developed A. Church) • Algol family – lambda calculus equivalent to Turing Machines, but provide – Stack machine, contour model of scope, heap storage useful syntax and computation rules • Smalltalk – Objects, communicating by messages. Innovations in the Design of Lisp Parts of Speech � Expression-oriented � Statement load 4094 r1 • function expressions • Imperative command • conditional expressions • Alters the contents of previously-accessible memory • recursive functions � Expression (x+5)/2 � Abstract view of memory • Syntactic entity that is evaluated • Cells instead of array of numbered locations • Has a value, need not change accessible memory • Garbage collection • If it does, has a side effect � Programs as data � Declaration integer x � Higher-order functions • Introduces new identifier • May bind value to identifier, specify type, etc. Function Expressions Conditional Expressions in Lisp � Generalized if-then-else � Example: (cond (p 1 e 1 ) (p 2 e 2 ) … (p n e n ) ) (lambda ( parameters ) ( function_body ) ) – Evaluate conditions p 1 … p n left to right � Syntax comes from lambda calculus: – If p i is first condition true, then evaluate e i λ f. λ x. f (f x) – Value of e i is value of expression (lambda (f) (lambda (x) (f (f x)))) Undefined if no p i true, or Function expression defines a function but does not give a name to it p 1 … p i false and p i+1 undefined, or ( (lambda (f) (lambda (x) (f (f x)))) relevant p i true and e i undefined (lambda (y) (+ 2 y))) Conditional statements in assembler ) Conditional expressions apparently new in Lisp 3
Examples Strictness (cond ((<2 1) 2) ((<1 2) 1)) � An operator or expression form is strict if it can have a value only if all operands or has value 1 subexpressions have a value. (cond ((<2 1 ) 2) ((<3 2) 3)) � Lisp cond is not strict, but addition is strict is undefined • (cond (true 1) (diverge 0)) • (+ e 1 e 2 ) (cond (diverge 1) (true 0)) is undefined, where diverge is undefined (cond (true 0) (diverge 1)) has value 0 Lisp Memory Model Sharing (a) (b) � Cons cells Address Decrement � Atoms and lists represented by cells A B A B A B Atom A � Both structures could be printed as (A.B).(A.B) 0 � Which is result of evaluating Atom B (cons (cons ‘A ‘B) (cons ‘A ‘B)) ? Atom C Garbage Collection Examples � Garbage: (car (cons ( e 1 ) ( e 2 ) )) At a given point in the execution of a program P , a Cells created in evaluation of e 2 may be garbage, memory location m is garbage if no continued execution unless shared by e 1 or other parts of program of P from this point can access location m . � Garbage Collection: ((lambda (x) (car (cons (… x…) (... x ...))) • Detect garbage during program execution '(Big Mess)) • GC invoked when more memory is needed The car and cdr of this cons cell may point to • Decision made by run-time system, not program overlapping structures. This is can be very convenient. Example: in building text-formatting program, ~40% of programmer time on memory management . 4
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