'Function application' diaporamas de présentation

An Introduction to LISP

An Introduction to LISP. Introduction LISP: A Brief Overview Expressions, the Syntactic Basis of LISP Control of LISP Evaluation: quote and eval Programming in LISP: Creating New Functions Program Control in LISP: Conditionals and Predicates Functions, Lists, and Symbolic Computing

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Computing Fundamentals 1 Lecture 8 Functions

Computing Fundamentals 1 Lecture 8 Functions. Lecturer: Patrick Browne http://www.comp.dit.ie/pbrowne/ Room K308 Based on Chapter 14. A Logical approach to Discrete Math By David Gries and Fred B. Schneider.

1.28k views • 108 slides

Formal Semantics

Formal Semantics. Slides by Julia Hockenmaier , Laura McGarrity , Bill McCartney, Chris Manning, and Dan Klein. Formal Semantics. It comes in two flavors: Lexical Semantics : The meaning of words

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Functional Programming

642 views • 48 slides

Lambda Calculus

Lambda Calculus. History and Syntax. History. The lambda calculus is a formal system designed to investigate function definition, function application and recursion. It was introduced by Alonzo Church and Stephen Cole Kleene in the 1930s

783 views • 47 slides

Multilisp: Concurrent Functional Programming

Ed Walters and Tim Richards University of Massachusetts Amherst. Multilisp: Concurrent Functional Programming. Overview. What is Multilisp? Overview of Scheme Features of Multilisp Where is Multilisp Now?. Overview. What is Multilisp? Overview of Scheme Features of Multilisp

342 views • 34 slides

Introduction to Scheme

Introduction to Scheme. Language Syntax(BNF) Semantics Pragmatics Data Control Abstract Data Types Denotational Axiomatic Operational

381 views • 30 slides

Security in Process Calculi

CS 259. Security in Process Calculi. Vitaly Shmatikov. Overview. Pi calculus Core language for parallel programming Modeling security via name scoping Applied pi calculus Modeling cryptographic primitives with functions and equational theories Equivalence-based notions of security

461 views • 30 slides

Parameterized Unit Tests

Parameterized Unit Tests. By Nikolai Tillmann and Wolfram Schulte Proc. of ESEC/FSE 2005 Presented by Yunho Kim Provable Software Lab, KAIST. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A A A. Introduction Parameterized unit tests

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CSE 130 : Spring 2011 Programming Languages

389 views • 27 slides

Security Definition

Security Definition. Unconditional Security The system cannot be defeated, no matter how much power is available by the adversary. Computational security

1.03k views • 26 slides

Recap

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Haskell

Haskell. Chapter 7. Topics. Defining data types Exporting types Type parameters Derived instances Type synonyms Either Type classes. Not covered record syntax recursive data structures subclassing parameterized types as instances of type classes

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Discrete Structures Lecture 2 Textual Substitution and Equality Read: Ch 1.1 - 1.4 (This lecture)

Discrete Structures Lecture 2 Textual Substitution and Equality Read: Ch 1.1 - 1.4 (This lecture) Ch 1.5 - 1.6 (Next lecture). What is an expression?. A constant (e.g. 41 ) is an expression. A variable (e.g. x ) is an expression. If E is an expression, then ( E ) is an expression.

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Every Bit Counts

346 views • 21 slides

A global environment

A global environment. val a = 15 val b = "foo"; val c = fn (n, p) => p = n * p; val d = [1,2];. Let and local environments. let val a = 20 in hd(d) + a end;. Function expressions generate closures. fun f(x, y) = let fun nested(z) = a + x + z in nested(y) end;.

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Introduction to RPAL

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Notes Over 2.2

Notes Over 2.2 1 3 5 8 7 Identifying Functions - Numerically Decide whether the relation is a function. 1. Input Output A function , because every input goes to only one output Not a function , because 4 goes to both 3 and 5

347 views • 11 slides

Notes Over 2.2

Notes Over 2.2. 1 3 5 8 7. Identifying Functions - Numerically. Decide whether the relation is a function. 1. Input Output. A function , because every input goes to only one output.

183 views • 11 slides

Fundamentals of Functional Programming Languages

Fundamentals of Functional Programming Languages. The objective of the design of a FPL is to mimic mathematical functions to the greatest extent possible The basic process of computation is fundamentally different in a FPL than in an imperative language

66 views • 5 slides