CS 251 Part 1: How to Program Defining Racket

Total Page:16

File Type:pdf, Size:1020Kb

CS 251 Part 1: How to Program Defining Racket CS 251 Fall 20192019 CS 251 Fall 20192019 Principles of of Programming Programming Languages Languages Principles of of Programming Programming Languages Languages λ Ben Wood λ Ben Wood CS 251 Part 1: Defining Racket: How to Program Expressions and Bindings via the meta-language of PL definitions https://cs.wellesley.edu/~cs251/f19/Expressions, Bindings, Meta-language 0 https://cs.wellesley.edu/~cs251/f19/Expressions, Bindings, Meta-language 1 Topics / Goals From AI to language-oriented programming LISP: List Processing language, 1950s-60s, MIT AI Lab. 1. Basic language forms and evaluation model. Advice Taker: represent logic as data, not just as a program. Metaprogramming and programs as data: 2. Foundations of defining syntax and semantics. • Symbolic computation (not just number crunching) – Informal descriptions (English) • Programs that manipulate logic (and run it too) Scheme: child of Lisp, 1970s, MIT AI Lab. – Formal descriptions (meta-language): Still motivated by AI applications, became more "functional" than Lisp. • Grammars for syntax. Important design changes/additions/cleanup: • simpler naming and function treatment • Judgments, inference rules, and derivations • lexical scope for big-step operational semantics. • first-class continuations • tail-call optimization, … 3. Learn Racket. (an opinionated subset) Racket: child of Scheme, 1990s-2010s, PLT group. – Not always idiomatic or the full story. Setup for transition to Standard ML. Revisions to Scheme for: • Rapid implementation of new languages. • Education. Became Racket in 2010. Expressions, Bindings, Meta-language 2 Expressions, Bindings, Meta-language 3 Defining Racket PL design/implementation: layers To define each new language feature: – Define its syntax. How is it written? – Define its dynamic semantics as evaluation rules. kernel How is it evaluated? primitive values, Features data types 1. Expressions syntactic sugar • A few today, more to come. 2. Bindings standard libraries 3. That's all! • A couple more advanced features later. user libraries Expressions, Bindings, Meta-language 4 Expressions, Bindings, Meta-language 5 Values Addition expression Expressions that cannot be evaluated further. Syntax: (+ e1 e2) – Parentheses required: no extras, no omissions. Syntax: – e1 and e2 stand in for any expressions. Numbers: 251 240 301 – Note prefix notation. Note recursive Booleans: #t #f structure! … Examples: (+ 251 240) (+ (+ 251 240) 301) Evaluation: (+ #t 251) Values evaluate to themselves. Expressions, Bindings, Meta-language 6 Expressions, Bindings, Meta-language 7 Addition expression Not quite! Addition expression Syntax: (+ e1 e2) Syntax: (+ e1 e2) Note recursive Evaluation: structure! Evaluation: Dynamic type checking 1. Evaluate e1 to a value v1. 1. Evaluate e1 to a value v1. 2. Evaluate e2 to a value v2. 2. Evaluate e2 to a value v2. 3. Return the arithmetic sum of v1 + v2. 3. If v1 and v2 are numbers then return the arithmetic sum of v1 + v2. Otherwise there is a type error. Expressions, Bindings, Meta-language 8 Expressions, Bindings, Meta-language 9 The language of languages ! A grammar formalizes syntax. Because it pays to be precise. non-terminal Syntax: symbols – Formal grammar notation e ::= v Non-terminal e – Conventions for writing syntax patterns | ( + e e ) has 2 productions, separated by "|". Grammar meta-syntax. terminal symbols "An expression e is one of: – Any value v – Any addition expression (+ e e) of any two expressions" Expressions, Bindings, Meta-language 10 Expressions, Bindings, Meta-language 11 Racket syntax so far Notation conventions Expressions Outside the grammar: e ::= v • Use of a non-terminal symbol, such as e, in syntax | ( + e e ) examples and evaluation rules means any expression matching one of the productions of e in the grammar. Literal Values • Two uses of e in the same context are aliases; they mean v ::= #f | #t | n the same expression. Number values • Subscripts (or suffixes) distinguish separate instances of a n ::= 0 | 1 | 2 | … single non-terminal, e.g., e1, e2, …, en or e1, e2, …, en. Expressions, Bindings, Meta-language 12 Expressions, Bindings, Meta-language 13 The language of languages ! Judgments and rules formalize semantics. Because it pays to be precise. Syntax: Judgment e ↓ v means "expression e evaluates to value v." – Formal grammar notation – Conventions for writing syntax patterns It is implemented by inference rules for different cases: Semantics: value rule: v ↓ v [value] – Judgments: addition rule: • formal assertions, like functions if e1 ↓ n1 – Inference rules: and e2 ↓ n2 e1 ↓ n1 and n is the arithmetic sum e2 ↓ n2 • implications between judgments, like cases of functions of n1 and n2 n = n1 + n2 – Derivations: then (+ e1 e2) ↓ n [add] (+ e1 e2) ↓ n • deductions based on rules, like applying functions … Expressions, Bindings, Meta-language 14 Expressions, Bindings, Meta-language 15 If all premises hold Inference rules then the conclusion holds. Evaluation derivations Axiom (no premises) Inference rule notation and meaning Bar is optional for axioms. An evaluation derivation is a "proof" that an expression Conclusion [value] v ↓ v evaluates to a value using the evaluation rules. Rule name (+ 3 (+ 5 4)) ↓ 12 by the addition rule because: Number values, not just any values. – 3 ↓ 3 by the value rule, where 3 is a number Models dynamic type checking. – and (+ 5 4) ↓ 9 by the addition rule , where 9 is a number, because: e1 ↓ n1 "v is the arithmetic sum Premises of the numbers n1 and n2." • 5 ↓ 5 by the value rule, where 5 is a number e2 ↓ n2 (not Racket syntax) n = n1 + n2 • and 4 ↓ 4 by the value rule, where 4 is a number Conclusion [add] (+ e1 e2) ↓ n • and 9 is the sum of 5 and 4 Rule name – and 12 is the sum of 3 and 9 . Expressions, Bindings, Meta-language 16 Expressions, Bindings, Meta-language 17 Evaluation derivations Errors are modeled by “stuck” derivations. Rules defining the evaluation judgment How to evaluate How to evaluate Adding vertical bars e ↓ v [value] helps clarify nesting. v ↓ v (+ #t (+ 5 4))? (+ (+ 1 2) (+ 5 #f))? ↓ e1 ↓ n1 #t n 1 ↓ 1 [value] 3 ↓ 3 [value] e2 ↓ n2 5 ↓ 5 [value] 2 ↓ 2 [value] n = n1 + n2 3 = 1 + 2 5 ↓ 5 [value] [add] 4 ↓ 4 [value] [add] (+ e1 e2) ↓ n 9 = 5 + 4 (+ 1 2) ↓ 3 4 ↓ 4 [value] [add] (+ 5 4) ↓ 9 5 ↓ 5 [value] 9 = 5 + 4 #f ↓ n [add] (+ 5 4) ↓ 9 [add] [add] Stuck. Can’t apply the [add] rule 12 = 3 + 9 [add] because there is no rule that Stuck. Can’t apply the [add] rule (+ 3 (+ 5 4)) ↓ 12 allows #t to evaluate to a number. because there is no rule that allows #t to evaluate to a number. Expressions, Bindings, Meta-language 18 Expressions, Bindings, Meta-language 19 Other number expressions Conditional if expressions Similar syntax and evaluation for: Syntax: (if e1 e2 e3) + - * / quotient < > <= >= = Some small differences. Evaluation: Build syntax and evaluation rules for: 1. Evaluate e1 to a value v1. and quotient > 2. If v1 is not the value #f then evaluate e2 and return the result otherwise evaluate e3 and return the result Expressions, Bindings, Meta-language 20 Expressions, Bindings, Meta-language 21 Evaluation rules for if expressions. if expressions if expressions are expressions. e1 ↓ v1 e3 is not evaluated! Racket has no "statements!" e2 ↓ v2 v1 is not #f [if nonfalse] (if (< 9 (- 251 240)) (if e1 e2 e3) ↓ v2 (+ 4 (* 3 2)) (+ 4 (* 3 3))) (+ 4 (* 3 (if (< 9 (- 251 240)) 2 3))) e1 ↓ #f e2 is not evaluated! e3 ↓ v3 (if (if (< 1 2) (> 4 3) (> 5 6)) [if false] (if e1 e2 e3) ↓ v3 (+ 7 8) (* 9 10) Notice: at most one of these rules can have its premises satisfied! Expressions, Bindings, Meta-language 22 Expressions, Bindings, Meta-language 23 if expression evaluation Language design choice: if semantics v1 not required to be a Boolean value Will either of these expressions result in an e1 ↓ v1 error (stuck derivation) when evaluated? e2 ↓ v2 v1 is not #f [if nonfalse] (if e1 e2 e3) ↓ v2 (if (> 251 240) 251 (/ 251 0)) Alternative design (if #f (+ #t 251) 251) e1 ↓ #t e2 ↓ v2 [if true] (if e1 e2 e3) ↓ v2 Expressions, Bindings, Meta-language 24 Expressions, Bindings, Meta-language 25 Variables and environments More Racket syntax How do we know the value of a variable? Bindings b ::= (define x e) (define x (+ 1 2)) (define y (* 4 x)) Expressions (define diff (- y x)) e ::= v | x | ( + e e ) | … | (if e e e) (define test (< x diff)) (if test (+ (* x y) diff) 17) Literal Values (booleans, numbers) Keep a dynamic environment: v ::= #f | #t | n – A sequence of bindings mapping identifier (variable name) to value. Identifiers (variable names) – “Context” for evaluation, used in evaluation rules. x (see valid identifier explanation) Expressions, Bindings, Meta-language 26 Expressions, Bindings, Meta-language 27 Dynamic environments Variable reference expressions Grammar for environment notation: Syntax: x E ::= . (empty environment) x is any identifier | x ⟼ v, E (one binding, rest of environment) where: Evaluation rule: • x is any legal variable identifier Look up x in the current environment, E, and return • v is any value the value, v, to which x is bound. If there is no binding for x, a name error occurs. Search from most to least recent (left to right). Concrete example: E ⊢ e ↓ v num ⟼ 17, absZero ⟼ -273, true ⟼ #t, . Abstract example: Revised expression E(x) = v x1 ⟼ v1, x2 ⟼ v2, …, xn ⟼ vn, . evaluation judgment [var] uses environment. E ⊢ x ↓ v Expressions, Bindings, Meta-language 28 Expressions, Bindings, Meta-language 29 Expression evaluation rules E ⊢ x ↓ v Derivation with environments must pass the environment. E ⊢ v ↓ v [value] E ⊢ e1 ↓ n1 E ⊢ e2 ↓ n2 Let E = test ⟼ #t, diff ⟼ 9, y ⟼ 12, x ⟼ 3 E(x) = v n = n1 + n2 [var] [add] E ⊢ x ↓ v E ⊢(+ e1 e2) ↓ n E ⊢ test ↓ #t [var] E ⊢ x ↓ 3 [var] E ⊢ e1 ↓ v1 E ⊢ e2 ↓ v2 E ⊢ 5 ↓ 5 [value] [mult] v1 is not #f E ⊢(* x 5) ↓ 15 [if nonfalse] E ⊢ (if e1 e2 e3) ↓ v2 E ⊢ diff ↓ 9 [var] [add] E ⊢ (+ (* x 5) diff) ↓ 24 E ⊢ e1 ↓ #f [if nonfalse] E ⊢ (if test (+ (* x 5) diff) 17) ↓ 24 E ⊢ e3 ↓ v3 [if false] E ⊢ (if e1 e2 e3) ↓ v3 Expressions, Bindings, Meta-language 30 Expressions, Bindings, Meta-language 31 define bindings Environment example ; E0 = .
Recommended publications
  • Introduction to Programming in Lisp
    Introduction to Programming in Lisp Supplementary handout for 4th Year AI lectures · D W Murray · Hilary 1991 1 Background There are two widely used languages for AI, viz. Lisp and Prolog. The latter is the language for Logic Programming, but much of the remainder of the work is programmed in Lisp. Lisp is the general language for AI because it allows us to manipulate symbols and ideas in a commonsense manner. Lisp is an acronym for List Processing, a reference to the basic syntax of the language and aim of the language. The earliest list processing language was in fact IPL developed in the mid 1950’s by Simon, Newell and Shaw. Lisp itself was conceived by John McCarthy and students in the late 1950’s for use in the newly-named field of artificial intelligence. It caught on quickly in MIT’s AI Project, was implemented on the IBM 704 and by 1962 to spread through other AI groups. AI is still the largest application area for the language, but the removal of many of the flaws of early versions of the language have resulted in its gaining somewhat wider acceptance. One snag with Lisp is that although it started out as a very pure language based on mathematic logic, practical pressures mean that it has grown. There were many dialects which threaten the unity of the language, but recently there was a concerted effort to develop a more standard Lisp, viz. Common Lisp. Other Lisps you may hear of are FranzLisp, MacLisp, InterLisp, Cambridge Lisp, Le Lisp, ... Some good things about Lisp are: • Lisp is an early example of an interpreted language (though it can be compiled).
    [Show full text]
  • PUB DAM Oct 67 CONTRACT N00014-83-6-0148; N00014-83-K-0655 NOTE 63P
    DOCUMENT RESUME ED 290 438 IR 012 986 AUTHOR Cunningham, Robert E.; And Others TITLE Chips: A Tool for Developing Software Interfaces Interactively. INSTITUTION Pittsburgh Univ., Pa. Learning Research and Development Center. SPANS AGENCY Office of Naval Research, Arlington, Va. REPORT NO TR-LEP-4 PUB DAM Oct 67 CONTRACT N00014-83-6-0148; N00014-83-K-0655 NOTE 63p. PUB TYPE Reports - Research/Technical (143) EDRS PRICE MF01/PC03 Plus Postage. DESCRIPTORS *Computer Graphics; *Man Machine Systems; Menu Driven Software; Programing; *Programing Languages IDENTIF7ERS Direct Manipulation Interface' Interface Design Theory; *Learning Research and Development Center; LISP Programing Language; Object Oriented Programing ABSTRACT This report provides a detailed description of Chips, an interactive tool for developing software employing graphical/computer interfaces on Xerox Lisp machines. It is noted that Chips, which is implemented as a collection of customizable classes, provides the programmer with a rich graphical interface for the creation of rich graphical interfaces, and the end-user with classes for modeling the graphical relationships of objects on the screen and maintaining constraints between them. This description of the system is divided into five main sections: () the introduction, which provides background material and a general description of the system; (2) a brief overview of the report; (3) detailed explanations of the major features of Chips;(4) an in-depth discussion of the interactive aspects of the Chips development environment; and (5) an example session using Chips to develop and modify a small portion of an interface. Appended materials include descriptions of four programming techniques that have been sound useful in the development of Chips; descriptions of several systems developed at the Learning Research and Development Centel tsing Chips; and a glossary of key terms used in the report.
    [Show full text]
  • Allegro CL User Guide
    Allegro CL User Guide Volume 1 (of 2) version 4.3 March, 1996 Copyright and other notices: This is revision 6 of this manual. This manual has Franz Inc. document number D-U-00-000-01-60320-1-6. Copyright 1985-1996 by Franz Inc. All rights reserved. No part of this pub- lication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means electronic, mechanical, by photocopying or recording, or otherwise, without the prior and explicit written permission of Franz incorpo- rated. Restricted rights legend: Use, duplication, and disclosure by the United States Government are subject to Restricted Rights for Commercial Software devel- oped at private expense as specified in DOD FAR 52.227-7013 (c) (1) (ii). Allegro CL and Allegro Composer are registered trademarks of Franz Inc. Allegro Common Windows, Allegro Presto, Allegro Runtime, and Allegro Matrix are trademarks of Franz inc. Unix is a trademark of AT&T. The Allegro CL software as provided may contain material copyright Xerox Corp. and the Open Systems Foundation. All such material is used and distrib- uted with permission. Other, uncopyrighted material originally developed at MIT and at CMU is also included. Appendix B is a reproduction of chapters 5 and 6 of The Art of the Metaobject Protocol by G. Kiczales, J. des Rivieres, and D. Bobrow. All this material is used with permission and we thank the authors and their publishers for letting us reproduce their material. Contents Volume 1 Preface 1 Introduction 1.1 The language 1-1 1.2 History 1-1 1.3 Format
    [Show full text]
  • S Allegro Common Lisp Foreign Function Interface
    Please do not remove this page Extensions to the Franz, Inc.'s Allegro Common Lisp foreign function interface Keane, John https://scholarship.libraries.rutgers.edu/discovery/delivery/01RUT_INST:ResearchRepository/12643408560004646?l#13643533500004646 Keane, J. (1996). Extensions to the Franz, Inc.’s Allegro Common Lisp foreign function interface. Rutgers University. https://doi.org/10.7282/t3-pqns-7h57 This work is protected by copyright. You are free to use this resource, with proper attribution, for research and educational purposes. Other uses, such as reproduction or publication, may require the permission of the copyright holder. Downloaded On 2021/09/29 22:58:32 -0400 Extensions to the Franz Incs Allegro Common Lisp Foreign Function Interface John Keane Department of Computer Science Rutgers University New Brunswick NJ keanecsrutgersedu January Abstract As provided by Franz Inc the foreign function interface of Allegro Com mon Lisp has a number of limitations This pap er describ es extensions to the interface that facilitate the inclusion of C and Fortran co de into Common Lisp systems In particular these extensions make it easy to utilize libraries of numerical subroutines such as those from Numerical Recip es in C from within ACL including those routines that take functions as arguments A mechanism for creating Lisplike dynamic runtime closures for C routines is also describ ed Acknowledgments The research presented in this do cument is supp orted in part by NASA grants NCC and NAG This research is also part of the Rutgers based
    [Show full text]
  • A Quick Introduction to Common Lisp
    CSC 244/444 Notes last updated Feb 3, 2020 A Quick Introduction to Common Lisp Lisp is a functional language well-suited to sym- bolic AI, based on the λ-calculus and with list structures as a very flexible basic data type; pro- grams are themselves list structures, and thus can be created and manipulated just like other data. This introduction isn't intended to give you all the details, but just enough to get across the essential ideas, and to let you get under way quickly. The best way to make use of it is in front of a computer, trying out all the things mentioned. Basic characteristics of Lisp and Common Lisp: • Lisp is primarily intended for manipulating symbolic data in the form of list struc- tures, e.g., (THREE (BLIND MICE) SEE (HOW (THEY RUN)) !) • Arithmetic is included, e.g., (SQRT (+ (* 3 3) (* 4 4))) or (sqrt (+ (* 3 3) (* 4 4))) (Common Lisp is case-insensitive, except in strings between quotes " ... ", specially delimited symbols like |Very Unusual Symbol!|, and for characters prefixed with \\"). • Common Lisp (unlike John McCarthy's original \pure" Lisp) has arrays and record structures; this leads to more understandable and efficient code, much as in typed languages, but there is no obligatory typing. • All computation consists of expression evaluation. For instance, typing in the above (SQRT ...) expression and hitting the enter key immediately gives 5. • Lisp is a functional language based on Alonzo Church's λ-calculus (which like Turing machines provides a complete basis for all computable functions). For instance, a function for the square root of the sum of two squares can be expressed as (lambda (x y) (sqrt (+ (* x x) (* y y)))).
    [Show full text]
  • Parallel Programming with Lisp for Performance
    Parallel Programming with Lisp for Performance Pascal Costanza, Intel, Belgium European Lisp Symposium 2014, Paris, France The views expressed are my own, and not those of my employer. Legal Notices • Cilk, Intel, the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. Other names and brands may be claimed as the property of others. Results have been estimated based on internal Intel analysis and are provided for informational purposes only. Any difference in system hardware or software design or configuration may affect actual performance. Intel does not control or audit the design or implementation of third party benchmark data or Web sites referenced in this document. Intel encourages all of its customers to visit the referenced Web sites or others where similar performance benchmark data are reported and confirm whether the referenced benchmark data are accurate and reflect performance of systems available for purchase. • Optimization Notice: Intel’s compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instructions sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. (Notice revision #20110804) • Copyright © 2014 Intel Corporation.
    [Show full text]
  • Common Lisp Quick Reference
    Common Lisp Quick Reference Compiled by W Burger WS Symb ols nil Constant whose value is itself NIL t Constant whose value is itself T symbolp e Returns T if e evaluates to a symb ol otherwise NIL boundp e Returns T if the value of e whichmust b e a symb ol has neither a global nor a lo cal value defvar sym e Denes sym to b e a global variable with initial value e defparameter sym e Denes sym to b e a global parameter whose value initial e will maychange at runtime but is not exp ected to defconstant sym e Denes sym to b e a global constant whose value e will not change while the program is running Value Assignment setf place e Stores the value of e in the place sp ecied by place setq sym e Evaluates e and makes it the value of the symbol sym the value of e is returned InputOutput read stream Reads the printed representation of a single ob ject from stream which defaults to standardinput builds a corresp onding ob ject and returns the ob ject readline stream eoferrorp eofvalue recursivep Reads a line of text terminated by a newline or endoffile character from stream which defaults to standardinput and returns two values the line as a character string and a Bo olean value T if the line was terminated byanendoffile and NIL if it was terminated by a newline readchar stream eoferrorp eofvalue recursivep Reads one character from stream which defaults to standardinput and returns the corre sp onding character ob ject readcharnohang stream eoferrorp eofvalue recursivep Reads and returns a character from stream which defaults to standardinputif
    [Show full text]
  • The Racket Manifesto∗
    The Racket Manifesto∗ Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shriram Krishnamurthi Eli Barzilay, Jay McCarthy, Sam Tobin-Hochstadt Abstract The creation of a programming language calls for guiding principles that point the developers to goals. This article spells out the three basic principles behind the 20-year development of Racket. First, programming is about stating and solving problems, and this activity normally takes place in a context with its own language of discourse; good programmers ought to for- mulate this language as a programming language. Hence, Racket is a programming language for creating new programming languages. Second, by following this language-oriented approach to programming, systems become multi-lingual collections of interconnected components. Each language and component must be able to protect its specific invariants. In support, Racket offers protection mechanisms to implement a full language spectrum, from C-level bit manipulation to soundly typed extensions. Third, because Racket considers programming as problem solving in the correct language, Racket also turns extra-linguistic mechanisms into linguistic constructs, especially mechanisms for managing resources and projects. The paper explains these principles and how Racket lives up to them, presents the evaluation framework behind the design process, and concludes with a sketch of Racket’s imperfections and opportunities for future improvements. 1998 ACM Subject Classification D.3.3 Language Constructs and Features Keywords and phrases design
    [Show full text]
  • An Open Source Implementation of the Locator/ID Separation Protocol
    OpenLISP: An Open Source Implementation of the Locator/ID Separation Protocol L. Iannone D. Saucez O. Bonaventure TUB – Deutsche Telekom Laboratories AG, Universit´ecatholique de Louvain Universit´ecatholique de Louvain [email protected] [email protected] [email protected] Abstract—The network research community has recently description of the encapsulation and decapsulation operations, started to work on the design of an alternate Internet Archi- the forwarding operation and offer several options as mapping tecture aiming at solving some scalability issues that the current system. Nevertheless there is no specification of an API to Internet is facing. The Locator/ID separation paradigm seems to well fit the requirements for this new Internet Architecture. allow the mapping system to interact with the forwarding Among the various solutions, LISP (Locator/ID Separation Pro- engine. In OpenLISP we proposed and implemented a new tocol), proposed by Cisco, has gained attention due to the fact socket based solution in order to overcome this issue: the that it is incrementally deployable. In the present paper we give Mapping Sockets. Mapping sockets make OpenLISP an open a short overview on OpenLISP, an open-source implementation and flexible solution, where different approaches for the lo- of LISP. Beside LISP’s basic specifications, OpenLISP provides a new socket-based API, namely the Mapping Sockets, which makes cator/ID separation paradigm can be experimented, even if OpenLISP an ideal experimentation platform for LISP, but also not strictly related to LISP. To the best of our knowledge, other related protocols. OpenLISP is the only existing effort in developing an open source Locator/ID separation approach.
    [Show full text]
  • Proposal for a Dynamic Synchronous Language Pejman Attar, Frédéric Boussinot, Louis Mandel, Jean-Ferdy Susini
    Proposal for a Dynamic Synchronous Language Pejman Attar, Frédéric Boussinot, Louis Mandel, Jean-Ferdy Susini To cite this version: Pejman Attar, Frédéric Boussinot, Louis Mandel, Jean-Ferdy Susini. Proposal for a Dynamic Syn- chronous Language. 2011. hal-00590420 HAL Id: hal-00590420 https://hal.archives-ouvertes.fr/hal-00590420 Preprint submitted on 3 May 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Proposal for a Dynamic Synchronous Language∗ Pejman Attar Fr´ed´eric Boussinot Louis Mandel INRIA - INDES INRIA - INDES Universit´eParis 11 - LRI [email protected] [email protected] INRIA - PARKAS [email protected] Jean-Ferdy Susini CNAM - C´edric [email protected] May 3, 2011 Abstract or Java threads). The simplification basically results from a cleaner and simpler semantics, which reduces We propose a new scripting language called DSL bas- the number of possible interleavings in parallel com- ed on the synchronous/reactive model. In DSL, sys- putations. However, standard synchronous languages tems are composed of several sites executed asyn- introduce specific issues (namely, non-termination of chronously, and each site is running scripts in a syn- instants) and have major difficulties to cope with dy- chronous parallel way.
    [Show full text]
  • The Kvaser T Programming Language
    The Kvaser t Programming Language Copyright 2011 KVASER AB, Mölndal, Sweden http://www.kvaser.com Compiler version: 3.1 Last updated 2013-01-30 This document is preliminary and subject to change. (This page is intentionally left blank.) KVASER AB, Aminogatan 25A, 431 53 Mölndal, Sweden http://www.kvaser.com The Kvaser t Programming Language 3(67) Table of Contents 1 t Programming ........................................................................................... 9 1.1 Overview ........................................................................................................................................ 9 1.1.1 Creating a t Program ............................................................................................................. 10 1.1.2 Using a t Program ................................................................................................................. 10 1.1.3 Version of t compiler ............................................................................................................ 10 1.1.4 Inherited Settings Versus t Program Settings........................................................................ 11 1.2 Introduction to the t Language for CAN .................................................................................. 11 1.2.1 Simple Example .................................................................................................................... 11 1.2.2 More Complex Example ......................................................................................................
    [Show full text]
  • How to Make Lisp Go Faster Than C [Pdf]
    IAENG International Journal of Computer Science, 32:4, IJCS_32_4_19 ______________________________________________________________________________________ How to make Lisp go faster than C Didier Verna∗ Abstract statically (hence known at compile-time), just as you would do in C. Contrary to popular belief, Lisp code can be very ef- cient today: it can run as fast as equivalent C code Safety Levels While dynamically typed Lisp code or even faster in some cases. In this paper, we explain leads to dynamic type checking at run-time, it how to tune Lisp code for performance by introducing is possible to instruct the compilers to bypass the proper type declarations, using the appropriate all safety checks in order to get optimum per- data structures and compiler information. We also formance. explain how eciency is achieved by the compilers. These techniques are applied to simple image process- Data Structures While Lisp is mainly known for ing algorithms in order to demonstrate the announced its basement on list processing, the Common- performance on pixel access and arithmetic operations Lisp standard features very ecient data types in both languages. such as specialized arrays, structs or hash tables, making lists almost completely obsolete. Keywords: Lisp, C, Numerical Calculus, Image Pro- cessing, Performance Experiments on the performance of Lisp and C were conducted in the eld of image processing. We bench- 1 Introduction marked, in both languages, 4 simple algorithms to measure the performances of the fundamental low- More than 15 years after the standardization process level operations: massive pixel access and arithmetic of Common-Lisp [5], and more than 10 years after processing.
    [Show full text]