LISP a Programmable Programming Language
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The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Bringing GNU Emacs to Native Code
Bringing GNU Emacs to Native Code Andrea Corallo Luca Nassi Nicola Manca [email protected] [email protected] [email protected] CNR-SPIN Genoa, Italy ABSTRACT such a long-standing project. Although this makes it didactic, some Emacs Lisp (Elisp) is the Lisp dialect used by the Emacs text editor limitations prevent the current implementation of Emacs Lisp to family. GNU Emacs can currently execute Elisp code either inter- be appealing for broader use. In this context, performance issues preted or byte-interpreted after it has been compiled to byte-code. represent the main bottleneck, which can be broken down in three In this work we discuss the implementation of an optimizing com- main sub-problems: piler approach for Elisp targeting native code. The native compiler • lack of true multi-threading support, employs the byte-compiler’s internal representation as input and • garbage collection speed, exploits libgccjit to achieve code generation using the GNU Com- • code execution speed. piler Collection (GCC) infrastructure. Generated executables are From now on we will focus on the last of these issues, which con- stored as binary files and can be loaded and unloaded dynamically. stitutes the topic of this work. Most of the functionality of the compiler is written in Elisp itself, The current implementation traditionally approaches the prob- including several optimization passes, paired with a C back-end lem of code execution speed in two ways: to interface with the GNU Emacs core and libgccjit. Though still a work in progress, our implementation is able to bootstrap a func- • Implementing a large number of performance-sensitive prim- tional Emacs and compile all lexically scoped Elisp files, including itive functions (also known as subr) in C. -
Common Lispworks User Guide
LispWorks® for the Windows® Operating System Common LispWorks User Guide Version 5.1 Copyright and Trademarks Common LispWorks User Guide (Windows version) Version 5.1 February 2008 Copyright © 2008 by LispWorks Ltd. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of LispWorks Ltd. The information in this publication is provided for information only, is subject to change without notice, and should not be construed as a commitment by LispWorks Ltd. LispWorks Ltd assumes no responsibility or liability for any errors or inaccuracies that may appear in this publication. The software described in this book is furnished under license and may only be used or copied in accordance with the terms of that license. LispWorks and KnowledgeWorks are registered trademarks of LispWorks Ltd. Adobe and PostScript are registered trademarks of Adobe Systems Incorporated. Other brand or product names are the registered trade- marks or trademarks of their respective holders. The code for walker.lisp and compute-combination-points is excerpted with permission from PCL, Copyright © 1985, 1986, 1987, 1988 Xerox Corporation. The XP Pretty Printer bears the following copyright notice, which applies to the parts of LispWorks derived therefrom: Copyright © 1989 by the Massachusetts Institute of Technology, Cambridge, Massachusetts. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, pro- vided that this copyright and permission notice appear in all copies and supporting documentation, and that the name of M.I.T. -
An Evaluation of Go and Clojure
An evaluation of Go and Clojure A thesis submitted in partial satisfaction of the requirements for the degree Bachelors of Science in Computer Science Fall 2010 Robert Stimpfling Department of Computer Science University of Colorado, Boulder Advisor: Kenneth M. Anderson, PhD Department of Computer Science University of Colorado, Boulder 1. Introduction Concurrent programming languages are not new, but they have been getting a lot of attention more recently due to their potential with multiple processors. Processors have gone from growing exponentially in terms of speed, to growing in terms of quantity. This means processes that are completely serial in execution will soon be seeing a plateau in performance gains since they can only rely on one processor. A popular approach to using these extra processors is to make programs multi-threaded. The threads can execute in parallel and use shared memory to speed up execution times. These multithreaded processes can significantly speed up performance, as long as the number of dependencies remains low. Amdahl‘s law states that these performance gains can only be relative to the amount of processing that can be parallelized [1]. However, the performance gains are significant enough to be looked into. These gains not only come from the processing being divvied up into sections that run in parallel, but from the inherent gains from sharing memory and data structures. Passing new threads a copy of a data structure can be demanding on the processor because it requires the processor to delve into memory and make an exact copy in a new location in memory. Indeed some studies have shown that the problem with optimizing concurrent threads is not in utilizing the processors optimally, but in the need for technical improvements in memory performance [2]. -
Programming with GNU Emacs Lisp
Programming with GNU Emacs Lisp William H. Mitchell (whm) Mitchell Software Engineering (.com) GNU Emacs Lisp Programming Slide 1 Copyright © 2001-2008 by William H. Mitchell GNU Emacs Lisp Programming Slide 2 Copyright © 2001-2008 by William H. Mitchell Emacs Lisp Introduction A little history GNU Emacs Lisp Programming Slide 3 Copyright © 2001-2008 by William H. Mitchell Introduction GNU Emacs is a full-featured text editor that contains a complete Lisp system. Emacs Lisp is used for a variety of things: • Complete applications such as mail and news readers, IM clients, calendars, games, and browsers of various sorts. • Improved interfaces for applications such as make, diff, FTP, shells, and debuggers. • Language-specific editing support. • Management of interaction with version control systems such as CVS, Perforce, SourceSafe, and StarTeam. • Implementation of Emacs itself—a substantial amount of Emacs is written in Emacs Lisp. And more... GNU Emacs Lisp Programming Slide 4 Copyright © 2001-2008 by William H. Mitchell A little history1 Lisp: John McCarthy is the father of Lisp. The name Lisp comes from LISt Processing Language. Initial ideas for Lisp were formulated in 1956-1958; some were implemented in FLPL (FORTRAN-based List Processing Language). The first Lisp implementation, for application to AI problems, took place 1958-1962 at MIT. There are many dialects of Lisp. Perhaps the most commonly used dialect is Common Lisp, which includes CLOS, the Common Lisp Object System. See http://www-formal.stanford.edu/jmc/history/lisp/lisp.html for some interesting details on the early history of Lisp. 1 Don't quote me! GNU Emacs Lisp Programming Slide 5 Copyright © 2001-2008 by William H. -
Understanding the Syntactic Rule Usage in Java
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by UCL Discovery Understanding the Syntactic Rule Usage in Java Dong Qiua, Bixin Lia,∗, Earl T. Barrb, Zhendong Suc aSchool of Computer Science and Engineering, Southeast University, China bDepartment of Computer Science, University College London, UK cDepartment of Computer Science, University of California Davis, USA Abstract Context: Syntax is fundamental to any programming language: syntax defines valid programs. In the 1970s, computer scientists rigorously and empirically studied programming languages to guide and inform language design. Since then, language design has been artistic, driven by the aesthetic concerns and intuitions of language architects. Despite recent studies on small sets of selected language features, we lack a comprehensive, quantitative, empirical analysis of how modern, real-world source code exercises the syntax of its programming language. Objective: This study aims to understand how programming language syntax is employed in actual development and explore their potential applications based on the results of syntax usage analysis. Method: We present our results on the first such study on Java, a modern, mature, and widely-used programming language. Our corpus contains over 5,000 open-source Java projects, totalling 150 million source lines of code (SLoC). We study both independent (i.e. applications of a single syntax rule) and dependent (i.e. applications of multiple syntax rules) rule usage, and quantify their impact over time and project size. Results: Our study provides detailed quantitative information and yields insight, particularly (i) confirming the conventional wisdom that the usage of syntax rules is Zipfian; (ii) showing that the adoption of new rules and their impact on the usage of pre-existing rules vary significantly over time; and (iii) showing that rule usage is highly contextual. -
Clojure, Given the Pun on Closure, Representing Anything Specific
dynamic, functional programming for the JVM “It (the logo) was designed by my brother, Tom Hickey. “It I wanted to involve c (c#), l (lisp) and j (java). I don't think we ever really discussed the colors Once I came up with Clojure, given the pun on closure, representing anything specific. I always vaguely the available domains and vast emptiness of the thought of them as earth and sky.” - Rich Hickey googlespace, it was an easy decision..” - Rich Hickey Mark Volkmann [email protected] Functional Programming (FP) In the spirit of saying OO is is ... encapsulation, inheritance and polymorphism ... • Pure Functions • produce results that only depend on inputs, not any global state • do not have side effects such as Real applications need some changing global state, file I/O or database updates side effects, but they should be clearly identified and isolated. • First Class Functions • can be held in variables • can be passed to and returned from other functions • Higher Order Functions • functions that do one or both of these: • accept other functions as arguments and execute them zero or more times • return another function 2 ... FP is ... Closures • main use is to pass • special functions that retain access to variables a block of code that were in their scope when the closure was created to a function • Partial Application • ability to create new functions from existing ones that take fewer arguments • Currying • transforming a function of n arguments into a chain of n one argument functions • Continuations ability to save execution state and return to it later think browser • back button 3 .. -
S-Algol Reference Manual Ron Morrison
S-algol Reference Manual Ron Morrison University of St. Andrews, North Haugh, Fife, Scotland. KY16 9SS CS/79/1 1 Contents Chapter 1. Preface 2. Syntax Specification 3. Types and Type Rules 3.1 Universe of Discourse 3.2 Type Rules 4. Literals 4.1 Integer Literals 4.2 Real Literals 4.3 Boolean Literals 4.4 String Literals 4.5 Pixel Literals 4.6 File Literal 4.7 pntr Literal 5. Primitive Expressions and Operators 5.1 Boolean Expressions 5.2 Comparison Operators 5.3 Arithmetic Expressions 5.4 Arithmetic Precedence Rules 5.5 String Expressions 5.6 Picture Expressions 5.7 Pixel Expressions 5.8 Precedence Table 5.9 Other Expressions 6. Declarations 6.1 Identifiers 6.2 Variables, Constants and Declaration of Data Objects 6.3 Sequences 6.4 Brackets 6.5 Scope Rules 7. Clauses 7.1 Assignment Clause 7.2 if Clause 7.3 case Clause 7.4 repeat ... while ... do ... Clause 7.5 for Clause 7.6 abort Clause 8. Procedures 8.1 Declarations and Calls 8.2 Forward Declarations 2 9. Aggregates 9.1 Vectors 9.1.1 Creation of Vectors 9.1.2 upb and lwb 9.1.3 Indexing 9.1.4 Equality and Equivalence 9.2 Structures 9.2.1 Creation of Structures 9.2.2 Equality and Equivalence 9.2.3 Indexing 9.3 Images 9.3.1 Creation of Images 9.3.2 Indexing 9.3.3 Depth Selection 9.3.4 Equality and Equivalence 10. Input and Output 10.1 Input 10.2 Output 10.3 i.w, s.w and r.w 10.4 End of File 11. -
The Evolution of Lisp
1 The Evolution of Lisp Guy L. Steele Jr. Richard P. Gabriel Thinking Machines Corporation Lucid, Inc. 245 First Street 707 Laurel Street Cambridge, Massachusetts 02142 Menlo Park, California 94025 Phone: (617) 234-2860 Phone: (415) 329-8400 FAX: (617) 243-4444 FAX: (415) 329-8480 E-mail: [email protected] E-mail: [email protected] Abstract Lisp is the world’s greatest programming language—or so its proponents think. The structure of Lisp makes it easy to extend the language or even to implement entirely new dialects without starting from scratch. Overall, the evolution of Lisp has been guided more by institutional rivalry, one-upsmanship, and the glee born of technical cleverness that is characteristic of the “hacker culture” than by sober assessments of technical requirements. Nevertheless this process has eventually produced both an industrial- strength programming language, messy but powerful, and a technically pure dialect, small but powerful, that is suitable for use by programming-language theoreticians. We pick up where McCarthy’s paper in the first HOPL conference left off. We trace the development chronologically from the era of the PDP-6, through the heyday of Interlisp and MacLisp, past the ascension and decline of special purpose Lisp machines, to the present era of standardization activities. We then examine the technical evolution of a few representative language features, including both some notable successes and some notable failures, that illuminate design issues that distinguish Lisp from other programming languages. We also discuss the use of Lisp as a laboratory for designing other programming languages. We conclude with some reflections on the forces that have driven the evolution of Lisp. -
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 -
Sugarj: Library-Based Syntactic Language Extensibility
SugarJ: Library-based Syntactic Language Extensibility Sebastian Erdweg, Tillmann Rendel, Christian Kastner,¨ and Klaus Ostermann University of Marburg, Germany Abstract import pair.Sugar; Existing approaches to extend a programming language with syntactic sugar often leave a bitter taste, because they cannot public class Test f be used with the same ease as the main extension mechanism private (String, Integer) p = ("12", 34); of the programming language—libraries. Sugar libraries are g a novel approach for syntactically extending a programming Figure 1. Using a sugar library for pairs. language within the language. A sugar library is like an or- dinary library, but can, in addition, export syntactic sugar for using the library. Sugar libraries maintain the compos- 1. Introduction ability and scoping properties of ordinary libraries and are Bridging the gap between domain concepts and the imple- hence particularly well-suited for embedding a multitude of mentation of these concepts in a programming language is domain-specific languages into a host language. They also one of the “holy grails” of software development. Domain- inherit self-applicability from libraries, which means that specific languages (DSLs), such as regular expressions for sugar libraries can provide syntactic extensions for the defi- the domain of text recognition or Java Server Pages for the nition of other sugar libraries. domain of dynamic web pages have often been proposed To demonstrate the expressiveness and applicability of to address this problem [31]. To use DSLs in large soft- sugar libraries, we have developed SugarJ, a language on ware systems that touch multiple domains, developers have top of Java, SDF and Stratego, which supports syntactic to be able to compose multiple domain-specific languages extensibility. -
ESA: a CLIM Library for Writing Emacs-Style Applications
ESA: A CLIM Library for Writing Emacs-Style Applications Robert Strandh Troels Henriksen LaBRI, Université Bordeaux 1 DIKU, University of Copenhagen 351, Cours de la Libération Universitetsparken 1, Copenhagen 33405 Talence Cedex [email protected] France [email protected] David Murray Christophe Rhodes ADMurray Associates Goldsmiths, University of London 10 Rue Carrier Belleuse, 75015 Paris New Cross Road, London, SE14 6NW [email protected] [email protected] ABSTRACT style applications. The central distinguishing feature of an We describe ESA (for Emacs-Style Application), a library Emacs-style application, for our purposes, is that it uses for writing applications with an Emacs look-and-feel within short sequences of keystrokes as the default method of in- the Common Lisp Interface Manager. The ESA library voking commands, and only occasionally requires the user to takes advantage of the layered design of CLIM to provide a type the full name of the command in a minibuffer. A spe- command loop that uses Emacs-style multi-keystroke com- cial keystroke (M-x) is used to invoke commands by name. mand invocation. ESA supplies other functionality for writ- This interaction style is substantially different from the one ing such applications such as a minibuffer for invoking ex- provided by CLIM by default, and therefore required us to tended commands and for supplying command arguments, write a different CLIM top level. Fortunately, CLIM was Emacs-style keyboard macros and numeric arguments, file designed to make this not only possible but fairly straight- and buffer management, and more. ESA is currently used forward, as the implementation of a replacement top level in two major CLIM applications: the Climacs text editor can build on the protocol layers beneath, just as the default (and the Drei text gadget integrated with the McCLIM im- top level is built.