Languages As Libraries
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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. -
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. -
How to Design Co-Programs
JFP, 15 pages, 2021. c Cambridge University Press 2021 1 doi:10.1017/xxxxx EDUCATIONMATTERS How to Design Co-Programs JEREMY GIBBONS Department of Computer Science, University of Oxford e-mail: [email protected] Abstract The observation that program structure follows data structure is a key lesson in introductory pro- gramming: good hints for possible program designs can be found by considering the structure of the data concerned. In particular, this lesson is a core message of the influential textbook “How to Design Programs” by Felleisen, Findler, Flatt, and Krishnamurthi. However, that book discusses using only the structure of input data for guiding program design, typically leading towards structurally recur- sive programs. We argue that novice programmers should also be taught to consider the structure of output data, leading them also towards structurally corecursive programs. 1 Introduction Where do programs come from? This mystery can be an obstacle to novice programmers, who can become overwhelmed by the design choices presented by a blank sheet of paper, or an empty editor window— where does one start? A good place to start, we tell them, is by analyzing the structure of the data that the program is to consume. For example, if the program h is to process a list of values, one may start by analyzing the structure of that list. Either the list is empty ([]), or it is non-empty (a : x) with a head (a) and a tail (x). This provides a candidate program structure: h [ ] = ::: h (a : x) = ::: a ::: x ::: where for the empty list some result must simply be chosen, and for a non-empty list the result depends on the head a and tail x. -
An Optimized R5RS Macro Expander
An Optimized R5RS Macro Expander Sean Reque A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Jay McCarthy, Chair Eric Mercer Quinn Snell Department of Computer Science Brigham Young University February 2013 Copyright c 2013 Sean Reque All Rights Reserved ABSTRACT An Optimized R5RS Macro Expander Sean Reque Department of Computer Science, BYU Master of Science Macro systems allow programmers abstractions over the syntax of a programming language. This gives the programmer some of the same power posessed by a programming language designer, namely, the ability to extend the programming language to fit the needs of the programmer. The value of such systems has been demonstrated by their continued adoption in more languages and platforms. However, several barriers to widespread adoption of macro systems still exist. The language Racket [6] defines a small core of primitive language constructs, including a powerful macro system, upon which all other features are built. Because of this design, many features of other programming languages can be implemented through libraries, keeping the core language simple without sacrificing power or flexibility. However, slow macro expansion remains a lingering problem in the language's primary implementation, and in fact macro expansion currently dominates compile times for Racket modules and programs. Besides the typical problems associated with slow compile times, such as slower testing feedback, increased mental disruption during the programming process, and unscalable build times for large projects, slow macro expansion carries its own unique problems, such as poorer performance for IDEs and other software analysis tools. -
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]. -
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 .. -
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. -
Final Shift for Call/Cc: Direct Implementation of Shift and Reset
Final Shift for Call/cc: Direct Implementation of Shift and Reset Martin Gasbichler Michael Sperber Universitat¨ Tubingen¨ fgasbichl,[email protected] Abstract JxKρ = λk:(k (ρ x)) 0 0 We present a direct implementation of the shift and reset con- Jλx:MKρ = λk:k (λv:λk :(JMK)(ρ[x 7! v]) k ) trol operators in the Scheme 48 system. The new implementation JE1 E2Kρ = λk:JE1Kρ (λ f :JE2Kρ (λa: f a k) improves upon the traditional technique of simulating shift and reset via call/cc. Typical applications of these operators exhibit Figure 1. Continuation semantics space savings and a significant overall performance gain. Our tech- nique is based upon the popular incremental stack/heap strategy for representing continuations. We present implementation details as well as some benchmark measurements for typical applications. this transformation has a direct counterpart as a semantic specifica- tion of the λ calculus; Figure 1 shows such a semantic specification for the bare λ calculus: each ρ is an environment mapping variables Categories and Subject Descriptors to values, and each k is a continuation—a function from values to values. An abstraction denotes a function from an environment to a D.3.3 [Programming Languages]: Language Constructs and Fea- function accepting an argument and a continuation. tures—Control structures In the context of the semantics, the rule for call/cc is this: General Terms Jcall=cc EKρ = λk:JEKρ (λ f : f (λv:λk0:k v) k) Languages, Performance Call=cc E evaluates E and calls the result f ; it then applies f to an Keywords escape function which discards the continuation k0 passed to it and replaces it by the continuation k of the call=cc expression. -
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 -
Functional SMT Solving: a New Interface for Programmers
Functional SMT solving: A new interface for programmers A thesis submitted in Partial Fulfillment of the Requirements for the Degree of Master of Technology by Siddharth Agarwal to the DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING INDIAN INSTITUTE OF TECHNOLOGY KANPUR June, 2012 v ABSTRACT Name of student: Siddharth Agarwal Roll no: Y7027429 Degree for which submitted: Master of Technology Department: Computer Science & Engineering Thesis title: Functional SMT solving: A new interface for programmers Name of Thesis Supervisor: Prof Amey Karkare Month and year of thesis submission: June, 2012 Satisfiability Modulo Theories (SMT) solvers are powerful tools that can quickly solve complex constraints involving booleans, integers, first-order logic predicates, lists, and other data types. They have a vast number of potential applications, from constraint solving to program analysis and verification. However, they are so complex to use that their power is inaccessible to all but experts in the field. We present an attempt to make using SMT solvers simpler by integrating the Z3 solver into a host language, Racket. Our system defines a programmer’s interface in Racket that makes it easy to harness the power of Z3 to discover solutions to logical constraints. The interface, although in Racket, retains the structure and brevity of the SMT-LIB format. We demonstrate this using a range of examples, from simple constraint solving to verifying recursive functions, all in a few lines of code. To my grandfather Acknowledgements This project would have never have even been started had it not been for my thesis advisor Dr Amey Karkare’s help and guidance. Right from the time we were looking for ideas to when we finally had a concrete proposal in hand, his support has been invaluable. -
Modernizing Applications with IBM CICS
Front cover Modernizing Applications with IBM CICS Russell Bonner Sophie Green Ezriel Gross Jim Harrison Debra Scharfstein Will Yates Redpaper IBM Redbooks Modernizing Applications with IBM CICS December 2020 REDP-5628-00 Note: Before using this information and the product it supports, read the information in “Notices” on page v. First Edition (December 2020) © Copyright International Business Machines Corporation 2020. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . .v Trademarks . vi Preface . vii Accompanying education course . vii Authors. viii Now you can become a published author, too! . viii Comments welcome. viii Stay connected to IBM Redbooks . ix Chapter 1. Introduction. 1 1.1 CICS and the hybrid multi-cloud . 2 1.2 Migrating to the hybrid multi-cloud . 2 1.2.1 Maintaining the status quo . 2 1.2.2 Using cloud-native applications. 2 1.2.3 Modernizing existing applications . 3 1.3 CICS Hello World COBOL example . 3 Chapter 2. IBM CICS application development . 5 2.1 Application development in CICS . 6 2.1.1 Batch processing versus online transaction processing . 6 2.1.2 Programming paradigm. 6 2.1.3 Basic architecture of a CICS program. 7 2.1.4 CICS resources. 9 2.2 CICS sample application. 10 2.3 CICS modernization . 11 2.4 CICS built-in transactions . 12 2.4.1 CICS Execute Command Interpreter . 12 2.4.2 CICS Execution Diagnostic Facility. 13 Chapter 3. Coding applications to run in IBM CICS. 15 3.1 Introduction to the EXEC CICS application programming interface . -
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.