Languages the Racket Way 2016 Language Workbench Challenge
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Processing an Intermediate Representation Written in Lisp
Processing an Intermediate Representation Written in Lisp Ricardo Pena,˜ Santiago Saavedra, Jaime Sanchez-Hern´ andez´ Complutense University of Madrid, Spain∗ [email protected],[email protected],[email protected] In the context of designing the verification platform CAVI-ART, we arrived to the need of deciding a textual format for our intermediate representation of programs. After considering several options, we finally decided to use S-expressions for that textual representation, and Common Lisp for processing it in order to obtain the verification conditions. In this paper, we discuss the benefits of this decision. S-expressions are homoiconic, i.e. they can be both considered as data and as code. We exploit this duality, and extensively use the facilities of the Common Lisp environment to make different processing with these textual representations. In particular, using a common compilation scheme we show that program execution, and verification condition generation, can be seen as two instantiations of the same generic process. 1 Introduction Building a verification platform such as CAVI-ART [7] is a challenging endeavour from many points of view. Some of the tasks require intensive research which can make advance the state of the art, as it is for instance the case of automatic invariant synthesis. Some others are not so challenging, but require a lot of pondering and discussion before arriving at a decision, in order to ensure that all the requirements have been taken into account. A bad or a too quick decision may have a profound influence in the rest of the activities, by doing them either more difficult, or longer, or more inefficient. -
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 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. -
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 -
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. -
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. -
Feature-Specific Profiling
Feature-Specific Profiling LEIF ANDERSEN, PLT @ Northeastern University, United States of America VINCENT ST-AMOUR, PLT @ Northwestern University, United States of America JAN VITEK, Northeastern University and Czech Technical University MATTHIAS FELLEISEN, PLT @ Northeastern University, United States of America While high-level languages come with significant readability and maintainability benefits, their performance remains difficult to predict. For example, programmers may unknowingly use language features inappropriately, which cause their programs to run slower than expected. To address this issue, we introduce feature-specific profiling, a technique that reports performance costs in terms of linguistic constructs. Festure-specific profilers help programmers find expensive uses of specific features of their language. We describe the architecture ofa profiler that implements our approach, explain prototypes of the profiler for two languages withdifferent characteristics and implementation strategies, and provide empirical evidence for the approach’s general usefulness as a performance debugging tool. ACM Reference Format: Leif Andersen, Vincent St-Amour, Jan Vitek, and Matthias Felleisen. 2018. Feature-Specific Profiling. 1,1 (September 2018), 35 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn 1 PROFILING WITH ACTIONABLE ADVICE When programs take too long to run, programmers tend to reach for profilers to diagnose the problem. Most profilers attribute the run-time costs during a program’s execution to cost centers such as function calls or statements in source code. Then they rank all of a program’s cost centers in order to identify and eliminate key bottlenecks (Amdahl 1967). If such a profile helps programmers optimize their code, we call it actionable because it points to inefficiencies that can be remedied with changes to the program. -
The Semantics of Syntax Applying Denotational Semantics to Hygienic Macro Systems
The Semantics of Syntax Applying Denotational Semantics to Hygienic Macro Systems Neelakantan R. Krishnaswami University of Birmingham <[email protected]> 1. Introduction body of a macro definition do not interfere with names oc- Typically, when semanticists hear the words “Scheme” or curring in the macro’s arguments. Consider this definition of and “Lisp”, what comes to mind is “untyped lambda calculus a short-circuiting operator: plus higher-order state and first-class control”. Given our (define-syntax and typical concerns, this seems to be the essence of Scheme: it (syntax-rules () is a dynamically typed applied lambda calculus that sup- ((and e1 e2) (let ((tmp e1)) ports mutable data and exposes first-class continuations to (if tmp the programmer. These features expose a complete com- e2 putational substrate to programmers so elegant that it can tmp))))) even be characterized mathematically; every monadically- representable effect can be implemented with state and first- In this definition, even if the variable tmp occurs freely class control [4]. in e2, it will not be in the scope of the variable definition However, these days even mundane languages like Java in the body of the and macro. As a result, it is important to support higher-order functions and state. So from the point interpret the body of the macro not merely as a piece of raw of view of a working programmer, the most distinctive fea- syntax, but as an alpha-equivalence class. ture of Scheme is something quite different – its support for 2.2 Open Recursion macros. The intuitive explanation is that a macro is a way of defining rewrites on abstract syntax trees. -
Meta-Tracing Makes a Fast Racket
Meta-tracing makes a fast Racket Carl Friedrich Bolz Tobias Pape Jeremy Siek Software Development Team Hasso-Plattner-Institut Indiana University King’s College London Potsdam [email protected] [email protected] [email protected] potsdam.de Sam Tobin-Hochstadt Indiana University [email protected] ABSTRACT 1. INTRODUCTION Tracing just-in-time (JIT) compilers record and optimize the instruc- Just-in-time (JIT) compilation has been applied to a wide variety tion sequences they observe at runtime. With some modifications, languages, with early examples including Lisp, APL, Basic, Fortran, a tracing JIT can perform well even when the executed program is Smalltalk, and Self [Aycock, 2003]. These days, JIT compilation itself an interpreter, an approach called meta-tracing. The advantage is mainstream; it is responsible for running both server-side Java of meta-tracing is that it separates the concern of JIT compilation applications [Paleczny et al., 2001] and client-side JavaScript appli- from language implementation, enabling the same JIT compiler to cations in web browsers [Hölttä, 2013]. be used with many different languages. The RPython meta-tracing Mitchell [1970] observed that one could obtain an instruction JIT compiler has enabled the efficient interpretation of several dy- sequence from an interpreter by recording its actions. The interpreter namic languages including Python (PyPy), Prolog, and Smalltalk. can then jump to this instruction sequence, this trace, when it returns In this paper we present initial findings in applying the RPython to interpret the same part of the program. For if-then-else statements, JIT to Racket. Racket comes from the Scheme family of program- there is a trace for only one branch. -
Functional SMT Solving with Z3 and Racket
Functional SMT Solving with Z3 and Racket Siddharth Agarwal∗y Amey Karkarey [email protected] [email protected] ∗Facebook Inc, yDepartment of Computer Science & Engineering Menlo Park, CA, USA Indian Institute of Technology Kanpur, India Abstract—Satisfiability Modulo Theories (SMT) solvers are can attack range from simple puzzles like Sudoku and n- powerful tools that can quickly solve complex constraints queens, to planning and scheduling, program analysis [8], involving Booleans, integers, first-order logic predicates, lists, whitebox fuzz testing [9] and bounded model checking [10]. and other data types. They have a vast number of potential Yet SMT solvers are only used by a small number of experts. It applications, from constraint solving to program analysis and isn’t hard to see why: the standard way for programs to interact verification. However, they are so complex to use that their power with SMT solvers like Z3 [4], Yices [5] and CVC3 [11] is via is inaccessible to all but experts in the field. We present an attempt to make using SMT solvers simpler by integrating the powerful but relatively arcane C APIs that require the users Z3 solver into a host language, Racket. The system defines a to know the particular solver’s internals. For example, here programmer’s interface in Racket that makes it easy to harness is a C program that asks Z3 whether the simple proposition the power of Z3 to discover solutions to logical constraints. The p ^ :p is satisfiable. interface, although in Racket, retains the structure and brevity Z3_config cfg = Z3_mk_config(); of the SMT-LIB format. -
Comparative Studies of 10 Programming Languages Within 10 Diverse Criteria
Department of Computer Science and Software Engineering Comparative Studies of 10 Programming Languages within 10 Diverse Criteria Jiang Li Sleiman Rabah Concordia University Concordia University Montreal, Quebec, Concordia Montreal, Quebec, Concordia [email protected] [email protected] Mingzhi Liu Yuanwei Lai Concordia University Concordia University Montreal, Quebec, Concordia Montreal, Quebec, Concordia [email protected] [email protected] COMP 6411 - A Comparative studies of programming languages 1/139 Sleiman Rabah, Jiang Li, Mingzhi Liu, Yuanwei Lai This page was intentionally left blank COMP 6411 - A Comparative studies of programming languages 2/139 Sleiman Rabah, Jiang Li, Mingzhi Liu, Yuanwei Lai Abstract There are many programming languages in the world today.Each language has their advantage and disavantage. In this paper, we will discuss ten programming languages: C++, C#, Java, Groovy, JavaScript, PHP, Schalar, Scheme, Haskell and AspectJ. We summarize and compare these ten languages on ten different criterion. For example, Default more secure programming practices, Web applications development, OO-based abstraction and etc. At the end, we will give our conclusion that which languages are suitable and which are not for using in some cases. We will also provide evidence and our analysis on why some language are better than other or have advantages over the other on some criterion. 1 Introduction Since there are hundreds of programming languages existing nowadays, it is impossible and inefficient