Coding Guidelines for Prolog Has Never Been Published
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From Plain Prolog to Logtalk Objects: Effective Code Encapsulation and Reuse
From Plain Prolog to Logtalk Objects: Effective Code Encapsulation and Reuse Paulo Moura Dep. of Computer Science, Univ. of Beira Interior, Portugal Center for Research in Advanced Computing Systems INESC Porto, Portugal http://logtalk.org/ [email protected] ICLP 2009 Inivited Talk Someone said I need one... 2 Spoilers • Objects in a Prolog world • Logtalk design goals • Logtalk architecture • Logtalk versus Prolog and Prolog modules • Logtalk overview and quick tour • Some demos (if time allows) • Logtalk as a portable Prolog application • Logtalk programming support 3 A warning... • I have a laser and I’m not afraid to use it ... Beware of asking embarrassing questions! • But please feel free to interrupt and ask nice ones that make the speaker shine! 4 A bit of history... • Project started in January 1998 • First version for registered users in July 1998 • First public beta in October 1998 • First stable version in February 1999 5 Logtalk in numbers • Compiler + runtime: ~11000 lines of Prolog code • 37 major releases, 122 including minor ones • Current version: Logtalk 2.37.2 minor release number major release number second generation of Logtalk • ~1500 downloads/month (so many earthlings, so little time) 6 Logtalk distribution • Full sources (compiler/runtime, Prolog config files, libraries) • MacOS X (pkg), Linux (rpm), Debian (deb), and Windows (exe) installers XHTML and PDF User and Reference Manuals • (121 + 144 pages) • +90 programming examples • Support for several text editors and syntax highlighters (text services and code publishing) 7 Objects in Prolog?!? We’re being invaded! 8 Objects have identifiers and dynamic state! • It seems Prolog modules are there first: Identifier! :- module(broadcast, [...]). -
Bash . . Notes, Version
2.2 Quoting and literals 4. ${#var} returns length of the string. Inside single quotes '' nothing is interpreted: 5. ${var:offset:length} skips first offset they preserve literal values of characters enclosed characters from var and truncates the output Bash 5.1.0 notes, version 0.2.209 within them. A single (strong) quote may not appear to given length. :length may be skipped. between single quotes, even when escaped, but it Negative values separated with extra space may appear between double (weak) quotes "". Remigiusz Suwalski are accepted. ey work quite similarly, with an exception that the 6. uses a default value, if shell expands any variables that appear within them ${var:-value} var August 19, 2021 is empty or unset. (pathname expansion, process substitution and word splitting are disabled, everything else works!). ${var:=value} does the same, but performs an assignment as well. Bash, a command line interface for interacting with It is a very important concept: without them Bash the operating system, was created in the 1980s. splits lines into words at whitespace characters – ${var:+value} uses an alternative value if 1 (Google) shell style guide tabs and spaces. See also: IFS variable and $'...' var isn’t empty or unset! and $"..." (both are Bash extensions, to be done). e following notes are meant to be summary of a 2.4.4 Command substitution style guide written by Paul Armstrong and too many Avoid backticks `code` at all cost! To execute commands in a subshell and then pass more to mention (revision 1.26). 2.3 Variables their stdout (but not stderr!), use $( commands) . -
On the Implementation of a Cloud-Based Computing Test Bench Environment for Prolog Systems †
information Article On the Implementation of a Cloud-Based Computing Test Bench Environment for Prolog Systems † Ricardo Gonçalves, Miguel Areias * ID and Ricardo Rocha ID CRACS & INESC TEC and Faculty of Sciences, University of Porto, Rua do Campo Alegre, 1021/1055, 4169-007 Porto, Portugal; [email protected] (R.G.); [email protected] (R.R.) * Correspondence: [email protected] † This paper is an extended version of our paper published in the Symposium on Languages, Applications and Technologies 2017. Received: 13 September 2017; Accepted: 13 October 2017; Published: 19 October 2017 Abstract: Software testing and benchmarking are key components of the software development process. Nowadays, a good practice in large software projects is the continuous integration (CI) software development technique. The key idea of CI is to let developers integrate their work as they produce it, instead of performing the integration at the end of each software module. In this paper, we extend a previous work on a benchmark suite for the YAP Prolog system, and we propose a fully automated test bench environment for Prolog systems, named Yet Another Prolog Test Bench Environment (YAPTBE), aimed to assist developers in the development and CI of Prolog systems. YAPTBE is based on a cloud computing architecture and relies on the Jenkins framework as well as a new Jenkins plugin to manage the underlying infrastructure. We present the key design and implementation aspects of YAPTBE and show its most important features, such as its graphical user interface (GUI) and the automated process that builds and runs Prolog systems and benchmarks. -
ANSI® Programmer's Reference Manual Line Matrix Series Printers
ANSI® Programmer’s Reference Manual Line Matrix Series Printers Printronix, LLC makes no representations or warranties of any kind regarding this material, including, but not limited to, implied warranties of merchantability and fitness for a particular purpose. Printronix, LLC shall not be held responsible for errors contained herein or any omissions from this material or for any damages, whether direct, indirect, incidental or consequential, in connection with the furnishing, distribution, performance or use of this material. The information in this manual is subject to change without notice. This document contains proprietary information protected by copyright. No part of this document may be reproduced, copied, translated or incorporated in any other material in any form or by any means, whether manual, graphic, electronic, mechanical or otherwise, without the prior written consent of Printronix, LLC Copyright © 1998, 2012 Printronix, LLC All rights reserved. Trademark Acknowledgements ANSI is a registered trademark of American National Standards Institute, Inc. Centronics is a registered trademark of Genicom Corporation. Dataproducts is a registered trademark of Dataproducts Corporation. Epson is a registered trademark of Seiko Epson Corporation. IBM and Proprinter are registered trademarks and PC-DOS is a trademark of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation. Printronix, IGP, PGL, LinePrinter Plus, and PSA are registered trademarks of Printronix, LLC. QMS is a registered -
Logical Segmentation of Source Code
Logical Segmentation of Source Code Jacob Dormuth, Ben Gelman, Jessica Moore, David Slater Machine Learning Group Two Six Labs Arlington, Virginia, United States E-mail: fjacob.dormuth, ben.gelman, jessica.moore, [email protected] Abstract identifying where to generate automatic comments, and lo- cating useful sub-function boundaries for bug detection. Many software analysis methods have come to rely on Current approaches to segmentation do not intentionally machine learning approaches. Code segmentation - the pro- capture logical content that could improve its usefulness to cess of decomposing source code into meaningful blocks - the aforementioned problems. Traditionally, code segmen- can augment these methods by featurizing code, reducing tation has been done at a syntactic level. This means that noise, and limiting the problem space. Traditionally, code language-specific syntax, such as the closing curly brace of segmentation has been done using syntactic cues; current a class or function, is the indicator for a segment. Although approaches do not intentionally capture logical content. We this method is conceptually simple, the resulting segments develop a novel deep learning approach to generate logical do not intentionally take into account semantic information. code segments regardless of the language or syntactic cor- Syntactic structures in natural language, such as sentences rectness of the code. Due to the lack of logically segmented and paragraphs, are generally also indicators of semantic source code, we introduce a unique data set construction separation. In other words, two different paragraphs likely technique to approximate ground truth for logically seg- capture two logically separate ideas, and it is simple to de- mented code. -
SNL Final Report
SNL Final Report BY James Lin AleX Liu AndrE Paiva Daniel Maxson December 17 2014 Contents 1 INTRODUCTION 1 1.1 INTRODUCTION . .1 1.2 Motivation . .1 1.3 Why CALL IT Stage (null) language? . .1 2 Language TUTORIAL 2 2.1 Compilation WALKTHROUGH . .2 2.1.1 Compiler Setup . .2 2.1.2 Compile SNL TO Java . .2 2.1.3 Compile SNL TO Java ExECUTABLE . .2 2.2 Stages . .3 2.3 Recipes . .3 2.4 VARIABLES . .3 2.5 Lists . .3 2.6 ContrOL FloW . .4 2.7 Input/Output . .4 3 Language ReferENCE Manual 5 3.1 LeXICAL Elements . .5 3.1.1 Comments . .5 3.1.2 IDENTIfiERS........................................5 3.1.3 KeYWORDS . .5 3.1.4 LiterALS . .5 3.1.5 OperATORS . .6 3.1.6 SeperATORS . .6 3.1.7 White Space . .6 3.2 Data TYPES . .7 3.2.1 TYPING . .7 3.2.2 Built-in Data TYPES . .7 3.3 ExprESSIONS AND OperATORS . .7 3.4 Recipes . .8 I 3.4.1 Recipe DefiNITIONS . .8 3.4.2 Calling Recipes . .8 3.5 PrOGRAM StructurE AND Scope . .9 3.5.1 PrOGRAM StructurE . .9 3.5.2 Stages . .9 3.5.3 Scope . .9 4 PrOJECT Plan 10 4.1 PrOJECT PrOCESSES . 10 4.1.1 Planning . 10 4.1.2 SpecifiCATION . 10 4.1.3 DeVELOPMENT . 10 4.1.4 TESTING . 10 4.2 Style Guide . 11 4.3 TEAM Responsibilities . 11 4.4 PrOJECT Timeline . 12 4.5 DeVELOPMENT EnvirONMENT . 12 4.6 PrOJECT Log . 12 5 ArCHITECTURAL Design 13 5.1 OvervieW . -
Cleiej Author Instructions
CLEI ELECTRONIC JOURNAL, VOLUME 21, NUMBER 1, PAPER 5, APRIL 2018 Attributes Influencing the Reading and Comprehension of Source Code – Discussing Contradictory Evidence Talita Vieira Ribeiro and Guilherme Horta Travassos PESC/COPPE/UFRJ – Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil, 21941-972 {tvribeiro, ght}@cos.ufrj.br Abstract Background: Coding guidelines can be contradictory despite their intention of providing a universal perspective on source code quality. For instance, five attributes (code size, semantic complexity, internal documentation, layout style, and identifier length) out of 13 presented contradictions regarding their influence (positive or negative) on the source code readability and comprehensibility. Aims: To investigate source code attributes and their influence on readability and comprehensibility. Method: A literature review was used to identify source code attributes impacting the source code reading and comprehension, and an empirical study was performed to support the assessment of four attributes that presented empirical contradictions in the technical literature. Results: Regardless participants’ experience; all participants showed more positive comprehensibility perceptions for Python snippets with more lines of code. However, their readability perceptions regarding code size were contradictory. The less experienced participants preferred more lines of code while the more experienced ones preferred fewer lines of code. Long and complete-word identifiers presented better readability and comprehensibility according to both novices and experts. Comments contribute to better comprehension. Furthermore, four indentation spaces dominated the code reading preference. Conclusions: Coding guidelines contradictions still demand further investigation to provide indications on possible confounding factors explaining some of the inconclusive results. Keywords: Source code quality, Readability, Comprehensibility, Experimental Software Engineering. -
A Linguistic Symbiosis Approach to Bring the Declarative Power of Prolog to Java
LogicObjects : A Linguistic Symbiosis Approach to Bring the Declarative Power of Prolog to Java Sergio Castro Kim Mens Paulo Moura RELEASeD lab RELEASeD lab Dept. of Computer Science ICTEAM Institute ICTEAM Institute University of Beira Interior Université catholique de Université catholique de & CRACS, INESC–TEC Louvain, Belgium Louvain, Belgium Portugal [email protected] [email protected] [email protected] ABSTRACT Although there exists some other work that focusses on Logic programming is well suited for declaratively solving facilitating the interaction from an object-oriented language computational problems that require knowledge representa- to a logic language, to the best of our knowledge this is the tion and reasoning. Object-oriented languages, on the other first approach that provides a truly transparent, automatic hand, are well suited for modeling real-world concepts and and customizable integration from the perspective of the profit from rich ecosystems developed around them, which object-oriented language. are often missing from logic languages. For applications that This paper is structured as follows: Section 2 presents a require both the declarative power of logic programming and problem of declarative nature and its implementation in a the rich modeling expressiveness and development environ- logic language. This will be referenced in the next sections. ments offered by object-oriented languages, there is a need Section 3 presents our framework and shows how it enables for reconciling both worlds. LogicObjects is our linguistic a transparent access from Java to our implementation in symbiosis framework for integrating Prolog within the Java logic. Section 4 discuss relevant related work and section 5 language. -
Identifying Javascript Skimmers on High-Value Websites
Imperial College of Science, Technology and Medicine Department of Computing CO401 - Individual Project MEng Identifying JavaScript Skimmers on High-Value Websites Author: Supervisor: Thomas Bower Dr. Sergio Maffeis Second marker: Dr. Soteris Demetriou June 17, 2019 Identifying JavaScript Skimmers on High-Value Websites Thomas Bower Abstract JavaScript Skimmers are a new type of malware which operate by adding a small piece of code onto a legitimate website in order to exfiltrate private information such as credit card numbers to an attackers server, while also submitting the details to the legitimate site. They are impossible to detect just by looking at the web page since they operate entirely in the background of the normal page operation and display no obvious indicators to their presence. Skimmers entered the public eye in 2018 after a series of high-profile attacks on major retailers including British Airways, Newegg, and Ticketmaster, claiming the credit card details of hundreds of thousands of victims between them. To date, there has been little-to-no work towards preventing websites becoming infected with skimmers, and even less so for protecting consumers. In this document, we propose a novel and effective solution for protecting users from skimming attacks by blocking attempts to contact an attackers server with sensitive information, in the form of a Google Chrome web extension. Our extension takes a two-pronged approach, analysing both the dynamic behaviour of the script such as outgoing requests, as well as static analysis by way of a number of heuristic techniques on scripts loaded onto the page which may be indicative of a skimmer. -
Comparative Programming Languages CM20253
We have briefly covered many aspects of language design And there are many more factors we could talk about in making choices of language The End There are many languages out there, both general purpose and specialist And there are many more factors we could talk about in making choices of language The End There are many languages out there, both general purpose and specialist We have briefly covered many aspects of language design The End There are many languages out there, both general purpose and specialist We have briefly covered many aspects of language design And there are many more factors we could talk about in making choices of language Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important For example, can you easily join together code written in Java and C? The End Or languages And then the interopability of languages becomes important For example, can you easily join together code written in Java and C? The End Or languages Often a single project can use several languages, each suited to its part of the project For example, can you easily join together code written in Java and C? The End Or languages Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important The End Or languages Often a single project can use several languages, each suited to its part of the project And then the interopability of languages becomes important For example, can you easily -
A Simple Approach to Distributed Objects in Prolog
A Simple Approach to Distributed Objects in Prolog Manuel Carro Manuel Hermenegildo Computer Science School Technical University of Madrid Boadilla del Monte, E-28660,Spain {mcarro,herme}@fi.upm.es Abstract. We present the design of a distributed object system for Prolog, based on adding remote execution and distribution capabilities to a previously existing object system. Remote execution brings RPC into a Prolog system, and its semantics is easy to express in terms of well-known Prolog builtins. The final distributed object design features state mobility and user-transparent network behavior. We sketch an implementation which provides distributed garbage collection and some degree of tolerance to network failures. We provide a preliminary study of the overhead of the communication mechanism for some test cases. Keywords: Objects, Distributed Execution, Remote Calis, Migration, Garbage Collection. 1 Introduction Distributed objects are the natural sequel to object oriented programming and distributed programming. They can be used to implement a wide range of software systems: remote databases, service migration to improve access speed, automatic caching, implementation of stateful agents, etc. A good deal of proposals combining distribution and objects have been developed in the realm of procedural and 00 languages; however, many of them boil down to adding convenient librarles to an existing host language which did not have any provisión for distributed execution [BGL98]. Among the proposals which address 00 and distribution from scratch we may cite Emerald [Jul88], Obliq [Car95], and, to some extent, Jini [We + OO]. Although there have been several proposals for coupling LP and 00 in the logic programming arena (e.g., SICStus objects [Swe99], Prolog++ [Mos94], LogTalk [MouOO], O'Ciao [PB02], and others), few proposal have been made, to the best of our knowledge, to couple objects and distribution. -
Learning a Metric for Code Readability Raymond P.L
TSE SPECIAL ISSUE ON THE ISSTA 2008 BEST PAPERS 1 Learning a Metric for Code Readability Raymond P.L. Buse, Westley Weimer Abstract—In this paper, we explore the concept of code readability and investigate its relation to software quality. With data collected from 120 human annotators, we derive associations between a simple set of local code features and human notions of readability. Using those features, we construct an automated readability measure and show that it can be 80% effective, and better than a human on average, at predicting readability judgments. Furthermore, we show that this metric correlates strongly with three measures of software quality: code changes, automated defect reports, and defect log messages. We measure these correlations on over 2.2 million lines of code, as well as longitudinally, over many releases of selected projects. Finally, we discuss the implications of this study on programming language design and engineering practice. For example, our data suggests that comments, in of themselves, are less important than simple blank lines to local judgments of readability. Index Terms—software readability, program understanding, machine learning, software maintenance, code metrics, FindBugs ✦ 1 INTRODUCTION its sequencing control (e.g., he conjectured that goto unnecessarily complicates program understanding), and E define readability as a human judgment of how employed that notion to help motivate his top-down easy a text is to understand. The readability of a W approach to system design [9]. program is related to its maintainability, and is thus a key We present a descriptive model of software readability factor in overall software quality.