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Fortran Isolates the CSE Community
Fortran Isolates the CSE Community Roscoe A. Bartlett, Oak Ridge National Laboratory 10/08/2013 Introduction testing and test-driven development (TDD) by Fortran-only developers. While the research and The continued usage of Fortran as a dominant data supporting the effectiveness of unit testing and programming language isolates the computational TDD has been around for many years [10, 3, 12, 7], science & engineering (CSE) community and hinders the usage of these very successful approaches is very the learning and adoption of modern software low in the Fortran CSE development community. engineering methods. The issue is not primarily that This claim is backed up by personal experience, web Fortran is not suitable for developing many different posts, web searches, and observations by other types of software. Indeed, the are many examples of authors. One interesting data point is that a Google quality CSE software written in Fortran that can search of \Fortran Unit Test" (on 10/4/2013) brings legitimately be considered to be \self-sustaining up a limited number of relevant search results but software" (i.e. clean design and code, well tested, the top result is for the FRUIT Fortran Unit Test minimal controlled dependencies, etc., see [1]). framework [5] (written in Ruby). Right on the main The problem is that there are many CSE page for FRUIT is a quote from FRUIT's author development groups and communities that only Andrew Hang Chen which states: know Fortran and are therefore isolated from the broader software development community where Most of the FORTRAN are important Fortran usage is extremely low (ranked 24th in the in nature, used in nuclear and aerospace TIOBE Index from Nov. -
Python - the Most Attractive & Fastest-Growing Programming Language for Developers
Vol-6 Issue-5 2020 IJARIIE-ISSN(O)-2395-4396 Python - The Most Attractive & Fastest-growing Programming Language for Developers Vishwa Prakash (SRKUMTSE1804) M-Tech, Department of Software Engineering, R.K.D.F. Institute of Science & Technology, Bhopal, M.P., India ABSTRACT Python is a very suitable and easy language for both learning and real-world programming. It is a powerful and high-level object-oriented programming language and created by Guido van Rossum. It is a very good choice for those who are learning programming for the first time because of its simple syntax. It has various standard libraries so it using by a developer in vast range and its capacity to integrate with other languages and use their features attract developers too. In this paper, we describe the main characteristics and features of Python programming. We also discuss the reasons behind python being credited as the most fastest-growing high-level object orient language. We collected the contents of the research done over the articles procured from various magazines and popular websites. This paper then discusses applications of Python programming. To end with we will see a few good examples where python programming is being used. Keyword : - Python, programming languages, object-oriented, open-source, interoperability, Real-world. etc… 1. INTRODUCTION In the late 1980s, Python was conceived, while its implementation began in late 1989 by Guido van Rossum in the Netherlands atCWI (Centrum Wiskunde & Informatica). It was implemented as a successor of ABC language and capable of interfacing and exception handling with the operating system Amoeba. Author Van Rossum is Python's principal and his continuing central role in deciding the road to the development of Python. -
The First Programming Language and Freshman Year in Computer Science: Characterization and Tips for Better Decision Making
The first programming language and freshman year in computer science: characterization and tips for better decision making Sónia Rolland Sobral [0000-0002-5041-3597] 1 REMIT, Universidade Portucalense, Porto, Portugal [email protected] Abstract. The ability to program is the “visible” competency to acquire in an introductory unit in com- puter science. However, before a student is able to write a program, he needs to understand the problem: before formalizing, the student must have to (be able) to think, (be able) to solve and (be able) to define. At an early stage of learning there are no significant differences between programming languages. The discussion of the early programming language continues: probably never will be a consensus among academics. The Association for Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE) computer science curriculum recommendations haven't clearly defined which programming language to adopt: it is the course directors and teachers who must make this choice, consciously and not only following the trends. This article presents a set of items that should be considered when you make a programming lan- guage choice for the first programming unit in higher education computer science courses. Keywords: Programming Languages, Undergraduate Studies; Introduction to Programming. 1 Introduction Programmability is the “visible” skill to be acquired in an introductory unit in computer science. Program- ming can be considered an art [1], a science [2], a discipline [3] or even the science of abstraction [4]. However, using a programming language is no more than a method for the programmer can communicate instructions to the computer. -
Release 0.11 Todd Gamblin
Spack Documentation Release 0.11 Todd Gamblin Feb 07, 2018 Basics 1 Feature Overview 3 1.1 Simple package installation.......................................3 1.2 Custom versions & configurations....................................3 1.3 Customize dependencies.........................................4 1.4 Non-destructive installs.........................................4 1.5 Packages can peacefully coexist.....................................4 1.6 Creating packages is easy........................................4 2 Getting Started 7 2.1 Prerequisites...............................................7 2.2 Installation................................................7 2.3 Compiler configuration..........................................9 2.4 Vendor-Specific Compiler Configuration................................ 13 2.5 System Packages............................................. 16 2.6 Utilities Configuration.......................................... 18 2.7 GPG Signing............................................... 20 2.8 Spack on Cray.............................................. 21 3 Basic Usage 25 3.1 Listing available packages........................................ 25 3.2 Installing and uninstalling........................................ 42 3.3 Seeing installed packages........................................ 44 3.4 Specs & dependencies.......................................... 46 3.5 Virtual dependencies........................................... 50 3.6 Extensions & Python support...................................... 53 3.7 Filesystem requirements........................................ -
The Power of Interoperability: Why Objects Are Inevitable
The Power of Interoperability: Why Objects Are Inevitable Jonathan Aldrich Carnegie Mellon University Pittsburgh, PA, USA [email protected] Abstract 1. Introduction Three years ago in this venue, Cook argued that in Object-oriented programming has been highly suc- their essence, objects are what Reynolds called proce- cessful in practice, and has arguably become the dom- dural data structures. His observation raises a natural inant programming paradigm for writing applications question: if procedural data structures are the essence software in industry. This success can be documented of objects, has this contributed to the empirical success in many ways. For example, of the top ten program- of objects, and if so, how? ming languages at the LangPop.com index, six are pri- This essay attempts to answer that question. After marily object-oriented, and an additional two (PHP reviewing Cook’s definition, I propose the term ser- and Perl) have object-oriented features.1 The equiva- vice abstractions to capture the essential nature of ob- lent numbers for the top ten languages in the TIOBE in- jects. This terminology emphasizes, following Kay, that dex are six and three.2 SourceForge’s most popular lan- objects are not primarily about representing and ma- guages are Java and C++;3 GitHub’s are JavaScript and nipulating data, but are more about providing ser- Ruby.4 Furthermore, objects’ influence is not limited vices in support of higher-level goals. Using examples to object-oriented languages; Cook [8] argues that Mi- taken from object-oriented frameworks, I illustrate the crosoft’s Component Object Model (COM), which has unique design leverage that service abstractions pro- a C language interface, is “one of the most pure object- vide: the ability to define abstractions that can be ex- oriented programming models yet defined.” Academ- tended, and whose extensions are interoperable in a ically, object-oriented programming is a primary focus first-class way. -
Comparing Languages for Engineering Server Software: Erlang, Go, and Scala with Akka
Comparing Languages for Engineering Server Software: Erlang, Go, and Scala with Akka Ivan Valkov, Natalia Chechina, and Phil Trinder School of Computing Science, University of Glasgow G12 8RZ, United Kingdom [email protected], {Natalia.Chechina, Phil.Trinder}@glasgow.ac.uk Abstract functional or object-oriented, with high-level coordination models, Servers are a key element of current IT infrastructures, and must e.g. actors as in Erlang [2] or a process algebra as in Go [6]. Indeed, often deal with large numbers of concurrent requests. The program- the success of some server-based companies is even attributed to ming language used to construct the server has an important role their use of specific languages. As examples WhatsApp’s success in engineering efficient server software, and must support massive is attributed to their use of Erlang [27]; the video streaming leader concurrency on multicore machines with low communication and Twitch uses Go to serve millions of users a day [13]. Research synchronisation overheads. contributions of this paper include the following: This paper investigates 12 highly concurrent programming lan- • A survey of programming language characteristics relevant for guages suitable for engineering servers, and analyses three repre- servers (Section 2.1). sentative languages in detail: Erlang, Go, and Scala with Akka. • The design and implementation of three benchmarks to analyse We have designed three server benchmarks that analyse key per- the multicore server capabilities of Erlang, Go, and Scala with formance characteristics of the languages. The benchmark results Akka (Section 3). suggest that where minimising message latency is crucial, Go and Erlang are best; that Scala with Akka is capable of supporting the • An evaluation of Erlang, Go, and Scala with Akka for key largest number of dormant processes; that for servers that frequently server capabilities, i.e. -
Programming Languages: a Survey
International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 5 Issue: 5 307 – 313 _______________________________________________________________________________________________ Programming Languages: A Survey Krishan Kumar1, Sonal Dahiya2 Assistant professor, ASET, Amity University Haryana, Gurgaon, Haryana, India1,2 [email protected], [email protected] Abstract— The world of Programming Languages is very dynamic. Every company is launching their own programming language which can cater their specific demand and requirement. In this paper, we discussed various popular rankings proposed by different organizations to decide most popular language on basis of various factors like number of Google Trends searches, number of job advertisements, and number of books sold for that language and many more factors. Keywords— Java Programming, Python, Ruby, C. __________________________________________________*****_________________________________________________ I. INTRODUCTION It is difficult to decide which programming languages are most widely used. One language may occupy the greater number of programmer hours, a different one have more lines of code, a third may utilize the most CPU time, and so on. Some languages are very popular for particular kind of applications. For example, COBOL is still strong in the corporate data center, often on large mainframes; FORTRAN in engineering applications; C in embedded applications and operating systems; and other languages are regularly used to write much different kind of applications. Various methods of measuring language popularity has been used, i.e; A. Counting the number of times the language name is mentioned in web searches, such as is done by Google Trends. B. counting the number of job advertisements that mention the language [1][2] C. -
Programming Language Trends in Open Source Development: an Evaluation Using Data from All Production Phase Sourceforge Projects
Programming Language Trends in Open Source Development: An Evaluation Using Data from All Production Phase SourceForge Projects Daniel P. Delorey Charles D. Knutson C. Giraud-Carrier Brigham Young University Brigham Young University Brigham Young University TMCB 2230 TMCB 2214 TMCB 3326 Provo, UT 84602 Provo, UT 84602 Provo, UT 84602 [email protected] [email protected] [email protected] ABSTRACT for natural language like those studied by Sapir, but for pro- In this work, we analyze data collected from the CVS repos- gramming languages as well. itories of 9,997 Open Source projects hosted on SourceForge in an effort to understand trends in programming language A tendency to hesitate in adopting new programming lan- usage in the Open Source community between 2000 and guages, however, may stifle creativity as the limited features 2005. The trends we consider include: 1) the relative popu- of an out-dated language prevent developers from conceiv- larity of the ten most popular programming languages over ing of novel solutions. To quote a well-worn cliche,“When all time, 2) the use of multiple programming languages by indi- you have is a hammer, everything looks like a nail.” Nielson vidual programmers and by individual projects, and 3) the [5] has demonstrated that developers hesitate to use multi- programming languages most often used in combination. paradigm features even after migrating to a new language opting instead to program as if they were using their old Categories and Subject Descriptors language. D.2.8 [Software Engineering]: Metrics—Performance Mea- sures, Process Metrics, Product Metrics In this paper, we use data gathered from the CVS reposito- ries of Open Source projects hosted on SourceForge to eval- Keywords uate trends in programming language usage among Open Source developers. -
Compiler Information
Compiler Information ©1995, Intel Corporation Intro • Compilers for Intel Architecture processors have been continuously improved over the past 2-3 years • Application performance has been improved > 25% during this period of time • All improvements have come from processor independent compiler techniques and enhancements Use a “new generation” compiler as a part of your APP development With on-going compiler improvements, there is tremendous benefit to be realized by using the latest compilers in your application development. These can provide performance enhancements for your applications when running on an Intel486™, Pentium®, or P6 processor. Compiler Program Status Versions of Compilers* w/Optimizations including Pentium® Processor Awareness Gen’l Availability – Absoft: Ftn, C for UNIX Now (4/93) – Borland: C/C++ for NT, Win32s, DOS32 Now (Q4’93) – IBM: C/C++ for OS/2 Now (6/93) – Lahey Ftn90 for DOS32 Now – Liant: Ftn, C for UNIX Now – MetaWare: C/C++ for UNIX Now (6/93) – Microsoft: C/C++ for NT, Win32s Now (8/93) – Microsoft: Fortran for NT, Win32s Now (11/93) – SCO: C for SCO UNIX Now (3/93) – SunPro: C/C++, Ftn for Solaris Now (5/93) – USL: C for UNIX SVR4 Now (Q4’92) – WATCOM: C/C++, Ftn for NT, Win32s, Now (6/93) DOS32, OS/2 Most optimizing compilers have been available since Summer ‘93! *other brands and names are property of their respective owners. Above is a quick list of compilers optimized for the Intel Architecture in general (with Pentium® processor awareness built into the code scheduling) over the last 2 years. The first formal release of Proton (Intel’s reference compiler whose purpose is to offer new compiler technology to the industry) was in March ‘93. -
Supported and Compatible Compilers – Release 2020A
Supported and Compatible Compilers – Release 2020a A number of MathWorks products or product features require that you have a third-party compiler installed on your system. The tables below outline the compilers that are supported by various MathWorks products. These compilers are provided by a number of vendors and are available under a variety of commercial, academic, or open source terms; visit the providers’ websites for further information. Please see Polyspace documentation for the list of compilers that Polyspace supports in the current release. See Supported Interfaces to Other Languages for information about using MATLAB with other programming languages. Windows MinGW is a supported C/C++ compiler which is available free of charge. Download MinGW now. Note: • MinGW will be updated to version 8.3 in a future release. mathworks.com MATLAB Product Family – Release 2020a Fixed Point HDL HDL Audio ROS MATLAB MATLAB Coder GPU Coder SimBiology Designer Coder Verifier Toolbox Toolbox For MEX-file For all features For all features For For For For DPI For For ROS 2 compilation, accelerated accelerated accelerated and TLM validating and custom Compiler loadlibrary, computation computation testbench component generating messages and external simulation generation audio and code usage of plugins generation MATLAB Engine and MAT-file APIs MinGW 6.3 C/C++ (Distributor: mingw-w64) Download Now Available at no charge Microsoft Visual C++ Update 3 Update 5 Update 5 Update 5 Update 5 2019 product family Microsoft Visual C++ 2017 product family11 -
Interface-Driven Software Requirements Analysis
European Scientific Journal October 2016 edition vol.12, No.30 ISSN: 1857 – 7881 (Print) e - ISSN 1857- 7431 Interface-Driven Software Requirements Analysis Rais Aziz Ahmad, Mgr. Department of Information Technologies University of Economics, Prague, Czech Republic doi: 10.19044/esj.2016.v12n30p40 URL:http://dx.doi.org/10.19044/esj.2016.v12n30p40 Abstract Software requirements are one of the root causes of failure for IT software development projects. Reasons for this may be that the requirements are high-level, many might simply be wishes, or frequently changed, or they might be unclear, missing, for example, goals, objectives, strategies, and so on. Another major reason for projects’ failure may also be the use of improper techniques for software requirements specification. Currently, most IT software development projects utilise textual techniques like use cases, user stories, scenarios, and features for software requirements elicitation, analysis and specification. While IT software development processes can construct software in different programming languages, the primary focus here will be those IT projects using object-oriented programming languages. Object-oriented programming itself has several characteristics worth noting, such as its popularity, reusability, modularity, concurrency, abstraction and encapsulation. Object-oriented analysis and design transforms software requirements gathered with textual techniques into object-oriented programming. This transformation can cause complexity in identifying objects, classes and interfaces, which, in turn, complicates the object-oriented analysis and design. Because requirements can change over the course of a project and, likewise, software design can evolve during software construction, the traceability of software requirements with objects and components can become difficult. Apart from leading to project complexity, such a process can impact software quality and, in the worst-case scenario, cause the project to fail entirely. -
The Definitive Guide to GCC
The Definitive Guide to GCC KURT WALL AND WILLIAM VON HAGEN APress Media, LLC The Definitive Guide to GCC Copyright ©2004 by Kurt Wall and William von Hagen Originally published by Apress in 2004 All rights reserved. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval system, without the prior written permission of the copyright owner and the publisher. ISBN 978-1-59059-109-3 ISBN 978-1-4302-0704-7 (eBook) DOI 10.1007/978-1-4302-0704-7 Trademarked names may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, we use the names only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. Technical Reviewer: Gene Sally Editorial Board: Steve Anglin, Dan Appleman, Gary Cornell, James Cox, Tony Davis, John Franklin, Chris Mills, Steven Rycroft, Dominic Shakeshaft, Julian Skinner, Martin Streicher, Jim Sumser, Karen Watterson, Gavin Wray, John Zukowski Assistant Publisher: Grace Wong Project Manager: Sofia Marchant Copy Editor: Ami Knox Production Manager: Kari Brooks Production Editor: Janet Vaii Proofreader: Elizabeth Berry Compositor and Artist: Kinetic Publishing Services, llC Indexer: Valerie Perry Cover Designer: Kurt Krames Manufacturing Manager: Tom Debolski The information in this book is distributed on an "as is" hasis, without warranty. Although every precaution bas been taken in the preparation of this work, neither the author(s) nor Apress shall have any liability to any person or entity with respect to any loss or damage caused or alleged to be caused directly or indirectly by the information contained in this work.