Evaluating the GO Programming Language with Design Patterns
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UNIX and Computer Science Spreading UNIX Around the World: by Ronda Hauben an Interview with John Lions
Winter/Spring 1994 Celebrating 25 Years of UNIX Volume 6 No 1 "I believe all significant software movements start at the grassroots level. UNIX, after all, was not developed by the President of AT&T." Kouichi Kishida, UNIX Review, Feb., 1987 UNIX and Computer Science Spreading UNIX Around the World: by Ronda Hauben An Interview with John Lions [Editor's Note: This year, 1994, is the 25th anniversary of the [Editor's Note: Looking through some magazines in a local invention of UNIX in 1969 at Bell Labs. The following is university library, I came upon back issues of UNIX Review from a "Work In Progress" introduced at the USENIX from the mid 1980's. In these issues were articles by or inter- Summer 1993 Conference in Cincinnati, Ohio. This article is views with several of the pioneers who developed UNIX. As intended as a contribution to a discussion about the sig- part of my research for a paper about the history and devel- nificance of the UNIX breakthrough and the lessons to be opment of the early days of UNIX, I felt it would be helpful learned from it for making the next step forward.] to be able to ask some of these pioneers additional questions The Multics collaboration (1964-1968) had been created to based on the events and developments described in the UNIX "show that general-purpose, multiuser, timesharing systems Review Interviews. were viable." Based on the results of research gained at MIT Following is an interview conducted via E-mail with John using the MIT Compatible Time-Sharing System (CTSS), Lions, who wrote A Commentary on the UNIX Operating AT&T and GE agreed to work with MIT to build a "new System describing Version 6 UNIX to accompany the "UNIX hardware, a new operating system, a new file system, and a Operating System Source Code Level 6" for the students in new user interface." Though the project proceeded slowly his operating systems class at the University of New South and it took years to develop Multics, Doug Comer, a Profes- Wales in Australia. -
B-Prolog User's Manual
B-Prolog User's Manual (Version 8.1) Prolog, Agent, and Constraint Programming Neng-Fa Zhou Afany Software & CUNY & Kyutech Copyright c Afany Software, 1994-2014. Last updated February 23, 2014 Preface Welcome to B-Prolog, a versatile and efficient constraint logic programming (CLP) system. B-Prolog is being brought to you by Afany Software. The birth of CLP is a milestone in the history of programming languages. CLP combines two declarative programming paradigms: logic programming and constraint solving. The declarative nature has proven appealing in numerous ap- plications, including computer-aided design and verification, databases, software engineering, optimization, configuration, graphical user interfaces, and language processing. It greatly enhances the productivity of software development and soft- ware maintainability. In addition, because of the availability of efficient constraint- solving, memory management, and compilation techniques, CLP programs can be more efficient than their counterparts that are written in procedural languages. B-Prolog is a Prolog system with extensions for programming concurrency, constraints, and interactive graphics. The system is based on a significantly refined WAM [1], called TOAM Jr. [19] (a successor of TOAM [16]), which facilitates software emulation. In addition to a TOAM emulator with a garbage collector that is written in C, the system consists of a compiler and an interpreter that are written in Prolog, and a library of built-in predicates that are written in C and in Prolog. B-Prolog does not only accept standard-form Prolog programs, but also accepts matching clauses, in which the determinacy and input/output unifications are explicitly denoted. Matching clauses are compiled into more compact and faster code than standard-form clauses. -
Cobol Vs Standards and Conventions
Number: 11.10 COBOL VS STANDARDS AND CONVENTIONS July 2005 Number: 11.10 Effective: 07/01/05 TABLE OF CONTENTS 1 INTRODUCTION .................................................................................................................................................. 1 1.1 PURPOSE .................................................................................................................................................. 1 1.2 SCOPE ...................................................................................................................................................... 1 1.3 APPLICABILITY ........................................................................................................................................... 2 1.4 MAINFRAME COMPUTER PROCESSING ....................................................................................................... 2 1.5 MAINFRAME PRODUCTION JOB MANAGEMENT ............................................................................................ 2 1.6 COMMENTS AND SUGGESTIONS ................................................................................................................. 3 2 COBOL DESIGN STANDARDS .......................................................................................................................... 3 2.1 IDENTIFICATION DIVISION .................................................................................................................. 4 2.1.1 PROGRAM-ID .......................................................................................................................... -
Introduction to Concurrent Programming
Introduction to Concurrent Programming Rob Pike Computing Sciences Research Center Bell Labs Lucent Technologies [email protected] February 2, 2000 1 Overview The world runs in parallel, but our usual model of software does not. Programming languages are sequential. This mismatch makes it hard to write systems software that provides the interface between a computer (or user) and the world. Solutions: processes, threads, concurrency, semaphores, spin locks, message-passing. But how do we use these things? Real problem: need an approach to writing concurrent software that guides our design and implementation. We will present our model for designing concurrent software. It’s been used in several languages for over a decade, producing everything from symbolic algebra packages to window systems. This course is not about parallel algorithms or using multiprocessors to run programs faster. It is about using the power of processes and communication to design elegant, responsive, reliable systems. 2 History (Biased towards Systems) Dijkstra: guarded commands, 1976. Hoare: Communicating Sequential Processes (CSP), (paper) 1978. Run multiple communicating guarded command sets in parallel. Hoare: CSP Book, 1985. Addition of channels to the model, rather than directly talking to processes. Cardelli and Pike: Squeak, 1983. Application of CSP model to user interfaces. Pike: Concurrent Window System, (paper) 1988. Application of Squeak approach to systems software. Pike: Newsqueak, 1989. Interpreted language; used to write toy window system. Winterbottom: Alef, 1994. True compiled concurrent language, used to write production systems software. Mullender: Thread library, 1999. Retrofit to C for general usability. 3 Other models exist Our approach is not the only way. -
UTF-8-Plan9-Paper
Hello World or Kαληµε´ρα κο´σµε or Rob Pike Ken Thompson AT&T Bell Laboratories Murray Hill, New Jersey 07974 ABSTRACT Plan 9 from Bell Labs has recently been converted from ASCII to an ASCII- compatible variant of Unicode, a 16-bit character set. In this paper we explain the rea- sons for the change, describe the character set and representation we chose, and present the programming models and software changes that support the new text format. Although we stopped short of full internationalizationÐfor example, system error mes- sages are in Unixese, not JapaneseÐwe believe Plan 9 is the first system to treat the rep- resentation of all major languages on a uniform, equal footing throughout all its software. Introduction The world is multilingual but most computer systems are based on English and ASCII. The release of Plan 9 [Pike90], a new distributed operating system from Bell Laboratories, seemed a good occasion to correct this chauvinism. It is easier to make such deep changes when building new systems than by refit- ting old ones. The ANSI C standard [ANSIC] contains some guidance on the matter of ‘wide’ and ‘multi-byte’ characters but falls far short of solving the myriad associated problems. We could find no literature on how to convert a system to larger character sets, although some individual programs had been converted. This paper reports what we discovered as we explored the problem of representing multilingual text at all levels of an operating system, from the file system and kernel through the applications and up to the window sys- tem and display. -
Tiny Tools Gerard J
Tiny Tools Gerard J. Holzmann Jet Propulsion Laboratory, California Institute of Technology Many programmers like the convenience of integrated development environments (IDEs) when developing code. The best examples are Microsoft’s Visual Studio for Windows and Eclipse for Unix-like systems, which have both been around for many years. You get all the features you need to build and debug software, and lots of other things that you will probably never realize are also there. You can use all these features without having to know very much about what goes on behind the screen. And there’s the rub. If you’re like me, you want to know precisely what goes on behind the screen, and you want to be able to control every bit of it. The IDEs can sometimes feel as if they are taking over every last corner of your computer, leaving you wondering how much bigger your machine would have to be to make things run a little more smoothly. So what follows is for those of us who don’t use IDEs. It’s for the bare metal programmers, who prefer to write code using their own screen editor, and who do everything else with command-line tools. There are no real conveniences that you need to give up to work this way, but what you gain is a better understanding your development environment, and the control to change, extend, or improve it whenever you find better ways to do things. Bare Metal Programming Many developers who write embedded software work in precisely this way. -
A Quick Reference to C Programming Language
A Quick Reference to C Programming Language Structure of a C Program #include(stdio.h) /* include IO library */ #include... /* include other files */ #define.. /* define constants */ /* Declare global variables*/) (variable type)(variable list); /* Define program functions */ (type returned)(function name)(parameter list) (declaration of parameter types) { (declaration of local variables); (body of function code); } /* Define main function*/ main ((optional argc and argv arguments)) (optional declaration parameters) { (declaration of local variables); (body of main function code); } Comments Format: /*(body of comment) */ Example: /*This is a comment in C*/ Constant Declarations Format: #define(constant name)(constant value) Example: #define MAXIMUM 1000 Type Definitions Format: typedef(datatype)(symbolic name); Example: typedef int KILOGRAMS; Variables Declarations: Format: (variable type)(name 1)(name 2),...; Example: int firstnum, secondnum; char alpha; int firstarray[10]; int doublearray[2][5]; char firststring[1O]; Initializing: Format: (variable type)(name)=(value); Example: int firstnum=5; Assignments: Format: (name)=(value); Example: firstnum=5; Alpha='a'; Unions Declarations: Format: union(tag) {(type)(member name); (type)(member name); ... }(variable name); Example: union demotagname {int a; float b; }demovarname; Assignment: Format: (tag).(member name)=(value); demovarname.a=1; demovarname.b=4.6; Structures Declarations: Format: struct(tag) {(type)(variable); (type)(variable); ... }(variable list); Example: struct student {int -
A Tutorial Introduction to the Language B
A TUTORIAL INTRODUCTION TO THE LANGUAGE B B. W. Kernighan Bell Laboratories Murray Hill, New Jersey 1. Introduction B is a new computer language designed and implemented at Murray Hill. It runs and is actively supported and documented on the H6070 TSS system at Murray Hill. B is particularly suited for non-numeric computations, typified by system programming. These usually involve many complex logical decisions, computations on integers and fields of words, especially charac- ters and bit strings, and no floating point. B programs for such operations are substantially easier to write and understand than GMAP programs. The generated code is quite good. Implementation of simple TSS subsystems is an especially good use for B. B is reminiscent of BCPL [2] , for those who can remember. The original design and implementation are the work of K. L. Thompson and D. M. Ritchie; their original 6070 version has been substantially improved by S. C. Johnson, who also wrote the runtime library. This memo is a tutorial to make learning B as painless as possible. Most of the features of the language are mentioned in passing, but only the most important are stressed. Users who would like the full story should consult A User’s Reference to B on MH-TSS, by S. C. Johnson [1], which should be read for details any- way. We will assume that the user is familiar with the mysteries of TSS, such as creating files, text editing, and the like, and has programmed in some language before. Throughout, the symbolism (->n) implies that a topic will be expanded upon in section n of this manual. -
Knowledge Management Enviroments for High Throughput Biology
Knowledge Management Enviroments for High Throughput Biology Abhey Shah A Thesis submitted for the degree of MPhil Biology Department University of York September 2007 Abstract With the growing complexity and scale of data sets in computational biology and chemoin- formatics, there is a need for novel knowledge processing tools and platforms. This thesis describes a newly developed knowledge processing platform that is different in its emphasis on architecture, flexibility, builtin facilities for datamining and easy cross platform usage. There exist thousands of bioinformatics and chemoinformatics databases, that are stored in many different forms with different access methods, this is a reflection of the range of data structures that make up complex biological and chemical data. Starting from a theoretical ba- sis, FCA (Formal Concept Analysis) an applied branch of lattice theory, is used in this thesis to develop a file system that automatically structures itself by it’s contents. The procedure of extracting concepts from data sets is examined. The system also finds appropriate labels for the discovered concepts by extracting data from ontological databases. A novel method for scaling non-binary data for use with the system is developed. Finally the future of integrative systems biology is discussed in the context of efficiently closed causal systems. Contents 1 Motivations and goals of the thesis 11 1.1 Conceptual frameworks . 11 1.2 Biological foundations . 12 1.2.1 Gene expression data . 13 1.2.2 Ontology . 14 1.3 Knowledge based computational environments . 15 1.3.1 Interfaces . 16 1.3.2 Databases and the character of biological data . -
Quick Tips and Tricks: Perl Regular Expressions in SAS® Pratap S
Paper 4005-2019 Quick Tips and Tricks: Perl Regular Expressions in SAS® Pratap S. Kunwar, Jinson Erinjeri, Emmes Corporation. ABSTRACT Programming with text strings or patterns in SAS® can be complicated without the knowledge of Perl regular expressions. Just knowing the basics of regular expressions (PRX functions) will sharpen anyone's programming skills. Having attended a few SAS conferences lately, we have noticed that there are few presentations on this topic and many programmers tend to avoid learning and applying the regular expressions. Also, many of them are not aware of the capabilities of these functions in SAS. In this presentation, we present quick tips on these expressions with various applications which will enable anyone learn this topic with ease. INTRODUCTION SAS has numerous character (string) functions which are very useful in manipulating character fields. Every SAS programmer is generally familiar with basic character functions such as SUBSTR, SCAN, STRIP, INDEX, UPCASE, LOWCASE, CAT, ANY, NOT, COMPARE, COMPBL, COMPRESS, FIND, TRANSLATE, TRANWRD etc. Though these common functions are very handy for simple string manipulations, they are not built for complex pattern matching and search-and-replace operations. Regular expressions (RegEx) are both flexible and powerful and are widely used in popular programming languages such as Perl, Python, JavaScript, PHP, .NET and many more for pattern matching and translating character strings. Regular expressions skills can be easily ported to other languages like SQL., However, unlike SQL, RegEx itself is not a programming language, but simply defines a search pattern that describes text. Learning regular expressions starts with understanding of character classes and metacharacters. -
Squinting at Power Series
Squinting at Power Series M. Douglas McIlroy AT&T Bell Laboratories Murray Hill, New Jersey 07974 ABSTRACT Data streams are an ideal vehicle for handling power series. Stream implementations can be read off directly from simple recursive equations that de®ne operations such as multiplication, substitution, exponentiation, and reversion of series. The bookkeeping that bedevils these algorithms when they are expressed in traditional languages is completely hidden when they are expressed in stream terms. Communicating processes are the key to the simplicity of the algorithms. Working versions are presented in newsqueak, the language of Pike's ``squint'' system; their effectiveness depends critically on the stream protocol. Series and streams Power series are natural objects for stream processing. Pertinent computations are neatly describable by recursive equations. CSP (communicating sequential process) languages1, 2 are good vehicles for implementation. This paper develops the algorithmic ideas and reduces them to practice in a working CSP language,3 not coincidentally illustrating the utility of concurrent programming notions in untangling the logic of some intricate computations on sequences. This elegant approach to power series computation, ®rst demonstrated but never published by Kahn and MacQueen as an application of their data stream system, is still little known.4 Power series are represented as streams of coef®cients, the exponents being given implicitly by ordinal position. (This is an in®nite analogue of the familiar representation of a polynomial as an array of coef®cients.) Thus the power series for the exponential function ∞ 1 1 1 e x = Σ x n / n! = 1 + x + __ x 2 + __ x 3 + ___ x 4 + . -
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.