Computer Languages

Total Page:16

File Type:pdf, Size:1020Kb

Computer Languages Computer Languages First Generation Machine language Binary code (0 and 1) Each type of CPU has its own unique machine language (i.e., its "instruction set") Addition = 0111 Subtraction = 0110 Input = 0001 Output = 1110 Halt = 1111 Address Op code Operands 0001 0001 01100100 1010 0010 0001 11001000 1011 0011 0100 1010 0001 0100 0100 1011 0010 0101 0111 0110 0011 1100 0111 1110 1100 1000 1111 1001 1010 01100100 1011 11001000 1100 Second Generation Assembly language Short abbreviations for binary instructions: ADD SUB MPY DIV Program source code must be translated into binary machine code (also known as object code) Translation software is called an assembler Address Op code Operands M1 INP 100,M10 M2 INP 200,M11 M3 MMR M10,REG1 M4 MMR M11,REG2 M5 ADD M6 MAM M12 M7 OUT M12 M8 HLT M9 M10 100 M11 200 M12 Address Op code Operands M1 INP 100,M10 M2 INP 200,M11 M3 MMR M10,REG1 M4 MMR M11,REG2 M5 ADD M6 MAM M12 M7 OUT M12 M8 HLT M9 M10 100 M11 200 M12 Address Op code Operands 0001 0001 01100100 1010 0010 0001 11001000 1011 0011 0100 1010 0001 0100 0100 1011 0010 0101 0111 0110 0011 1100 0111 1110 1100 1000 1111 1001 1010 01100100 1011 11001000 1100 Third Generation Higher level than assembly language Not as detailed More abstract Program source code must be translated into binary machine code Two types of translation software: Compiler Interpreter A = 100 B = 200 C = A+B DISPLAY C Address Op code Operands 0001 0001 01100100 1010 0010 0001 11001000 1011 0011 0100 1010 0001 0100 0100 1011 0010 0101 0111 0110 0011 1100 0111 1110 1100 1000 1111 1001 1010 01100100 1011 11001000 1100 ASSIGN 100 TO A ASSIGN 200 TO B ADD A TO B GIVING C DISPLAY C Address Op code Operands 0001 0001 01100100 1010 0010 0001 11001000 1011 0011 0100 1010 0001 0100 0100 1011 0010 0101 0111 0110 0011 1100 0111 1110 1100 1000 1111 1001 1010 01100100 1011 11001000 1100 Address Op code Operands 0001 0001 01100100 1010 0010 0001 11001000 1011 0011 0100 1010 0001 A = 100 0100 0100 1011 0010 0101 0111 B = 200 0110 0011 1100 0111 1110 1100 C = A+B 1000 1111 1001 DISPLAY C 1010 01100100 1011 11001000 1100 Address Op code Operands 0001 1000 01100100 1010 0010 1000 11001000 1011 0011 0101 1010 0001 0100 0101 1011 0010 0101 1111 0110 0111 1100 0111 1100 1100 1000 1110 1001 1010 01100100 1011 11001000 1100 Examples FORTRAN Invented in 1954 Math, science, engineering, statistics Pi, e, imaginary numbers, trigonometry functions COBOL Invented in 1959 Business data processing on large mainframe computers Payroll, banking, billing, inventory management, census English commands: ADD A TO B GIVING C Examples BASIC Invented in 1963 Educational language (at first) Copied by many hardware and software companies The first interpreter language Instructions translated to machine code one-at-a-time in real time Many others C ALGOL PL/1, APL, SPSS, SAS, WATFOR, GPSS, RPG II, PASCAL, ADA, Modula-2, LISP, PROLOG, FORTH, LOGO Fourth Generation Data base languages SQL Visual languages Visual Basic Visual Age Object-oriented languages C++ C# Java Smalltalk Fourth Generation Rapid Application Development (RAD) Computer Assisted Software Engineering (CASE) Examples: Delphi Power Builder Automatic Program Generator Internet Languages Client-side processing HTML Javascript VB Script Cascading Style Sheets (CSS) eXtensible Markup Language (XML) Server-side processing Perl Python Rexx Ruby Mobile App Languages Objective C Objective Pascal C++ C# Java Visual Basic HTML5 Others Who invents computer languages? Hardware companies IBM developed FORTRAN in 1954 IBM developed PL/1, RPG II, APL, GPSS, SQL, etc. in the 60's and 70's AT&T Bell Labs developed C Sun Microsystems invented Java Who invents computer languages? Software companies Microsoft developed GWBASIC, QBASIC, QuickBASIC, Visual Basic, Visual Basic for Applications (VBA), Visual Basic .NET, J++, and C# Netscape invented JavaScript Borland developed Delphi Sybase developed PowerBuilder Who invents computer languages? Universities BASIC was developed at Dartmouth University in 1963 LISP and LOGO were developed at M.I.T. WATFOR was developed at the University of Waterloo (Canada) Who invents computer languages? Governments/standards organizations COBOL was developed by the U.S. Department of Defense in 1959 ALGOL was developed by a consortium of European governments in the 1960's ADA was developed by the U.S. Government in the late 70's Who invents computer languages? Individuals Bjarne Stroustrup invented C++ (while working at AT&T Bell Labs) Charles Moore invented FORTH. Nicklaus Wirth invented PASCAL, Modula-2, and other languages Larry Wall invented Perl Jim Guerber invented InernetBasic Brad Cox and Tom Love invented Objective C The future… What types of programmable devices will we have? Meta programming Natural language programming .
Recommended publications
  • Compilers & Translator Writing Systems
    Compilers & Translators Compilers & Translator Writing Systems Prof. R. Eigenmann ECE573, Fall 2005 http://www.ece.purdue.edu/~eigenman/ECE573 ECE573, Fall 2005 1 Compilers are Translators Fortran Machine code C Virtual machine code C++ Transformed source code Java translate Augmented source Text processing language code Low-level commands Command Language Semantic components Natural language ECE573, Fall 2005 2 ECE573, Fall 2005, R. Eigenmann 1 Compilers & Translators Compilers are Increasingly Important Specification languages Increasingly high level user interfaces for ↑ specifying a computer problem/solution High-level languages ↑ Assembly languages The compiler is the translator between these two diverging ends Non-pipelined processors Pipelined processors Increasingly complex machines Speculative processors Worldwide “Grid” ECE573, Fall 2005 3 Assembly code and Assemblers assembly machine Compiler code Assembler code Assemblers are often used at the compiler back-end. Assemblers are low-level translators. They are machine-specific, and perform mostly 1:1 translation between mnemonics and machine code, except: – symbolic names for storage locations • program locations (branch, subroutine calls) • variable names – macros ECE573, Fall 2005 4 ECE573, Fall 2005, R. Eigenmann 2 Compilers & Translators Interpreters “Execute” the source language directly. Interpreters directly produce the result of a computation, whereas compilers produce executable code that can produce this result. Each language construct executes by invoking a subroutine of the interpreter, rather than a machine instruction. Examples of interpreters? ECE573, Fall 2005 5 Properties of Interpreters “execution” is immediate elaborate error checking is possible bookkeeping is possible. E.g. for garbage collection can change program on-the-fly. E.g., switch libraries, dynamic change of data types machine independence.
    [Show full text]
  • Application Program Interface Guide
    APPLICATION PROGRAM INTERFACE GUIDE VWS-2001, VWS-2002 V WS-2001 V WS-2002 API GUIDE 24/7 TECHNICAL SUPPORT AT 1.877.877.2269 OR VISIT BLACKBOX.COM RemoteRemote Command Command Line Line Status Configure Status Client connected Enabled Monitor Client authorized Settings… Client disconnected Client authorized “C:\Program Files (x86)\Wall Control\wallctl.exe”- Active Server Telnet Command Lin — — — OK Cancel Apply Help NEED HELP? LEAVE THE TECH TO US LIVE 24/7 TABLE OF CONTENTS TECHNICAL SUPPORT 1.877.877.2269 1. INTRODUCTION ............................................................................................................................................................................. 3 1.1 API Programs ................................................................................................................................................................................................................3 1.2 Nomenclature ...............................................................................................................................................................................................................3 2. LAYOUTS ........................................................................................................................................................................................ 4 2.1 Example Usage ............................................................................................................................................................................................................4
    [Show full text]
  • Chapter 2 Basics of Scanning And
    Chapter 2 Basics of Scanning and Conventional Programming in Java In this chapter, we will introduce you to an initial set of Java features, the equivalent of which you should have seen in your CS-1 class; the separation of problem, representation, algorithm and program – four concepts you have probably seen in your CS-1 class; style rules with which you are probably familiar, and scanning - a general class of problems we see in both computer science and other fields. Each chapter is associated with an animating recorded PowerPoint presentation and a YouTube video created from the presentation. It is meant to be a transcript of the associated presentation that contains little graphics and thus can be read even on a small device. You should refer to the associated material if you feel the need for a different instruction medium. Also associated with each chapter is hyperlinked code examples presented here. References to previously presented code modules are links that can be traversed to remind you of the details. The resources for this chapter are: PowerPoint Presentation YouTube Video Code Examples Algorithms and Representation Four concepts we explicitly or implicitly encounter while programming are problems, representations, algorithms and programs. Programs, of course, are instructions executed by the computer. Problems are what we try to solve when we write programs. Usually we do not go directly from problems to programs. Two intermediate steps are creating algorithms and identifying representations. Algorithms are sequences of steps to solve problems. So are programs. Thus, all programs are algorithms but the reverse is not true.
    [Show full text]
  • 13-DUALOSS-MV Commercial Grade In-Wall Occupancy/Vacancy Sensor
    13-DUALOSS-MV Commercial Grade In-Wall Occupancy/Vacancy Sensor APPLICATIONS This Multi-Technology Wall Switch Sensor combine advanced passive infrared (PIR) and ultrasonic technologies into one unit. The combined technologies helps eliminate false triggering even in difficult applications. Selectable operating modes allow the sensor to turn a load on, and hold it on as long as either or both technologies detect occupancy . After no movement is detected for the selected time delay, the lights switch off. A "walk-through" mode can turn lights off after only 3 minutes, if no activity is detected after 30 seconds following an occupancy detection. This sensor also contains a light level sensor. If adequate daylight is present, the sensor holds the load OFF until light levels drop, even if the area is occupied. MODEL #: 13-DUALOSS-MV FEATURES • Integrated PIR and Ultrasonic sensor technology to detect very fine COVERAGE AREA motion and provide accurate motion sensing Top View • Allows to choose triggering when both technologies detect motion or when only PIR detects motion 20' • Less false trigger, fast ON/OFF; commercial grade sensor for closet, garage, hotels, meeting room, work places 10' • Adjustable timeout from 15 seconds to 30 minutes; Walk-Through mode: 3 minutes if no activity after first 30 seconds SPECIFICATIONS 10' • Voltage: 120/277VAC, 50/60Hz • Incandescent: 800W-120VAC, 50/60Hz • Fluorescent: 800VA-120VAC, 1600VA-277VAC, 50/60Hz 20' • Resistive: 800W-120VAC, 50/60Hz • Motor: 1/4 HP-120VAC, 50/60Hz • Adjustment Time Delay: 5 Sec to 30 Mins 5' • Walk-Through Mode: 3-minutes if no activity after 30 sec.
    [Show full text]
  • Scripting: Higher- Level Programming for the 21St Century
    . John K. Ousterhout Sun Microsystems Laboratories Scripting: Higher- Cybersquare Level Programming for the 21st Century Increases in computer speed and changes in the application mix are making scripting languages more and more important for the applications of the future. Scripting languages differ from system programming languages in that they are designed for “gluing” applications together. They use typeless approaches to achieve a higher level of programming and more rapid application development than system programming languages. or the past 15 years, a fundamental change has been ated with system programming languages and glued Foccurring in the way people write computer programs. together with scripting languages. However, several The change is a transition from system programming recent trends, such as faster machines, better script- languages such as C or C++ to scripting languages such ing languages, the increasing importance of graphical as Perl or Tcl. Although many people are participat- user interfaces (GUIs) and component architectures, ing in the change, few realize that the change is occur- and the growth of the Internet, have greatly expanded ring and even fewer know why it is happening. This the applicability of scripting languages. These trends article explains why scripting languages will handle will continue over the next decade, with more and many of the programming tasks in the next century more new applications written entirely in scripting better than system programming languages. languages and system programming
    [Show full text]
  • PS TEXT EDIT Reference Manual Is Designed to Give You a Complete Is About Overview of TEDIT
    Information Management Technology Library PS TEXT EDIT™ Reference Manual Abstract This manual describes PS TEXT EDIT, a multi-screen block mode text editor. It provides a complete overview of the product and instructions for using each command. Part Number 058059 Tandem Computers Incorporated Document History Edition Part Number Product Version OS Version Date First Edition 82550 A00 TEDIT B20 GUARDIAN 90 B20 October 1985 (Preliminary) Second Edition 82550 B00 TEDIT B30 GUARDIAN 90 B30 April 1986 Update 1 82242 TEDIT C00 GUARDIAN 90 C00 November 1987 Third Edition 058059 TEDIT C00 GUARDIAN 90 C00 July 1991 Note The second edition of this manual was reformatted in July 1991; no changes were made to the manual’s content at that time. New editions incorporate any updates issued since the previous edition. Copyright All rights reserved. No part of this document may be reproduced in any form, including photocopying or translation to another language, without the prior written consent of Tandem Computers Incorporated. Copyright 1991 Tandem Computers Incorporated. Contents What This Book Is About xvii Who Should Use This Book xvii How to Use This Book xvii Where to Go for More Information xix What’s New in This Update xx Section 1 Introduction to TEDIT What Is PS TEXT EDIT? 1-1 TEDIT Features 1-1 TEDIT Commands 1-2 Using TEDIT Commands 1-3 Terminals and TEDIT 1-3 Starting TEDIT 1-4 Section 2 TEDIT Topics Overview 2-1 Understanding Syntax 2-2 Note About the Examples in This Book 2-3 BALANCED-EXPRESSION 2-5 CHARACTER 2-9 058059 Tandem Computers
    [Show full text]
  • Unix for Newbies from Duane A
    Content borrowed and updated (with permission) Unix for Newbies from Duane A. Bailey’s guidelines from 2007. Getting help on unix: Some Tips To Make Your UNIX Life More Reasonable man <command-name>!!Get full description of command man -k <keyword>!! ! List command mentioning keyword in title 0. Walk away from the machine. If you’re not making progress, don’t waste time banging your head (literally or Logging in and out of a system: figuratively) against the machine. Save your files, print the buggy output, or logout!!!!Terminate session create a backup and walk away. Find someone to talk to about something else. Your exit!!!!Terminate current “shell” mind will work on the problem while you go get a snack and take a break. ssh <username>@<remote host>!Login securely as username to remote host 1. Read man pages. File Manipulation: Realize that you don’t know everything. Take the time to learn how man pages are emacs <file>!!!Edit a text file (See the emacs cheatsheet) structured and what they can teach you. You find answers to many questions on the mv <old> <new>!!!Move or rename <old> file as <new> file internet, but you learn even more by finding and reading the man pages. Better, rm <file(s)>!!!Delete file(s) from filesystem you learn elegant solutions to questions you didn’t think to ask. cp <orig> <duplicate>!!Copy <orig> to file named <duplicate> sftp <remote host>!!Secure batch file transfers between machines 2. Learn the emacs keystrokes. scp host:<orig> host:<dub>!Securely transfer files between machines It will save you time when you work on a machine whose mouse or arrow keys aren’t cat <file>!!!Display or catenate file contents to screen working, and the keystrokes often work in other editors.
    [Show full text]
  • The Future of DNA Data Storage the Future of DNA Data Storage
    The Future of DNA Data Storage The Future of DNA Data Storage September 2018 A POTOMAC INSTITUTE FOR POLICY STUDIES REPORT AC INST M IT O U T B T The Future O E P F O G S R IE of DNA P D O U Data LICY ST Storage September 2018 NOTICE: This report is a product of the Potomac Institute for Policy Studies. The conclusions of this report are our own, and do not necessarily represent the views of our sponsors or participants. Many thanks to the Potomac Institute staff and experts who reviewed and provided comments on this report. © 2018 Potomac Institute for Policy Studies Cover image: Alex Taliesen POTOMAC INSTITUTE FOR POLICY STUDIES 901 North Stuart St., Suite 1200 | Arlington, VA 22203 | 703-525-0770 | www.potomacinstitute.org CONTENTS EXECUTIVE SUMMARY 4 Findings 5 BACKGROUND 7 Data Storage Crisis 7 DNA as a Data Storage Medium 9 Advantages 10 History 11 CURRENT STATE OF DNA DATA STORAGE 13 Technology of DNA Data Storage 13 Writing Data to DNA 13 Reading Data from DNA 18 Key Players in DNA Data Storage 20 Academia 20 Research Consortium 21 Industry 21 Start-ups 21 Government 22 FORECAST OF DNA DATA STORAGE 23 DNA Synthesis Cost Forecast 23 Forecast for DNA Data Storage Tech Advancement 28 Increasing Data Storage Density in DNA 29 Advanced Coding Schemes 29 DNA Sequencing Methods 30 DNA Data Retrieval 31 CONCLUSIONS 32 ENDNOTES 33 Executive Summary The demand for digital data storage is currently has been developed to support applications in outpacing the world’s storage capabilities, and the life sciences industry and not for data storage the gap is widening as the amount of digital purposes.
    [Show full text]
  • How Do You Know Your Search Algorithm and Code Are Correct?
    Proceedings of the Seventh Annual Symposium on Combinatorial Search (SoCS 2014) How Do You Know Your Search Algorithm and Code Are Correct? Richard E. Korf Computer Science Department University of California, Los Angeles Los Angeles, CA 90095 [email protected] Abstract Is a Given Solution Correct? Algorithm design and implementation are notoriously The first question to ask of a search algorithm is whether the error-prone. As researchers, it is incumbent upon us to candidate solutions it returns are valid solutions. The algo- maximize the probability that our algorithms, their im- rithm should output each solution, and a separate program plementations, and the results we report are correct. In should check its correctness. For any problem in NP, check- this position paper, I argue that the main technique for ing candidate solutions can be done in polynomial time. doing this is confirmation of results from multiple in- dependent sources, and provide a number of concrete Is a Given Solution Optimal? suggestions for how to achieve this in the context of combinatorial search algorithms. Next we consider whether the solutions returned are opti- mal. In most cases, there are multiple very different algo- rithms that compute optimal solutions, starting with sim- Introduction and Overview ple brute-force algorithms, and progressing through increas- Combinatorial search results can be theoretical or experi- ingly complex and more efficient algorithms. Thus, one can mental. Theoretical results often consist of correctness, com- compare the solution costs returned by the different algo- pleteness, the quality of solutions returned, and asymptotic rithms, which should all be the same.
    [Show full text]
  • NAPCS Product List for NAICS 5112, 518 and 54151: Software
    NAPCS Product List for NAICS 5112, 518 and 54151: Software Publishers, Internet Service Providers, Web Search Portals, and Data Processing Services, and Computer Systems Design and Related Services 1 2 3 456 7 8 9 National Product United States Industry Working Tri- Detail Subject Group lateral NAICS Industries Area Code Detail Can Méx US Title Definition Producing the Product 5112 1.1 X Information Providing advice or expert opinion on technical matters related to the use of information technology. 511210 518111 518 technology (IT) 518210 54151 54151 technical consulting Includes: 54161 services • advice on matters such as hardware and software requirements and procurement, systems integration, and systems security. • providing expert testimony on IT related issues. Excludes: • advice on issues related to business strategy, such as advising on developing an e-commerce strategy, is in product 2.3, Strategic management consulting services. • advice bundled with the design and development of an IT solution (web site, database, specific application, network, etc.) is in the products under 1.2, Information technology (IT) design and development services. 5112 1.2 Information Providing technical expertise to design and/or develop an IT solution such as custom applications, 511210 518111 518 technology (IT) networks, and computer systems. 518210 54151 54151 design and development services 5112 1.2.1 Custom software Designing the structure and/or writing the computer code necessary to create and/or implement a 511210 518111 518 application design software application. 518210 54151 54151 and development services 5112 1.2.1.1 X Web site design and Designing the structure and content of a web page and/or of writing the computer code necessary to 511210 518111 518 development services create and implement a web page.
    [Show full text]
  • Media Theory and Semiotics: Key Terms and Concepts Binary
    Media Theory and Semiotics: Key Terms and Concepts Binary structures and semiotic square of oppositions Many systems of meaning are based on binary structures (masculine/ feminine; black/white; natural/artificial), two contrary conceptual categories that also entail or presuppose each other. Semiotic interpretation involves exposing the culturally arbitrary nature of this binary opposition and describing the deeper consequences of this structure throughout a culture. On the semiotic square and logical square of oppositions. Code A code is a learned rule for linking signs to their meanings. The term is used in various ways in media studies and semiotics. In communication studies, a message is often described as being "encoded" from the sender and then "decoded" by the receiver. The encoding process works on multiple levels. For semiotics, a code is the framework, a learned a shared conceptual connection at work in all uses of signs (language, visual). An easy example is seeing the kinds and levels of language use in anyone's language group. "English" is a convenient fiction for all the kinds of actual versions of the language. We have formal, edited, written English (which no one speaks), colloquial, everyday, regional English (regions in the US, UK, and around the world); social contexts for styles and specialized vocabularies (work, office, sports, home); ethnic group usage hybrids, and various kinds of slang (in-group, class-based, group-based, etc.). Moving among all these is called "code-switching." We know what they mean if we belong to the learned, rule-governed, shared-code group using one of these kinds and styles of language.
    [Show full text]
  • The Intercal Programming Language Revised Reference Manual
    THE INTERCAL PROGRAMMING LANGUAGE REVISED REFERENCE MANUAL Donald R. Woods and James M. Lyon C-INTERCAL revisions: Louis Howell and Eric S. Raymond Copyright (C) 1973 by Donald R. Woods and James M. Lyon Copyright (C) 1996 by Eric S. Raymond Redistribution encouragedunder GPL (This version distributed with C-INTERCAL 0.15) -1- 1. INTRODUCTION The names you are about to ignore are true. However, the story has been changed significantly.Any resemblance of the programming language portrayed here to other programming languages, living or dead, is purely coincidental. 1.1 Origin and Purpose The INTERCAL programming language was designed the morning of May 26, 1972 by Donald R. Woods and James M. Lyon, at Princeton University.Exactly when in the morning will become apparent in the course of this manual. Eighteen years later (give ortakeafew months) Eric S. Raymond perpetrated a UNIX-hosted INTERCAL compiler as a weekend hack. The C-INTERCAL implementation has since been maintained and extended by an international community of technomasochists, including Louis Howell, Steve Swales, Michael Ernst, and Brian Raiter. (There was evidently an Atari implementation sometime between these two; notes on it got appended to the INTERCAL-72 manual. The culprits have sensibly declined to identify themselves.) INTERCAL was inspired by one ambition: to have a compiler language which has nothing at all in common with anyother major language. By ’major’ was meant anything with which the authors were at all familiar,e.g., FORTRAN, BASIC, COBOL, ALGOL, SNOBOL, SPITBOL, FOCAL, SOLVE, TEACH, APL, LISP,and PL/I. For the most part, INTERCAL has remained true to this goal, sharing only the basic elements such as variables, arrays, and the ability to do I/O, and eschewing all conventional operations other than the assignment statement (FORTRAN "=").
    [Show full text]