Programming Paradigms
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Programming Paradigms & Object-Oriented
4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Syllabus Content: 4.3.1 Programming paradigms Show understanding of what is meant by a programming paradigm Show understanding of the characteristics of a number of programming paradigms (low- level, imperative (procedural), object-oriented, declarative) – low-level programming Demonstrate an ability to write low-level code that uses various address modes: o immediate, direct, indirect, indexed and relative (see Section 1.4.3 and Section 3.6.2) o imperative programming- see details in Section 2.3 (procedural programming) Object-oriented programming (OOP) o demonstrate an ability to solve a problem by designing appropriate classes o demonstrate an ability to write code that demonstrates the use of classes, inheritance, polymorphism and containment (aggregation) declarative programming o demonstrate an ability to solve a problem by writing appropriate facts and rules based on supplied information o demonstrate an ability to write code that can satisfy a goal using facts and rules Programming paradigms 1 4.3 (Programming Paradigms & Object-Oriented- Computer Science 9608 Programming) with Majid Tahir Programming paradigm: A programming paradigm is a set of programming concepts and is a fundamental style of programming. Each paradigm will support a different way of thinking and problem solving. Paradigms are supported by programming language features. Some programming languages support more than one paradigm. There are many different paradigms, not all mutually exclusive. Here are just a few different paradigms. Low-level programming paradigm The features of Low-level programming languages give us the ability to manipulate the contents of memory addresses and registers directly and exploit the architecture of a given processor. -
Bioconductor: Open Software Development for Computational Biology and Bioinformatics Robert C
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Collection Of Biostatistics Research Archive Bioconductor Project Bioconductor Project Working Papers Year 2004 Paper 1 Bioconductor: Open software development for computational biology and bioinformatics Robert C. Gentleman, Department of Biostatistical Sciences, Dana Farber Can- cer Institute Vincent J. Carey, Channing Laboratory, Brigham and Women’s Hospital Douglas J. Bates, Department of Statistics, University of Wisconsin, Madison Benjamin M. Bolstad, Division of Biostatistics, University of California, Berkeley Marcel Dettling, Seminar for Statistics, ETH, Zurich, CH Sandrine Dudoit, Division of Biostatistics, University of California, Berkeley Byron Ellis, Department of Statistics, Harvard University Laurent Gautier, Center for Biological Sequence Analysis, Technical University of Denmark, DK Yongchao Ge, Department of Biomathematical Sciences, Mount Sinai School of Medicine Jeff Gentry, Department of Biostatistical Sciences, Dana Farber Cancer Institute Kurt Hornik, Computational Statistics Group, Department of Statistics and Math- ematics, Wirtschaftsuniversitat¨ Wien, AT Torsten Hothorn, Institut fuer Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universitat Erlangen-Nurnberg, DE Wolfgang Huber, Department for Molecular Genome Analysis (B050), German Cancer Research Center, Heidelberg, DE Stefano Iacus, Department of Economics, University of Milan, IT Rafael Irizarry, Department of Biostatistics, Johns Hopkins University Friedrich Leisch, Institut fur¨ Statistik und Wahrscheinlichkeitstheorie, Technische Universitat¨ Wien, AT Cheng Li, Department of Biostatistical Sciences, Dana Farber Cancer Institute Martin Maechler, Seminar for Statistics, ETH, Zurich, CH Anthony J. Rossini, Department of Medical Education and Biomedical Informat- ics, University of Washington Guenther Sawitzki, Statistisches Labor, Institut fuer Angewandte Mathematik, DE Colin Smith, Department of Molecular Biology, The Scripps Research Institute, San Diego Gordon K. -
Functional Languages
Functional Programming Languages (FPL) 1. Definitions................................................................... 2 2. Applications ................................................................ 2 3. Examples..................................................................... 3 4. FPL Characteristics:.................................................... 3 5. Lambda calculus (LC)................................................. 4 6. Functions in FPLs ....................................................... 7 7. Modern functional languages...................................... 9 8. Scheme overview...................................................... 11 8.1. Get your own Scheme from MIT...................... 11 8.2. General overview.............................................. 11 8.3. Data Typing ...................................................... 12 8.4. Comments ......................................................... 12 8.5. Recursion Instead of Iteration........................... 13 8.6. Evaluation ......................................................... 14 8.7. Storing and using Scheme code ........................ 14 8.8. Variables ........................................................... 15 8.9. Data types.......................................................... 16 8.10. Arithmetic functions ......................................... 17 8.11. Selection functions............................................ 18 8.12. Iteration............................................................. 23 8.13. Defining functions ........................................... -
PHP Programming Cookbook I
PHP Programming Cookbook i PHP Programming Cookbook PHP Programming Cookbook ii Contents 1 PHP Tutorial for Beginners 1 1.1 Introduction......................................................1 1.1.1 Where is PHP used?.............................................1 1.1.2 Why PHP?..................................................2 1.2 XAMPP Setup....................................................3 1.3 PHP Language Basics.................................................5 1.3.1 Escaping to PHP...............................................5 1.3.2 Commenting PHP..............................................5 1.3.3 Hello World..................................................6 1.3.4 Variables in PHP...............................................6 1.3.5 Conditional Statements in PHP........................................7 1.3.6 Loops in PHP.................................................8 1.4 PHP Arrays...................................................... 10 1.5 PHP Functions.................................................... 12 1.6 Connecting to a Database............................................... 14 1.6.1 Connecting to MySQL Databases...................................... 14 1.6.2 Connecting to MySQLi Databases (Procedurial).............................. 14 1.6.3 Connecting to MySQLi databases (Object-Oriented)............................ 15 1.6.4 Connecting to PDO Databases........................................ 15 1.7 PHP Form Handling................................................. 15 1.8 PHP Include & Require Statements......................................... -
Object-Oriented Programming Basics with Java
Object-Oriented Programming Object-Oriented Programming Basics With Java In his keynote address to the 11th World Computer Congress in 1989, renowned computer scientist Donald Knuth said that one of the most important lessons he had learned from his years of experience is that software is hard to write! Computer scientists have struggled for decades to design new languages and techniques for writing software. Unfortunately, experience has shown that writing large systems is virtually impossible. Small programs seem to be no problem, but scaling to large systems with large programming teams can result in $100M projects that never work and are thrown out. The only solution seems to lie in writing small software units that communicate via well-defined interfaces and protocols like computer chips. The units must be small enough that one developer can understand them entirely and, perhaps most importantly, the units must be protected from interference by other units so that programmers can code the units in isolation. The object-oriented paradigm fits these guidelines as designers represent complete concepts or real world entities as objects with approved interfaces for use by other objects. Like the outer membrane of a biological cell, the interface hides the internal implementation of the object, thus, isolating the code from interference by other objects. For many tasks, object-oriented programming has proven to be a very successful paradigm. Interestingly, the first object-oriented language (called Simula, which had even more features than C++) was designed in the 1960's, but object-oriented programming has only come into fashion in the 1990's. -
Paradigms of Computer Programming
Paradigms of computer programming l This course aims to teach programming as a unified discipline that covers all programming languages l We cover the essential concepts and techniques in a uniform framework l Second-year university level: requires some programming experience and mathematics (sets, lists, functions) l The course covers four important themes: l Programming paradigms l Mathematical semantics of programming l Data abstraction l Concurrency l Let’s see how this works in practice Hundreds of programming languages are in use... So many, how can we understand them all? l Key insight: languages are based on paradigms, and there are many fewer paradigms than languages l We can understand many languages by learning few paradigms! What is a paradigm? l A programming paradigm is an approach to programming a computer based on a coherent set of principles or a mathematical theory l A program is written to solve problems l Any realistic program needs to solve different kinds of problems l Each kind of problem needs its own paradigm l So we need multiple paradigms and we need to combine them in the same program How can we study multiple paradigms? l How can we study multiple paradigms without studying multiple languages (since most languages only support one, or sometimes two paradigms)? l Each language has its own syntax, its own semantics, its own system, and its own quirks l We could pick three languages, like Java, Erlang, and Haskell, and structure our course around them l This would make the course complicated for no good reason -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Functional Programming Laboratory 1 Programming Paradigms
Intro 1 Functional Programming Laboratory C. Beeri 1 Programming Paradigms A programming paradigm is an approach to programming: what is a program, how are programs designed and written, and how are the goals of programs achieved by their execution. A paradigm is an idea in pure form; it is realized in a language by a set of constructs and by methodologies for using them. Languages sometimes combine several paradigms. The notion of paradigm provides a useful guide to understanding programming languages. The imperative paradigm underlies languages such as Pascal and C. The object-oriented paradigm is embodied in Smalltalk, C++ and Java. These are probably the paradigms known to the students taking this lab. We introduce functional programming by comparing it to them. 1.1 Imperative and object-oriented programming Imperative programming is based on a simple construct: A cell is a container of data, whose contents can be changed. A cell is an abstraction of a memory location. It can store data, such as integers or real numbers, or addresses of other cells. The abstraction hides the size bounds that apply to real memory, as well as the physical address space details. The variables of Pascal and C denote cells. The programming construct that allows to change the contents of a cell is assignment. In the imperative paradigm a program has, at each point of its execution, a state represented by a collection of cells and their contents. This state changes as the program executes; assignment statements change the contents of cells, other statements create and destroy cells. Yet others, such as conditional and loop statements allow the programmer to direct the control flow of the program. -
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 -
ALGORITHMS for ARTIFICIAL INTELLIGENCE in Apl2 By
MAY 1986 REVISED Nov 1986 TR 03·281 ALGORITHMS FOR ARTIFICIAL INTELLIGENCE IN APl2 By DR JAMES A· BROWN ED EUSEBI JANICE COOK lEO H GRONER INTERNATIONAL BUSINESS MACHINES CORPORATION GENERAL PRODUCTS DIVISION SANTA TERESA LABORATORY SAN JOSE~ CALIFORNIA ABSTRACT Many great advances in science and mathematics were preceded by notational improvements. While a g1yen algorithm can be implemented in any general purpose programming language, discovery of algorithms is heavily influenced by the notation used to Lnve s t Lq a t.e them. APL2 c o nce p t.ua Lly applies f unc t Lons in parallel to arrays of data and so is a natural notation in which to investigate' parallel algorithins. No c LaLm is made that APL2 1s an advance in notation that will precede a breakthrough in Artificial Intelligence but it 1s a new notation that allows a new view of the pr-obl.ems in AI and their solutions. APL2 can be used ill problems tractitionally programmed in LISP, and is a possible implementation language for PROLOG-like languages. This paper introduces a subset of the APL2 notation and explores how it can be applied to Artificial Intelligence. 111 CONTENTS Introduction. • • • • • • • • • • 1 Part 1: Artificial Intelligence. • • • 2 Part 2: Logic... · • 8 Part 3: APL2 ..... · 22 Part 4: The Implementations . · .40 Part 5: Going Beyond the Fundamentals .. • 61 Summary. .74 Conclus i ons , . · .75 Acknowledgements. • • 76 References. · 77 Appendix 1 : Implementations of the Algorithms.. 79 Appendix 2 : Glossary. • • • • • • • • • • • • • • • • 89 Appendix 3 : A Summary of Predicate Calculus. · 95 Appendix 4 : Tautologies. · 97 Appendix 5 : The DPY Function. -
Functional and Imperative Object-Oriented Programming in Theory and Practice
Uppsala universitet Inst. för informatik och media Functional and Imperative Object-Oriented Programming in Theory and Practice A Study of Online Discussions in the Programming Community Per Jernlund & Martin Stenberg Kurs: Examensarbete Nivå: C Termin: VT-19 Datum: 14-06-2019 Abstract Functional programming (FP) has progressively become more prevalent and techniques from the FP paradigm has been implemented in many different Imperative object-oriented programming (OOP) languages. However, there is no indication that OOP is going out of style. Nevertheless the increased popularity in FP has sparked new discussions across the Internet between the FP and OOP communities regarding a multitude of related aspects. These discussions could provide insights into the questions and challenges faced by programmers today. This thesis investigates these online discussions in a small and contemporary scale in order to identify the most discussed aspect of FP and OOP. Once identified the statements and claims made by various discussion participants were selected and compared to literature relating to the aspects and the theory behind the paradigms in order to determine whether there was any discrepancies between practitioners and theory. It was done in order to investigate whether the practitioners had different ideas in the form of best practices that could influence theories. The most discussed aspect within FP and OOP was immutability and state relating primarily to the aspects of concurrency and performance. This thesis presents a selection of representative quotes that illustrate the different points of view held by groups in the community and then addresses those claims by investigating what is said in literature. -
Functional Javascript
www.it-ebooks.info www.it-ebooks.info Functional JavaScript Michael Fogus www.it-ebooks.info Functional JavaScript by Michael Fogus Copyright © 2013 Michael Fogus. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://my.safaribooksonline.com). For more information, contact our corporate/ institutional sales department: 800-998-9938 or [email protected]. Editor: Mary Treseler Indexer: Judith McConville Production Editor: Melanie Yarbrough Cover Designer: Karen Montgomery Copyeditor: Jasmine Kwityn Interior Designer: David Futato Proofreader: Jilly Gagnon Illustrator: Robert Romano May 2013: First Edition Revision History for the First Edition: 2013-05-24: First release See http://oreilly.com/catalog/errata.csp?isbn=9781449360726 for release details. Nutshell Handbook, the Nutshell Handbook logo, and the O’Reilly logo are registered trademarks of O’Reilly Media, Inc. Functional JavaScript, the image of an eider duck, and related trade dress are trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O’Reilly Media, Inc., was aware of a trade‐ mark claim, the designations have been printed in caps or initial caps. While every precaution has been taken in the preparation of this book, the publisher and author assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.