Array Operators Using Multiple Dispatch: a Design Methodology for Array Implementations in Dynamic Languages
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Programming for Engineers Pointers in C Programming: Part 02
Programming For Engineers Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff1, Ahmad Fakhri Ab. Nasir2 Faculty of Manufacturing Engineering [email protected], [email protected] PFE – Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff and Ahmad Fakhri Ab. Nasir 0.0 Chapter’s Information • Expected Outcomes – To further use pointers in C programming • Contents 1.0 Pointer and Array 2.0 Pointer and String 3.0 Pointer and dynamic memory allocation PFE – Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff and Ahmad Fakhri Ab. Nasir 1.0 Pointer and Array • We will review array data type first and later we will relate array with pointer. • Previously, we learn about basic data types such as integer, character and floating numbers. In C programming language, if we have 5 test scores and would like to average the scores, we may code in the following way. PFE – Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff and Ahmad Fakhri Ab. Nasir 1.0 Pointer and Array PFE – Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff and Ahmad Fakhri Ab. Nasir 1.0 Pointer and Array • This program is manageable if the scores are only 5. What should we do if we have 100,000 scores? In such case, we need an efficient way to represent a collection of similar data type1. In C programming, we usually use array. • Array is a fixed-size sequence of elements of the same data type.1 • In C programming, we declare an array like the following statement: PFE – Pointers in C Programming: Part 02 by Wan Azhar Wan Yusoff and Ahmad Fakhri Ab. -
MANNING Greenwich (74° W
Object Oriented Perl Object Oriented Perl DAMIAN CONWAY MANNING Greenwich (74° w. long.) For electronic browsing and ordering of this and other Manning books, visit http://www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact: Special Sales Department Manning Publications Co. 32 Lafayette Place Fax: (203) 661-9018 Greenwich, CT 06830 email: [email protected] ©2000 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Library of Congress Cataloging-in-Publication Data Conway, Damian, 1964- Object oriented Perl / Damian Conway. p. cm. includes bibliographical references. ISBN 1-884777-79-1 (alk. paper) 1. Object-oriented programming (Computer science) 2. Perl (Computer program language) I. Title. QA76.64.C639 1999 005.13'3--dc21 99-27793 CIP Manning Publications Co. Copyeditor: Adrianne Harun 32 Lafayette -
Homework 2: Reflection and Multiple Dispatch in Smalltalk
Com S 541 — Programming Languages 1 October 2, 2002 Homework 2: Reflection and Multiple Dispatch in Smalltalk Due: Problems 1 and 2, September 24, 2002; problems 3 and 4, October 8, 2002. This homework can either be done individually or in teams. Its purpose is to familiarize you with Smalltalk’s reflection facilities and to help learn about other issues in OO language design. Don’t hesitate to contact the staff if you are not clear about what to do. In this homework, you will adapt the “multiple dispatch as dispatch on tuples” approach, origi- nated by Leavens and Millstein [1], to Smalltalk. To do this you will have to read their paper and then do the following. 1. (30 points) In a new category, Tuple-Smalltalk, add a class Tuple, which has indexed instance variables. Design this type to provide the necessary methods for working with dispatch on tuples, for example, we’d like to have access to the tuple of classes of the objects in a given tuple. Some of these methods will depend on what’s below. Also design methods so that tuples can be used as a data structure (e.g., to pass multiple arguments and return multiple results). 2. (50 points) In the category, Tuple-Smalltalk, design other classes to hold the behavior that will be declared for tuples. For example, you might want something analogous to a method dictionary and other things found in the class Behavior or ClassDescription. It’s worth studying those classes to see what can be adapted to our purposes. -
C Programming: Data Structures and Algorithms
C Programming: Data Structures and Algorithms An introduction to elementary programming concepts in C Jack Straub, Instructor Version 2.07 DRAFT C Programming: Data Structures and Algorithms, Version 2.07 DRAFT C Programming: Data Structures and Algorithms Version 2.07 DRAFT Copyright © 1996 through 2006 by Jack Straub ii 08/12/08 C Programming: Data Structures and Algorithms, Version 2.07 DRAFT Table of Contents COURSE OVERVIEW ........................................................................................ IX 1. BASICS.................................................................................................... 13 1.1 Objectives ...................................................................................................................................... 13 1.2 Typedef .......................................................................................................................................... 13 1.2.1 Typedef and Portability ............................................................................................................. 13 1.2.2 Typedef and Structures .............................................................................................................. 14 1.2.3 Typedef and Functions .............................................................................................................. 14 1.3 Pointers and Arrays ..................................................................................................................... 16 1.4 Dynamic Memory Allocation ..................................................................................................... -
Data Structure
EDUSAT LEARNING RESOURCE MATERIAL ON DATA STRUCTURE (For 3rd Semester CSE & IT) Contributors : 1. Er. Subhanga Kishore Das, Sr. Lect CSE 2. Mrs. Pranati Pattanaik, Lect CSE 3. Mrs. Swetalina Das, Lect CA 4. Mrs Manisha Rath, Lect CA 5. Er. Dillip Kumar Mishra, Lect 6. Ms. Supriti Mohapatra, Lect 7. Ms Soma Paikaray, Lect Copy Right DTE&T,Odisha Page 1 Data Structure (Syllabus) Semester & Branch: 3rd sem CSE/IT Teachers Assessment : 10 Marks Theory: 4 Periods per Week Class Test : 20 Marks Total Periods: 60 Periods per Semester End Semester Exam : 70 Marks Examination: 3 Hours TOTAL MARKS : 100 Marks Objective : The effectiveness of implementation of any application in computer mainly depends on the that how effectively its information can be stored in the computer. For this purpose various -structures are used. This paper will expose the students to various fundamentals structures arrays, stacks, queues, trees etc. It will also expose the students to some fundamental, I/0 manipulation techniques like sorting, searching etc 1.0 INTRODUCTION: 04 1.1 Explain Data, Information, data types 1.2 Define data structure & Explain different operations 1.3 Explain Abstract data types 1.4 Discuss Algorithm & its complexity 1.5 Explain Time, space tradeoff 2.0 STRING PROCESSING 03 2.1 Explain Basic Terminology, Storing Strings 2.2 State Character Data Type, 2.3 Discuss String Operations 3.0 ARRAYS 07 3.1 Give Introduction about array, 3.2 Discuss Linear arrays, representation of linear array In memory 3.3 Explain traversing linear arrays, inserting & deleting elements 3.4 Discuss multidimensional arrays, representation of two dimensional arrays in memory (row major order & column major order), and pointers 3.5 Explain sparse matrices. -
A Trusted Mechanised Javascript Specification
A Trusted Mechanised JavaScript Specification Martin Bodin Arthur Charguéraud Daniele Filaretti Inria & ENS Lyon Inria & LRI, Université Paris Sud, CNRS Imperial College London [email protected] [email protected] d.fi[email protected] Philippa Gardner Sergio Maffeis Daiva Naudžiunien¯ e˙ Imperial College London Imperial College London Imperial College London [email protected] sergio.maff[email protected] [email protected] Alan Schmitt Gareth Smith Inria Imperial College London [email protected] [email protected] Abstract sation was crucial. Client code that works on some of the main JavaScript is the most widely used web language for client-side ap- browsers, and not others, is not useful. The first official standard plications. Whilst the development of JavaScript was initially just appeared in 1997. Now we have ECMAScript 3 (ES3, 1999) and led by implementation, there is now increasing momentum behind ECMAScript 5 (ES5, 2009), supported by all browsers. There is the ECMA standardisation process. The time is ripe for a formal, increasing momentum behind the ECMA standardisation process, mechanised specification of JavaScript, to clarify ambiguities in the with plans for ES6 and 7 well under way. ECMA standards, to serve as a trusted reference for high-level lan- JavaScript is the only language supported natively by all major guage compilation and JavaScript implementations, and to provide web browsers. Programs written for the browser are either writ- a platform for high-assurance proofs of language properties. ten directly in JavaScript, or in other languages which compile to We present JSCert, a formalisation of the current ECMA stan- JavaScript. -
Programming the Capabilities of the PC Have Changed Greatly Since the Introduction of Electronic Computers
1 www.onlineeducation.bharatsevaksamaj.net www.bssskillmission.in INTRODUCTION TO PROGRAMMING LANGUAGE Topic Objective: At the end of this topic the student will be able to understand: History of Computer Programming C++ Definition/Overview: Overview: A personal computer (PC) is any general-purpose computer whose original sales price, size, and capabilities make it useful for individuals, and which is intended to be operated directly by an end user, with no intervening computer operator. Today a PC may be a desktop computer, a laptop computer or a tablet computer. The most common operating systems are Microsoft Windows, Mac OS X and Linux, while the most common microprocessors are x86-compatible CPUs, ARM architecture CPUs and PowerPC CPUs. Software applications for personal computers include word processing, spreadsheets, databases, games, and myriad of personal productivity and special-purpose software. Modern personal computers often have high-speed or dial-up connections to the Internet, allowing access to the World Wide Web and a wide range of other resources. Key Points: 1. History of ComputeWWW.BSSVE.INr Programming The capabilities of the PC have changed greatly since the introduction of electronic computers. By the early 1970s, people in academic or research institutions had the opportunity for single-person use of a computer system in interactive mode for extended durations, although these systems would still have been too expensive to be owned by a single person. The introduction of the microprocessor, a single chip with all the circuitry that formerly occupied large cabinets, led to the proliferation of personal computers after about 1975. Early personal computers - generally called microcomputers - were sold often in Electronic kit form and in limited volumes, and were of interest mostly to hobbyists and technicians. -
TAMING the MERGE OPERATOR a Type-Directed Operational Semantics Approach
Technical Report, Department of Computer Science, the University of Hong Kong, Jan 2021. 1 TAMING THE MERGE OPERATOR A Type-directed Operational Semantics Approach XUEJING HUANG JINXU ZHAO BRUNO C. D. S. OLIVEIRA The University of Hong Kong (e-mail: fxjhuang, jxzhao, [email protected]) Abstract Calculi with disjoint intersection types support a symmetric merge operator with subtyping. The merge operator generalizes record concatenation to any type, enabling expressive forms of object composition, and simple solutions to hard modularity problems. Unfortunately, recent calculi with disjoint intersection types and the merge operator lack a (direct) operational semantics with expected properties such as determinism and subject reduction, and only account for terminating programs. This paper proposes a type-directed operational semantics (TDOS) for calculi with intersection types and a merge operator. We study two variants of calculi in the literature. The first calculus, called li, is a variant of a calculus presented by Oliveira et al. (2016) and closely related to another calculus by Dunfield (2014). Although Dunfield proposes a direct small-step semantics for her calcu- lus, her semantics lacks both determinism and subject reduction. Using our TDOS we obtain a direct + semantics for li that has both properties. The second calculus, called li , employs the well-known + subtyping relation of Barendregt, Coppo and Dezani-Ciancaglini (BCD). Therefore, li extends the more basic subtyping relation of li, and also adds support for record types and nested composition (which enables recursive composition of merged components). To fully obtain determinism, both li + and li employ a disjointness restriction proposed in the original li calculus. -
BCL: a Cross-Platform Distributed Data Structures Library
BCL: A Cross-Platform Distributed Data Structures Library Benjamin Brock, Aydın Buluç, Katherine Yelick University of California, Berkeley Lawrence Berkeley National Laboratory {brock,abuluc,yelick}@cs.berkeley.edu ABSTRACT high-performance computing, including several using the Parti- One-sided communication is a useful paradigm for irregular paral- tioned Global Address Space (PGAS) model: Titanium, UPC, Coarray lel applications, but most one-sided programming environments, Fortran, X10, and Chapel [9, 11, 12, 25, 29, 30]. These languages are including MPI’s one-sided interface and PGAS programming lan- especially well-suited to problems that require asynchronous one- guages, lack application-level libraries to support these applica- sided communication, or communication that takes place without tions. We present the Berkeley Container Library, a set of generic, a matching receive operation or outside of a global collective. How- cross-platform, high-performance data structures for irregular ap- ever, PGAS languages lack the kind of high level libraries that exist plications, including queues, hash tables, Bloom filters and more. in other popular programming environments. For example, high- BCL is written in C++ using an internal DSL called the BCL Core performance scientific simulations written in MPI can leverage a that provides one-sided communication primitives such as remote broad set of numerical libraries for dense or sparse matrices, or get and remote put operations. The BCL Core has backends for for structured, unstructured, or adaptive meshes. PGAS languages MPI, OpenSHMEM, GASNet-EX, and UPC++, allowing BCL data can sometimes use those numerical libraries, but are missing the structures to be used natively in programs written using any of data structures that are important in some of the most irregular these programming environments. -
Julia: a Fresh Approach to Numerical Computing
RSDG @ UCL Julia: A Fresh Approach to Numerical Computing Mosè Giordano @giordano [email protected] Knowledge Quarter Codes Tech Social October 16, 2019 Julia’s Facts v1.0.0 released in 2018 at UCL • Development started in 2009 at MIT, first • public release in 2012 Julia co-creators won the 2019 James H. • Wilkinson Prize for Numerical Software Julia adoption is growing rapidly in • numerical optimisation, differential equations, machine learning, differentiable programming It is used and taught in several universities • (https://julialang.org/teaching/) Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 2 / 29 Julia on Nature Nature 572, 141-142 (2019). doi: 10.1038/d41586-019-02310-3 Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 3 / 29 Solving the Two-Language Problem: Julia Multiple dispatch • Dynamic type system • Good performance, approaching that of statically-compiled languages • JIT-compiled scripts • User-defined types are as fast and compact as built-ins • Lisp-like macros and other metaprogramming facilities • No need to vectorise: for loops are fast • Garbage collection: no manual memory management • Interactive shell (REPL) for exploratory work • Call C and Fortran functions directly: no wrappers or special APIs • Call Python functions: use the PyCall package • Designed for parallelism and distributed computation • Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 4 / 29 Multiple Dispatch using DifferentialEquations -
Comp 411 Principles of Programming Languages Lecture 19 Semantics of OO Languages
Comp 411 Principles of Programming Languages Lecture 19 Semantics of OO Languages Corky Cartwright Mar 10-19, 2021 Overview I • In OO languages, OO data values (except for designated non-OO types) are special records [structures] (finite mappings from names to values). In OO parlance, the components of record are called members. • Some members of an object may be functions called methods. Methods take this (the object in question) as an implicit parameter. Some OO languages like Java also support static methods that do not depend on this; these methods have no implicit parameters. In efficient OO language implementations, method members are shared since they are the same for all instances of a class, but this sharing is an optimization in statically typed OO languages since the collection of methods in a class is immutable during program evaluation (computation). • A method (instance method in Java) can only be invoked on an object (the receiver, an implicit parameter). Additional parameters are optional, depending on whether the method expects them. This invocation process is called dynamic dispatch because the executed code is literally extracted from the object: the code invoked at a call site depends on the value of the receiver, which can change with each execution of the call. • A language with objects is OO if it supports dynamic dispatch (discussed in more detail in Overview II & III) and inheritance, an explicit taxonomy for classifying objects based on their members and class names where superclass/parent methods are inherited unless overridden. • In single inheritance, this taxonomy forms a tree; • In multiple inheritance, it forms a rooted DAG (directed acyclic graph) where the root class is the universal class (Object in Java). -
Dynamic Dispatch
CS 3110 Lecture 24: Dynamic Dispatch Prof. Clarkson Spring 2015 Today’s music: "Te Core" by Eric Clapton Review Current topic: functional vs. object-oriented programming Today: • Continue encoding objects in OCaml • Te core of OOP – dynamic dispatch – sigma calculus Review: key features of OOP 1. Encapsulation 2. Subtyping 3. Inheritance 4. Dynamic dispatch Review: Counters class Counter {! protected int x = 0;! public int get() { return x; }! public void inc() { x++; }! }! Review: Objects • Type of object is record of functions !type counter = {! !get : unit -> int;! !inc : unit -> unit;! !} • Let-binding hides internal state (with closure) !let x = ref 0 in {! !get = (fun () -> !x);! !inc = (fun () -> x := !x+1);! !}! Review: Classes • Representation type for internal state: !type counter_rep = {! !!x : int ref;! !}! • Class is a function from representation type to object: !let counter_class (r:counter_rep) = {! !!get = (fun () -> !(r.x));! !!inc = (fun () -> (r.x := !(r.x) + 1));! !}! • Constructor uses class function to make a new object: !let new_counter () =! !!let r = {x = ref 0} in! ! !counter_class r !! Review: Inheritance • Subclass creates an object of the superclass with the same internal state as its own – Bind resulting parent object to super • Subclass creates a new object with same internal state • Subclass copies (inherits) any implementations it wants from superclass 4. DYNAMIC DISPATCH This class SetCounter {! protected int x = 0;! public int get() { return x; }! public void set(int i) { x = i; }! public void inc()