Uniform Treatment of Code and Data in the Web Setting (Thesis Format
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Preview Objective-C Tutorial (PDF Version)
Objective-C Objective-C About the Tutorial Objective-C is a general-purpose, object-oriented programming language that adds Smalltalk-style messaging to the C programming language. This is the main programming language used by Apple for the OS X and iOS operating systems and their respective APIs, Cocoa and Cocoa Touch. This reference will take you through simple and practical approach while learning Objective-C Programming language. Audience This reference has been prepared for the beginners to help them understand basic to advanced concepts related to Objective-C Programming languages. Prerequisites Before you start doing practice with various types of examples given in this reference, I'm making an assumption that you are already aware about what is a computer program, and what is a computer programming language? Copyright & Disclaimer © Copyright 2015 by Tutorials Point (I) Pvt. Ltd. All the content and graphics published in this e-book are the property of Tutorials Point (I) Pvt. Ltd. The user of this e-book can retain a copy for future reference but commercial use of this data is not allowed. Distribution or republishing any content or a part of the content of this e-book in any manner is also not allowed without written consent of the publisher. We strive to update the contents of our website and tutorials as timely and as precisely as possible, however, the contents may contain inaccuracies or errors. Tutorials Point (I) Pvt. Ltd. provides no guarantee regarding the accuracy, timeliness or completeness of our website or its contents including this tutorial. If you discover any errors on our website or in this tutorial, please notify us at [email protected] ii Objective-C Table of Contents About the Tutorial .................................................................................................................................. -
A New Macro-Programming Paradigm in Data Collection Sensor Networks
SpaceTime Oriented Programming: A New Macro-Programming Paradigm in Data Collection Sensor Networks Hiroshi Wada and Junichi Suzuki Department of Computer Science University of Massachusetts, Boston Program Insert This paper proposes a new programming paradigm for wireless sensor networks (WSNs). It is designed to significantly reduce the complexity of WSN programming by providing a new high- level programming abstraction to specify spatio-temporal data collections in a WSN from a global viewpoint as a whole rather than sensor nodes as individuals. Abstract SpaceTime Oriented Programming (STOP) is new macro-programming paradigm for wireless sensor networks (WSNs) in that it supports both spatial and temporal aspects of sensor data and it provides a high-level abstraction to express data collections from a global viewpoint for WSNs as a whole rather than sensor nodes as individuals. STOP treats space and time as first-class citizens and combines them as spacetime continuum. A spacetime is a three dimensional object that consists of a two special dimensions and a time playing the role of the third dimension. STOP allows application developers to program data collections to spacetime, and abstracts away the details in WSNs, such as how many nodes are deployed in a WSN, how nodes are connected with each other, and how to route data queries in a WSN. Moreover, STOP provides a uniform means to specify data collections for the past and future. Using the STOP application programming interfaces (APIs), application programs (STOP macro programs) can obtain a “snapshot” space at a given time in a given spatial resolutions (e.g., a space containing data on at least 60% of nodes in a give spacetime at 30 minutes ago.) and a discrete set of spaces that meet specified spatial and temporal resolutions. -
JETIR Research Journal
© 2018 JETIR October 2018, Volume 5, Issue 10 www.jetir.org (ISSN-2349-5162) QUALITATIVE COMPARISON OF KEY-VALUE BIG DATA DATABASES 1Ahmad Zia Atal, 2Anita Ganpati 1M.Tech Student, 2Professor, 1Department of computer Science, 1Himachal Pradesh University, Shimla, India Abstract: Companies are progressively looking to big data to convey valuable business insights that cannot be taken care by the traditional Relational Database Management System (RDBMS). As a result, a variety of big data databases options have developed. From past 30 years traditional Relational Database Management System (RDBMS) were being used in companies but now they are replaced by the big data. All big bata technologies are intended to conquer the limitations of RDBMS by enabling organizations to extract value from their data. In this paper, three key-value databases are discussed and compared on the basis of some general databases features and system performance features. Keywords: Big data, NoSQL, RDBMS, Riak, Redis, Hibari. I. INTRODUCTION Systems that are designed to store big data are often called NoSQL databases since they do not necessarily depend on the SQL query language used by RDBMS. NoSQL today is the term used to address the class of databases that do not follow Relational Database Management System (RDBMS) principles and are specifically designed to handle the speed and scale of the likes of Google, Facebook, Yahoo, Twitter and many more [1]. Many types of NoSQL database are designed for different use cases. The major categories of NoSQL databases consist of Key-Values store, Column family stores, Document databaseand graph database. Each of these technologies has their own benefits individually but generally Big data use cases are benefited by these technologies. -
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 ........................................... -
A Concurrent PASCAL Compiler for Minicomputers
512 Appendix A DIFFERENCES BETWEEN UCSD'S PASCAL AND STANDARD PASCAL The PASCAL language used in this book contains most of the features described by K. Jensen and N. Wirth in PASCAL User Manual and Report, Springer Verlag, 1975. We refer to the PASCAL defined by Jensen and Wirth as "Standard" PASCAL, because of its widespread acceptance even though no international standard for the language has yet been established. The PASCAL used in this book has been implemented at University of California San Diego (UCSD) in a complete software system for use on a variety of small stand-alone microcomputers. This will be referred to as "UCSD PASCAL", which differs from the standard by a small number of omissions, a very small number of alterations, and several extensions. This appendix provides a very brief summary Of these differences. Only the PASCAL constructs used within this book will be mentioned herein. Documents are available from the author's group at UCSD describing UCSD PASCAL in detail. 1. CASE Statements Jensen & Wirth state that if there is no label equal to the value of the case statement selector, then the result of the case statement is undefined. UCSD PASCAL treats this situation by leaving the case statement normally with no action being taken. 2. Comments In UCSD PASCAL, a comment appears between the delimiting symbols "(*" and "*)". If the opening delimiter is followed immediately by a dollar sign, as in "(*$", then the remainder of the comment is treated as a directive to the compiler. The only compiler directive mentioned in this book is (*$G+*), which tells the compiler to allow the use of GOTO statements. -
Why Untyped Nonground Metaprogramming Is Not (Much Of) a Problem
NORTH- HOLLAND WHY UNTYPED NONGROUND METAPROGRAMMING IS NOT (MUCH OF) A PROBLEM BERN MARTENS* and DANNY DE SCHREYE+ D We study a semantics for untyped, vanilla metaprograms, using the non- ground representation for object level variables. We introduce the notion of language independence, which generalizes range restriction. We show that the vanilla metaprogram associated with a stratified normal oljjctct program is weakly stratified. For language independent, stratified normal object programs, we prove that there is a natural one-to-one correspon- dence between atoms p(tl, . , tr) in the perfect Herbrand model of t,he object program and solve(p(tl, , tT)) atoms in the weakly perfect Her\) and model of the associated vanilla metaprogram. Thus, for this class of programs, the weakly perfect, Herbrand model provides a sensible SC mantics for the metaprogram. We show that this result generalizes to nonlanguage independent programs in the context of an extended Hcr- brand semantics, designed to closely mirror the operational behavior of logic programs. Moreover, we also consider a number of interesting exterl- sions and/or variants of the basic vanilla metainterpreter. For instance. WC demonstrate how our approach provides a sensible semantics for a limit4 form of amalgamation. a “Partly supported by the Belgian National Fund for Scientific Research, partly by ESPRlT BRA COMPULOG II, Contract 6810, and partly by GOA “Non-Standard Applications of Ab- stract Interpretation,” Belgium. TResearch Associate of the Belgian National Fund for Scientific Research Address correspondence to Bern Martens and Danny De Schreye, Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A. B-3001 Hevrrlee Belgium E-mail- {bern, dannyd}@cs.kuleuven.ac.be. -
Algorithms and Data Structures Lecture 11: Symbol Table ADT
cs2010: algorithms and data structures Lecture 11: Symbol Table ADT Vasileios Koutavas School of Computer Science and Statistics Trinity College Dublin Algorithms ROBERT SEDGEWICK | KEVIN WAYNE 3.1 SYMBOL TABLES ‣ API ‣ elementary implementations Algorithms ‣ ordered operations FOURTH EDITION ROBERT SEDGEWICK | KEVIN WAYNE http://algs4.cs.princeton.edu 3.1 SYMBOL TABLES ‣ API ‣ elementary implementations Algorithms ‣ ordered operations ROBERT SEDGEWICK | KEVIN WAYNE http://algs4.cs.princeton.edu Symbol tables Key-value pair abstraction. ・Insert a value with specified key. ・Given a key, search for the corresponding value. Ex. DNS lookup. ・Insert domain name with specified IP address. ・Given domain name, find corresponding IP address. domain name IP address www.cs.princeton.edu 128.112.136.11 www.princeton.edu 128.112.128.15 www.yale.edu 130.132.143.21 www.harvard.edu 128.103.060.55 www.simpsons.com 209.052.165.60 key value 3 Symbol table applications application purpose of search key value dictionary find definition word definition book index find relevant pages term list of page numbers file share find song to download name of song computer ID financial account process transactions account number transaction details web search find relevant web pages keyword list of page names compiler find properties of variables variable name type and value routing table route Internet packets destination best route DNS find IP address domain name IP address reverse DNS find domain name IP address domain name genomics find markers DNA string known positions file system find file on disk filename location on disk 4 Symbol tables: context Also known as: maps, dictionaries, associative arrays. -
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. -
Practical Reflection and Metaprogramming for Dependent
Practical Reflection and Metaprogramming for Dependent Types David Raymond Christiansen Advisor: Peter Sestoft Submitted: November 2, 2015 i Abstract Embedded domain-specific languages are special-purpose pro- gramming languages that are implemented within existing general- purpose programming languages. Dependent type systems allow strong invariants to be encoded in representations of domain-specific languages, but it can also make it difficult to program in these em- bedded languages. Interpreters and compilers must always take these invariants into account at each stage, and authors of embedded languages must work hard to relieve users of the burden of proving these properties. Idris is a dependently typed functional programming language whose semantics are given by elaboration to a core dependent type theory through a tactic language. This dissertation introduces elabo- rator reflection, in which the core operators of the elaborator are real- ized as a type of computations that are executed during the elab- oration process of Idris itself, along with a rich API for reflection. Elaborator reflection allows domain-specific languages to be imple- mented using the same elaboration technology as Idris itself, and it gives them additional means of interacting with native Idris code. It also allows Idris to be used as its own metalanguage, making it into a programmable programming language and allowing code re-use across all three stages: elaboration, type checking, and execution. Beyond elaborator reflection, other forms of compile-time reflec- tion have proven useful for embedded languages. This dissertation also describes error reflection, in which Idris code can rewrite DSL er- ror messages before presenting domain-specific messages to users, as well as a means for integrating quasiquotation into a tactic-based elaborator so that high-level syntax can be used for low-level reflected terms. -
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. -
INTRODUCTION to PL/1 PL/I Is a Structured Language to Develop Systems and Applications Programs (Both Business and Scientific)
INTRODUCTION TO PL/1 PL/I is a structured language to develop systems and applications programs (both business and scientific). Significant features : v Allows Free format v Regards a program as a continuous stream of data v Supports subprogram and functions v Uses defaults 1 Created by Sanjay Sinha Building blocks of PL/I : v Made up of a series of subprograms and called Procedure v Program is structured into a MAIN program and subprograms. v Subprograms include subroutine and functions. Every PL/I program consists of : v At least one Procedure v Blocks v Group 2 Created by Sanjay Sinha v There must be one and only one MAIN procedure to every program, the MAIN procedure statement consists of : v Label v The statement ‘PROCEDURE OPTIONS (MAIN)’ v A semicolon to mark the end of the statement. Coding a Program : 1. Comment line(s) begins with /* and ends with */. Although comments may be embedded within a PL/I statements , but it is recommended to keep the embedded comments minimum. 3 Created by Sanjay Sinha 2. The first PL/I statement in the program is the PROCEDURE statement : AVERAGE : PROC[EDURE] OPTIONS(MAIN); AVERAGE -- it is the name of the program(label) and compulsory and marks the beginning of a program. OPTIONS(MAIN) -- compulsory for main programs and if not specified , then the program is a subroutine. A PL/I program is compiled by PL/I compiler and converted into the binary , Object program file for link editing . 4 Created by Sanjay Sinha Advantages of PL/I are : 1. Better integration of sets of programs covering several applications. -
Open Office Specification 1.0
Open Office Specification 1.0 Committee Draft 1, 22 Mar 2004 Document identifier: office-spec-1.0-cd-1.sxw Location: http://www.oasis-open.org/committees/office/ Editors: Michael Brauer, Sun Microsystems <[email protected]> Gary Edwards <[email protected]> Daniel Vogelheim, Sun Microsystems <[email protected]> Contributors: Doug Alberg, Boeing <[email protected]> Simon Davis, National Archive of Australia <[email protected]> Patrick Durusau, Society of Biblical Literature <[email protected]> David Faure, <[email protected]> Paul Grosso, Arbortext <[email protected]> Tom Magliery, Blast Radius <[email protected]> Phil Boutros, Stellent <[email protected]> John Chelsom, CSW Informatics <[email protected]> Jason Harrop, SpeedLegal <[email protected]> Mark Heller, New York State Office of the Attorney General <[email protected]> Paul Langille, Corel <[email protected]> Monica Martin, Drake Certivo <[email protected]> Uche Ogbuji <[email protected]> Lauren Wood <[email protected]> Abstract: This is the specification of Open Office XML, an open, XML-based file format for office applications, based on OpenOffice.org XML [OOo]. Status: This document is a draft, and will be updated periodically on no particular schedule. Send comments to the editors. Committee members should send comments on this specification to the [email protected] list. Others should subscribe to and send comments to the [email protected] list. To subscribe, send an email message to office- [email protected] with the word "subscribe" as the body of the message.