Java Byte Data Type Example
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Type-Safe Composition of Object Modules*
International Conference on Computer Systems and Education I ISc Bangalore Typ esafe Comp osition of Ob ject Mo dules Guruduth Banavar Gary Lindstrom Douglas Orr Department of Computer Science University of Utah Salt LakeCity Utah USA Abstract Intro duction It is widely agreed that strong typing in We describ e a facility that enables routine creases the reliability and eciency of soft typ echecking during the linkage of exter ware However compilers for statically typ ed nal declarations and denitions of separately languages suchasC and C in tradi compiled programs in ANSI C The primary tional nonintegrated programming environ advantage of our serverstyle typ echecked ments guarantee complete typ esafety only linkage facility is the ability to program the within a compilation unit but not across comp osition of ob ject mo dules via a suite of suchunits Longstanding and widely avail strongly typ ed mo dule combination op era able linkers comp ose separately compiled tors Such programmability enables one to units bymatching symb ols purely byname easily incorp orate programmerdened data equivalence with no regard to their typ es format conversion stubs at linktime In ad Such common denominator linkers accom dition our linkage facility is able to automat mo date ob ject mo dules from various source ically generate safe co ercion stubs for com languages by simply ignoring the static se patible encapsulated data mantics of the language Moreover com monly used ob ject le formats are not de signed to incorp orate source language typ e -
Application of TRIE Data Structure and Corresponding Associative Algorithms for Process Optimization in GRID Environment
Application of TRIE data structure and corresponding associative algorithms for process optimization in GRID environment V. V. Kashanskya, I. L. Kaftannikovb South Ural State University (National Research University), 76, Lenin prospekt, Chelyabinsk, 454080, Russia E-mail: a [email protected], b [email protected] Growing interest around different BOINC powered projects made volunteer GRID model widely used last years, arranging lots of computational resources in different environments. There are many revealed problems of Big Data and horizontally scalable multiuser systems. This paper provides an analysis of TRIE data structure and possibilities of its application in contemporary volunteer GRID networks, including routing (L3 OSI) and spe- cialized key-value storage engine (L7 OSI). The main goal is to show how TRIE mechanisms can influence de- livery process of the corresponding GRID environment resources and services at different layers of networking abstraction. The relevance of the optimization topic is ensured by the fact that with increasing data flow intensi- ty, the latency of the various linear algorithm based subsystems as well increases. This leads to the general ef- fects, such as unacceptably high transmission time and processing instability. Logically paper can be divided into three parts with summary. The first part provides definition of TRIE and asymptotic estimates of corresponding algorithms (searching, deletion, insertion). The second part is devoted to the problem of routing time reduction by applying TRIE data structure. In particular, we analyze Cisco IOS switching services based on Bitwise TRIE and 256 way TRIE data structures. The third part contains general BOINC architecture review and recommenda- tions for highly-loaded projects. -
An Overview of the 50 Most Common Web Scraping Tools
AN OVERVIEW OF THE 50 MOST COMMON WEB SCRAPING TOOLS WEB SCRAPING IS THE PROCESS OF USING BOTS TO EXTRACT CONTENT AND DATA FROM A WEBSITE. UNLIKE SCREEN SCRAPING, WHICH ONLY COPIES PIXELS DISPLAYED ON SCREEN, WEB SCRAPING EXTRACTS UNDERLYING CODE — AND WITH IT, STORED DATA — AND OUTPUTS THAT INFORMATION INTO A DESIGNATED FILE FORMAT. While legitimate uses cases exist for data harvesting, illegal purposes exist as well, including undercutting prices and theft of copyrighted content. Understanding web scraping bots starts with understanding the diverse and assorted array of web scraping tools and existing platforms. Following is a high-level overview of the 50 most common web scraping tools and platforms currently available. PAGE 1 50 OF THE MOST COMMON WEB SCRAPING TOOLS NAME DESCRIPTION 1 Apache Nutch Apache Nutch is an extensible and scalable open-source web crawler software project. A-Parser is a multithreaded parser of search engines, site assessment services, keywords 2 A-Parser and content. 3 Apify Apify is a Node.js library similar to Scrapy and can be used for scraping libraries in JavaScript. Artoo.js provides script that can be run from your browser’s bookmark bar to scrape a website 4 Artoo.js and return the data in JSON format. Blockspring lets users build visualizations from the most innovative blocks developed 5 Blockspring by engineers within your organization. BotScraper is a tool for advanced web scraping and data extraction services that helps 6 BotScraper organizations from small and medium-sized businesses. Cheerio is a library that parses HTML and XML documents and allows use of jQuery syntax while 7 Cheerio working with the downloaded data. -
Data and Computer Communications (Eighth Edition)
DATA AND COMPUTER COMMUNICATIONS Eighth Edition William Stallings Upper Saddle River, New Jersey 07458 Library of Congress Cataloging-in-Publication Data on File Vice President and Editorial Director, ECS: Art Editor: Gregory Dulles Marcia J. Horton Director, Image Resource Center: Melinda Reo Executive Editor: Tracy Dunkelberger Manager, Rights and Permissions: Zina Arabia Assistant Editor: Carole Snyder Manager,Visual Research: Beth Brenzel Editorial Assistant: Christianna Lee Manager, Cover Visual Research and Permissions: Executive Managing Editor: Vince O’Brien Karen Sanatar Managing Editor: Camille Trentacoste Manufacturing Manager, ESM: Alexis Heydt-Long Production Editor: Rose Kernan Manufacturing Buyer: Lisa McDowell Director of Creative Services: Paul Belfanti Executive Marketing Manager: Robin O’Brien Creative Director: Juan Lopez Marketing Assistant: Mack Patterson Cover Designer: Bruce Kenselaar Managing Editor,AV Management and Production: Patricia Burns ©2007 Pearson Education, Inc. Pearson Prentice Hall Pearson Education, Inc. Upper Saddle River, NJ 07458 All rights reserved. No part of this book may be reproduced in any form or by any means, without permission in writing from the publisher. Pearson Prentice Hall™ is a trademark of Pearson Education, Inc. All other tradmarks or product names are the property of their respective owners. The author and publisher of this book have used their best efforts in preparing this book.These efforts include the development, research, and testing of the theories and programs to determine their effectiveness.The author and publisher make no warranty of any kind, expressed or implied, with regard to these programs or the documentation contained in this book.The author and publisher shall not be liable in any event for incidental or consequential damages in connection with, or arising out of, the furnishing, performance, or use of these programs. -
Customizing and Extending Powerdesigner SAP Powerdesigner Documentation Collection Content
User Guide PUBLIC SAP PowerDesigner Document Version: 16.6.2 – 2017-01-05 Customizing and Extending PowerDesigner SAP PowerDesigner Documentation Collection Content 1 PowerDesigner Resource Files.................................................... 9 1.1 Opening Resource Files in the Editor.................................................10 1.2 Navigating and Searching in Resource Files............................................ 11 1.3 Editing Resource Files........................................................... 13 1.4 Saving Changes................................................................13 1.5 Sharing and Embedding Resource Files...............................................13 1.6 Creating and Copying Resource Files.................................................14 1.7 Specifying Directories to Search for Resource Files.......................................15 1.8 Comparing Resource Files........................................................ 15 1.9 Merging Resource Files.......................................................... 16 2 Extension Files................................................................18 2.1 Creating an Extension File.........................................................19 2.2 Attaching Extensions to a Model....................................................20 2.3 Exporting an Embedded Extension File for Sharing.......................................21 2.4 Extension File Properties......................................................... 21 2.5 Example: Adding a New Attribute from a Property -
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 ..................................................................................................... -
The Hexadecimal Number System and Memory Addressing
C5537_App C_1107_03/16/2005 APPENDIX C The Hexadecimal Number System and Memory Addressing nderstanding the number system and the coding system that computers use to U store data and communicate with each other is fundamental to understanding how computers work. Early attempts to invent an electronic computing device met with disappointing results as long as inventors tried to use the decimal number sys- tem, with the digits 0–9. Then John Atanasoff proposed using a coding system that expressed everything in terms of different sequences of only two numerals: one repre- sented by the presence of a charge and one represented by the absence of a charge. The numbering system that can be supported by the expression of only two numerals is called base 2, or binary; it was invented by Ada Lovelace many years before, using the numerals 0 and 1. Under Atanasoff’s design, all numbers and other characters would be converted to this binary number system, and all storage, comparisons, and arithmetic would be done using it. Even today, this is one of the basic principles of computers. Every character or number entered into a computer is first converted into a series of 0s and 1s. Many coding schemes and techniques have been invented to manipulate these 0s and 1s, called bits for binary digits. The most widespread binary coding scheme for microcomputers, which is recog- nized as the microcomputer standard, is called ASCII (American Standard Code for Information Interchange). (Appendix B lists the binary code for the basic 127- character set.) In ASCII, each character is assigned an 8-bit code called a byte. -
Abstract Data Types
Chapter 2 Abstract Data Types The second idea at the core of computer science, along with algorithms, is data. In a modern computer, data consists fundamentally of binary bits, but meaningful data is organized into primitive data types such as integer, real, and boolean and into more complex data structures such as arrays and binary trees. These data types and data structures always come along with associated operations that can be done on the data. For example, the 32-bit int data type is defined both by the fact that a value of type int consists of 32 binary bits but also by the fact that two int values can be added, subtracted, multiplied, compared, and so on. An array is defined both by the fact that it is a sequence of data items of the same basic type, but also by the fact that it is possible to directly access each of the positions in the list based on its numerical index. So the idea of a data type includes a specification of the possible values of that type together with the operations that can be performed on those values. An algorithm is an abstract idea, and a program is an implementation of an algorithm. Similarly, it is useful to be able to work with the abstract idea behind a data type or data structure, without getting bogged down in the implementation details. The abstraction in this case is called an \abstract data type." An abstract data type specifies the values of the type, but not how those values are represented as collections of bits, and it specifies operations on those values in terms of their inputs, outputs, and effects rather than as particular algorithms or program code. -
PL/SQL Data Types
PPLL//SSQQLL -- DDAATTAA TTYYPPEESS http://www.tutorialspoint.com/plsql/plsql_data_types.htm Copyright © tutorialspoint.com PL/SQL variables, constants and parameters must have a valid data type, which specifies a storage format, constraints, and valid range of values. This tutorial will take you through SCALAR and LOB data types available in PL/SQL and other two data types will be covered in other chapters. Category Description Scalar Single values with no internal components, such as a NUMBER, DATE, or BOOLEAN. Large Object LOB Pointers to large objects that are stored separately from other data items, such as text, graphic images, video clips, and sound waveforms. Composite Data items that have internal components that can be accessed individually. For example, collections and records. Reference Pointers to other data items. PL/SQL Scalar Data Types and Subtypes PL/SQL Scalar Data Types and Subtypes come under the following categories: Date Type Description Numeric Numeric values on which arithmetic operations are performed. Character Alphanumeric values that represent single characters or strings of characters. Boolean Logical values on which logical operations are performed. Datetime Dates and times. PL/SQL provides subtypes of data types. For example, the data type NUMBER has a subtype called INTEGER. You can use subtypes in your PL/SQL program to make the data types compatible with data types in other programs while embedding PL/SQL code in another program, such as a Java program. PL/SQL Numeric Data Types and Subtypes Following -
Midterm-2020-Solution.Pdf
HONOR CODE Questions Sheet. A Lets C. [6 Points] 1. What type of address (heap,stack,static,code) does each value evaluate to Book1, Book1->name, Book1->author, &Book2? [4] 2. Will all of the print statements execute as expected? If NO, write print statement which will not execute as expected?[2] B. Mystery [8 Points] 3. When the above code executes, which line is modified? How many times? [2] 4. What is the value of register a6 at the end ? [2] 5. What is the value of register a4 at the end ? [2] 6. In one sentence what is this program calculating ? [2] C. C-to-RISC V Tree Search; Fill in the blanks below [12 points] D. RISCV - The MOD operation [8 points] 19. The data segment starts at address 0x10000000. What are the memory locations modified by this program and what are their values ? E Floating Point [8 points.] 20. What is the smallest nonzero positive value that can be represented? Write your answer as a numerical expression in the answer packet? [2] 21. Consider some positive normalized floating point number where p is represented as: What is the distance (i.e. the difference) between p and the next-largest number after p that can be represented? [2] 22. Now instead let p be a positive denormalized number described asp = 2y x 0.significand. What is the distance between p and the next largest number after p that can be represented? [2] 23. Sort the following minifloat numbers. [2] F. Numbers. [5] 24. What is the smallest number that this system can represent 6 digits (assume unsigned) ? [1] 25. -
2018-19 MAP 160 Byte File Layout Specifications
2018-19 MAP 160 Byte File Layout Specifications OVERVIEW: A) ISAC will provide an Eligibility Status File (ESF) record for each student to all schools listed as a college choice on the student’s Student Aid Report (SAR). The ESF records will be available daily as Record Type = 7. ESF records may be retrieved via the File Extraction option in MAP. B) Schools will transmit Payment Requests to ISAC via File Transfer Protocol (FTP) using the MAP 160byte layout and identify these with Record Type = 4. C) When payment requests are processed, ISAC will provide payment results to schools through the MAP system. The payment results records can be retrieved in the 160 byte format using the MAP Payment Results File Extraction Option. MAP results records have a Record Type = 5. The MAP Payment Results file contains some eligibility status data elements. Also, the same student record may appear on both the Payment Results and the Eligibility Status extract files. Schools may also use the Reports option in MAP to obtain payment results. D) To cancel Payment Requests, the school with the current Payment Results record on ISAC's Payment Database must transmit a matching record with MAP Payment Request Code = C, with the Requested Award Amount field equal to zero and the Enrollment Hours field equal to 0 along with other required data elements. These records must be transmitted to ISAC as Record Type = 4. E) Summary of Data Element Changes, revision (highlighted in grey) made to the 2018-19 layout. NONE 1 2018-19 MAP 160 Byte File Layout Specifications – 9/17 2018-19 MAP 160 Byte File Layout Specifications F) The following 160 byte record layout will be used for transmitting data between schools and ISAC. -
5. Data Types
IEEE FOR THE FUNCTIONAL VERIFICATION LANGUAGE e Std 1647-2011 5. Data types The e language has a number of predefined data types, including the integer and Boolean scalar types common to most programming languages. In addition, new scalar data types (enumerated types) that are appropriate for programming, modeling hardware, and interfacing with hardware simulators can be created. The e language also provides a powerful mechanism for defining OO hierarchical data structures (structs) and ordered collections of elements of the same type (lists). The following subclauses provide a basic explanation of e data types. 5.1 e data types Most e expressions have an explicit data type, as follows: — Scalar types — Scalar subtypes — Enumerated scalar types — Casting of enumerated types in comparisons — Struct types — Struct subtypes — Referencing fields in when constructs — List types — The set type — The string type — The real type — The external_pointer type — The “untyped” pseudo type Certain expressions, such as HDL objects, have no explicit data type. See 5.2 for information on how these expressions are handled. 5.1.1 Scalar types Scalar types in e are one of the following: numeric, Boolean, or enumerated. Table 17 shows the predefined numeric and Boolean types. Both signed and unsigned integers can be of any size and, thus, of any range. See 5.1.2 for information on how to specify the size and range of a scalar field or variable explicitly. See also Clause 4. 5.1.2 Scalar subtypes A scalar subtype can be named and created by using a scalar modifier to specify the range or bit width of a scalar type.