DOCSLIB.ORG

Document Title Application Interfaces User Guide Document Owner AUTOSAR Document Responsibility AUTOSAR Document Identification No 442

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Document Title Application Interfaces User Guide Document Owner AUTOSAR Document Responsibility AUTOSAR Document Identification No 442 Application Interfaces User Guide AUTOSAR CP Release 4.3.1 Document Title Application Interfaces User Guide Document Owner AUTOSAR Document Responsibility AUTOSAR Document Identification No 442 Document Status Final Part of AUTOSAR Standard Classic Platform Part of Standard Release 4.3.1 Document Change History Date Release Changed by Change Description 2017-12-08 4.3.1 AUTOSAR Editorial changes Release Management 2016-11-30 4.3.0 AUTOSAR Add chapter about implementation Release of data types as integer or floating Management point data types – Chapter ID 4.2.3.3. Bugzilla # 72021 2015-07-31 4.2.2 AUTOSAR Updated explanation of the Release COMPU_METHOD reusage Management Updated the Linear Conversion Example 2014-10-31 4.2.1 AUTOSAR Sensors and Actuators Pattern Release adopted in the AI Domain Management Obsolete AI Table substituted by new official AI Tool for content development phase and arxml generation Enhanced collections arxml deliverables structure 2013-10-31 4.1.2 AUTOSAR New ARXML file distribution feature Release Management 2013-03-15 4.1.1 AUTOSAR Updated categories of model Administration elements (Data Constraints and Keywords to Blueprints) Introduced description of Backward Compatibility, Lifecyle State and Variant Handling (Views) concepts Deliverables from Application Interfaces updated 1 of 101 Document ID 442: AUTOSAR_EXP_AIUserGuide - AUTOSAR confidential - Application Interfaces User Guide AUTOSAR CP Release 4.3.1 Document Change History Date Release Changed by Change Description 2011-12-22 4.0.3 AUTOSAR Description of Categories of model Administration elements created Synchronization of Update of XML package structure especially regarding Port Blueprints Synchronization to updates of AUTOSAR meta model Description of Naming conventions for connectors 2011-04-15 4.0.2 AUTOSAR Initial Release Administration 2 of 101 Document ID 442: AUTOSAR_EXP_AIUserGuide - AUTOSAR confidential - Application Interfaces User Guide AUTOSAR CP Release 4.3.1 Disclaimer This work (specification and/or software implementation) and the material contained in it, as released by AUTOSAR, is for the purpose of information only. AUTOSAR and the companies that have contributed to it shall not be liable for any use of the work. The material contained in this work is protected by copyright and other types of intellectual property rights. The commercial exploitation of the material contained in this work requires a license to such intellectual property rights. This work may be utilized or reproduced without any modification, in any form or by any means, for informational purposes only. For any other purpose, no part of the work may be utilized or reproduced, in any form or by any means, without permission in writing from the publisher. The work has been developed for automotive applications only. It has neither been developed, nor tested for non-automotive applications. The word AUTOSAR and the AUTOSAR logo are registered trademarks. 3 of 101 Document ID 442: AUTOSAR_EXP_AIUserGuide - AUTOSAR confidential - Application Interfaces User Guide AUTOSAR CP Release 4.3.1 Table of Contents 1 Purpose of this document .................................................................................. 7 1.1 Document Overview ..................................................................................... 7 2 Introduction to Application Interfaces Table ....................................................... 8 2.1 Structural overview of Domains in AI Table ................................................ 10 3 AUTOSAR Methodology .................................................................................. 11 3.1 Overview on available documents .............................................................. 12 3.1.1 Software Component Template [1] ........................................................ 12 3.1.2 Standardization Template [2] ................................................................. 12 3.1.3 Generic Structure Template [4] .............................................................. 12 3.1.4 AI Specification [6] ................................................................................. 12 3.1.5 Modeling Guide for Application Interfaces [9] ......................................... 12 3.1.6 AUTOSAR Methodology [10] ................................................................. 12 3.1.7 Explanation of Application Interfaces for Domain Body Comfort [11] ..... 13 3.1.8 Explanation of Application Interfaces for Domain Powertrain [12] .......... 13 3.1.9 Explanation of Application Interfaces for Domain Chassis [13] .............. 13 3.1.10 Explanation of Application Interfaces for Domain Occupant and Pedestrian Safety [14] ............................................................................ 13 3.1.11 Explanation of Application Interfaces for Domain Multimedia, Telematics, Human Machine Interface [15] ............................................ 13 4 Metamodel representation of AI Table ............................................................. 14 4.1 Category of Model Elements ...................................................................... 14 4.1.1 STANDARD ........................................................................................... 14 4.1.2 BLUEPRINT ........................................................................................... 14 4.1.3 EXAMPLE .............................................................................................. 15 4.2 Meta model diagrams and the AI Table ...................................................... 15 4.2.1 Composition ........................................................................................... 15 4.2.2 Blueprint Mapping & BlueprintMappingSet............................................. 20 4.2.3 PortPrototypes ....................................................................................... 21 4.2.4 PortInterfaces ......................................................................................... 23 4.2.5 DataTypes .............................................................................................. 26 4.2.6 Physical Units ........................................................................................ 32 4.2.7 Computation Methods ............................................................................ 33 4.2.8 Keyword and KeywordSet ...................................................................... 33 5 Backward Compatibility .................................................................................... 36 4 of 101 Document ID 442: AUTOSAR_EXP_AIUserGuide - AUTOSAR confidential - Application Interfaces User Guide AUTOSAR CP Release 4.3.1 5.1 Introduction ................................................................................................. 36 5.2 Backward Compatibility Definition .............................................................. 36 5.3 Summary .................................................................................................... 39 6 Life Cycle States .............................................................................................. 40 6.1 Introduction ................................................................................................. 40 6.2 Representation in AI Table ......................................................................... 40 6.3 Representation in meta model and arxml ................................................... 41 7 View Concept in Application Interfaces (Variant Handling) .............................. 43 7.1 Introduction ................................................................................................. 43 7.2 Implementation in Application Interfaces and Meta Model Representation 43 8 Structure of Application Interfaces (AI) Table ................................................... 47 8.1 Main sheets of the AI Table ........................................................................ 47 8.1.1 Sheet 04_Keywords ............................................................................... 47 8.1.2 Sheet 05_TopLevel ................................................................................ 48 8.1.3 Sheets 050xxxxx .................................................................................... 51 8.1.4 Sheet 06_Interfaces_DataElements (SenderReceiverInterface) ............ 52 8.1.5 Sheet 06_Interface_ClientServer ........................................................... 54 8.1.6 Sheet 07_DataTypes_ContinuousValue ................................................ 56 8.1.7 Sheet 08_DataTypes_Enumeration ....................................................... 56 8.1.8 Sheet 09_DataTypes_Array ................................................................... 58 8.1.9 Sheet 11_DataTypes_Record ................................................................ 59 8.1.10 Sheet 13_Units ...................................................................................... 61 8.1.11 Sheet 15_Redirected_Ports ................................................................... 62 8.2 Complete List of all Sheets of the AI Table ................................................. 63 9 Relationship between AI Table data and XML Output ...................................... 66 9.1 Overview .................................................................................................... 66 9.1.1 Dependencies of XML Generation ......................................................... 66 9.1.2 Contents of Generated XML .................................................................
Load more

Recommended publications
  • 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.
    [Show full text]
  • 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 .....................................................................................................
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Lecture Notes)
    Sri Vidya College of Engineering & Technology Course Material ( Lecture Notes) Data structures can be classified as · Simple data structure · Compound data structure · Linear data structure · Non linear data structure Simple Data Structure: Simple data structure can be constructed with the help of primitive data structure. A primitive data structure used to represent the standard data types of any one of the computer languages. Variables, arrays, pointers, structures, unions, etc. are examples of primitive data structures. Compound Data structure: Compound data structure can be constructed with the help of any one of the primitive data structure and it is having a specific functionality. It can be designed by user. It can be classified as 1) Linear data structure 2) Non-linear data structure Linear data structure : Collection of nodes which are logically adjacent in which logical adjacency is maintained by pointers (or) Linear data structures can be constructed as a continuous arrangement of data elements in the memory. It can be constructed by using array data type. In the linear Data Structures the relation ship of adjacency is maintained between the Data elements. Operations applied on linear data structure : The following list of operations applied on linear data structures 1. Add an element 2. Delete an element 3. Traverse 4. Sort the list of elements CS8391 – Data Structures - Unit I Page 1 Sri Vidya College of Engineering & Technology Course Material ( Lecture Notes) 5. Search for a data element By applying one or more functionalities to create different types of data structures For example Stack, Queue, Tables, List, and Linked Lists. Non-linear data structure: Non-linear data structure can be constructed as a collection of randomly distributed set of data item joined together by using a special pointer (tag).
    [Show full text]
  • Array Data Structure
    © 2014 IJIRT | Volume 1 Issue 6 | ISSN : 2349-6002 ARRAY DATA STRUCTURE Isha Batra, Divya Raheja Information Technology Dronacharya College Of Engineering, Farukhnagar,Gurgaon Abstract- In computer science, an array data structure valid index tuples and the addresses of the elements or simply an array is a data structure consisting of a (and hence the element addressing formula) are collection of elements (values or variables), each usually but not always fixed while the array is in use. identified by at least one array index or key. An array is The term array is often used to mean array data type, stored so that the position of each element can be a kind of data type provided by most high-level computed from its index tuple by a mathematical formula. The simplest type of data structure is a linear programming languages that consists of a collection array, also called one-dimensional array. For example, of values or variables that can be selected by one or an array of 10 32-bit integer variables, with indices 0 more indices computed at run-time. Array types are through 9, may be stored as 10 words at memory often implemented by array structures; however, in addresses 2000, 2004, 2008, … 2036, so that the element some languages they may be implemented by hash with index i has the address 2000 + 4 × i. The term array tables, linked lists, search trees, or other data is often used to mean array data type, a kind of data structures. The term is also used, especially in the type provided by most high-level programming description of algorithms, to mean associative array languages that consists of a collection of values or or "abstract array", a theoretical computer science variables that can be selected by one or more indices computed at run-time.
    [Show full text]
  • Reference Metamodel for the EXPRESS Information Modeling Language Specification
    Reference Metamodel for the EXPRESS Information Modeling Language Specification Version 1.0 - October 2010 OMG Document Number: formal/2010-10-01 Standard document URL: http://www.omg.org/spec/EXPRESS/1.0 Associated Files*: http://www.omg.org/spec/EXPRESS/20091201 * Original files: dtc/09-12-09 (cmof.xmi) Copyright © 2008, JBIC (Japan Biological Informatics Consortium) Copyright © 2010, Object Management Group, Inc. USE OF SPECIFICATION - TERMS, CONDITIONS & NOTICES The material in this document details an Object Management Group specification in accordance with the terms, conditions and notices set forth below. This document does not represent a commitment to implement any portion of this specification in any company’s products. The information contained in this document is subject to change without notice. LICENSES The companies listed above have granted to the Object Management Group, Inc. (OMG) a nonexclusive, royalty-free, paid up, worldwide license to copy and distribute this document and to modify this document and distribute copies of the modified version. Each of the copyright holders listed above has agreed that no person shall be deemed to have infringed the copyright in the included material of any such copyright holder by reason of having used the specification set forth herein or having conformed any computer software to the specification. Subject to all of the terms and conditions below, the owners of the copyright in this specification hereby grant you a fully-paid up, non-exclusive, nontransferable, perpetual, worldwide
    [Show full text]
  • Array Operators Using Multiple Dispatch: a Design Methodology for Array Implementations in Dynamic Languages
    Array Operators Using Multiple Dispatch: A design methodology for array implementations in dynamic languages The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Jeff Bezanson, Jiahao Chen, Stefan Karpinski, Viral Shah, and Alan Edelman. 2014. Array Operators Using Multiple Dispatch: A design methodology for array implementations in dynamic languages. In Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming (ARRAY '14). ACM, New York, NY, USA, 56-61, 6 pages. As Published http://dx.doi.org/10.1145/2627373.2627383 Publisher Association for Computing Machinery (ACM) Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/92858 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike Detailed Terms http://creativecommons.org/licenses/by-nc-sa/4.0/ Array Operators Using Multiple Dispatch Array Operators Using Multiple Dispatch A design methodology for array implementations in dynamic languages Jeff Bezanson Jiahao Chen Stefan Karpinski Viral Shah Alan Edelman MIT Computer Science and Artificial Intelligence Laboratory [email protected], [email protected], [email protected], [email protected], [email protected] Abstract ficient, such as loop fusion for array traversals and common subex- Arrays are such a rich and fundamental data type that they tend to pression elimination for indexing operations [3, 24]. Many lan- be built into a language, either in the compiler or in a large low- guage implementations therefore choose to build array semantics level library. Defining this functionality at the user level instead into compilers. provides greater flexibility for application domains not envisioned Only a few of the languages that support n-arrays, however, by the language designer.
    [Show full text]
  • Data Structures Arrays and Structs 9.1 the Array Data Type Arrays Arrays
    9.1 The Array Data Type Array elements have a common name – The array as a whole is referenced through the common name Array elements are of the same type — the Data Structures base type Arrays and Structs Individual elements of the array are referenced by sub_scripting the group name Chapter 9 2 Arrays Arrays Analogies Language restrictions – Egg carton – Subscripts are denoted as expressions – Apartments within brackets: [ ] – Cassette carrier – Base type can be any fundamental, More terminology library-defined, or programmer -defined – Ability to refer to a particular element type • Indexing or sub_scripting – Ability to look inside an element • Accessing value 3 4 Arrays Array Declaration – The index type is integer and the index range must be BaseTypeId [ SizeExp] ; 0 ... n-1 Type of Bracketed • where n is a programmer-defined constant values in constant list Name expression expression. of list indicating – Parameter passing style number of elements in • Always call by reference (no indication list necessary) 5 6 1 Sample Declarations Sample Declarations Suppose Then the following are all correct array const int N = 20; declarations. const int M = 40; int A[10]; const int MaxStringSize = 80; char B[MaxStringSize]; const int MaxListSize = 1000; float C[M*N]; int Values[MaxListSize]; Rational D[N-15]; 7 8 Subscripting Subscripting Suppose – Second element of A has index 1, and so on int A[10]; // array of 10 ints A[1] To access an individual element we must – Last element has an index one less than the size apply a subscript
    [Show full text]
  • A Brief Overview of Functional Programming Languages
    electronic Journal of Computer Science and Information Technology (eJCSIT), Vol. 6, No. 1, 2016 A Brief Overview of Functional Programming Languages Jagatheesan Kunasaikaran1, Azlan Iqbal2 1ZALORA Malaysia, Jalan Dua, Chan Sow Lin, Kuala Lumpur, Malaysia e-mail: [email protected] 2College of Computer Science and Information Technology, Universiti Tenaga Nasional, Putrajaya Campus, Selangor, Malaysia e-mail: [email protected] Abstract – Functional programming is an important Common programming paradigms are procedural, object- programming paradigm. It is based on a branch of oriented and functional. Figure 1 illustrates conceptually mathematics known as lambda calculus. In this article, we the differences between the common programming provide a brief overview, aimed at those new to the field, and language paradigms [1]. Procedural and object-oriented explain the progress of functional programming since its paradigms mutate or alter the data along program inception. A selection of functional languages are provided as examples. We also suggest some improvements and speculate execution. On the other hand, in pure functional style, the on the potential future directions of this paradigm. data does not exist by itself or independently. A composition of function calls with a set of arguments Keywords – functional, programming languages, LISP, Python; generates the final result that is expected. Each function is Javascript,Java, Elm, Haskell ‘atomic’ as it only executes operations defined in it to the input data and returns the result of the computation to the ‘callee’. I. INTRODUCTION II. FUNCTIONAL LANGUAGES Programming languages can be classified into the style of programming each language supports. There are multiple Functional programming is based on mathematical logic.
    [Show full text]
  • Systemverilog Reference
    SystemVerilog Reference Product Version 9.2 July 2010 © 1995-2010 Cadence Design Systems, Inc. All rights reserved worldwide. Printed in the United States of America. Cadence Design Systems, Inc., 555 River Oaks Parkway, San Jose, CA 95134, USA Trademarks: Trademarks and service marks of Cadence Design Systems, Inc. (Cadence) contained in this document are attributed to Cadence with the appropriate symbol. For queries regarding Cadence’s trademarks, contact the corporate legal department at the address shown above or call 800.862.4522. Open SystemC, Open SystemC Initiative, OSCI, SystemC, and SystemC Initiative are trademarks or registered trademarks of Open SystemC Initiative, Inc. in the United States and other countries and are used with permission. All other trademarks are the property of their respective holders. Restricted Print Permission: This publication is protected by copyright and any unauthorized use of this publication may violate copyright, trademark, and other laws. Except as specified in this permission statement, this publication may not be copied, reproduced, modified, published, uploaded, posted, transmitted, or distributed in any way, without prior written permission from Cadence. This statement grants you permission to print one (1) hard copy of this publication subject to the following conditions: 1. The publication may be used solely for personal, informational, and noncommercial purposes; 2. The publication may not be modified in any way; 3. Any copy of the publication or portion thereof must include all original copyright, trademark, and other proprietary notices and this permission statement; and 4. Cadence reserves the right to revoke this authorization at any time, and any such use shall be discontinued immediately upon written notice from Cadence.
    [Show full text]
  • The Role of Data Structures in Multiple Disciplines of Computer Science- a Review
    International Journal of Scientific & Engineering Research, Volume 4, Issue 7, July-2013 2286 ISSN 2229-5518 The Role of Data Structures in Multiple Disciplines of Computer Science- A Review N. Shobha Rani, Suman S.P. Abstract— This paper revises the applications of data structures associated with field of computer science and also with great relevance in accomplishing the functions of Operating system and improving the throughput by resource utilization. There is an amount of essential complexity in organizing/processing the data and files present in system. No brute force approaches can minimize and manifest it so easily by adopting to the non-synchronized methodology of storage and management, but it can be placed so that it doesn't get in the way and it's also easy to understand. The best such place is a data structure. Data structures have many applications in the area of system development, data base design, software coding and computer networks. The efficiency of using data structures in performing various operating system jobs are explored in detail with examples. Index Terms—Data structures, operating system, applications, computer science, linear, non-linear. —————————— —————————— 1. INTRODUCTION also to system software like operating system and their ordeal in performing its operational tasks. The data organized with data The heart of a system is its data, which is entered through a structures are processed by means of certain operations. The system’s input, and is subsequently stored in files [1]. Data is decisive action of choosing a particular data structure for a given simply assumed as values or set of values [2], on the other hand in situation depends largely on frequency with which specific database terminology data is also defined as collection of raw operations are performed.
    [Show full text]