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Enhancing software fault prediction ...

Rashid, Ekbal, (1976-)

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Enhancing software fault prediction with machine learning = emerging research and opportunities /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Enhancing software fault prediction with machine learning/ by Ekbal Rashid.
Reminder of title:	emerging research and opportunities /
Author:	Rashid, Ekbal,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xiv, 129 p.)
[NT 15003449]:	Chapter 1. Software quality -- Chapter 2. Literature survey and scope of the present work -- Chapter 3. Overview of machine learning approaches -- Chapter 4. Methods of software quality prediction with similarity measures : as an expert system -- Chapter 5. Software quality measures as degree of excellence -- Chapter 6. Understanding the state of quality software -- Chapter 7. Estimation and evaluation of software quality at a particular stage of software development.
Subject:	Software failures - Prevention -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3185-2
ISBN:	9781522531869 (ebook)

Enhancing software fault prediction with machine learning = emerging research and opportunities /
Rashid, Ekbal,1976-

Enhancing software fault prediction with machine learningemerging research and opportunities /[electronic resource] :by Ekbal Rashid. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xiv, 129 p.) - Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series . - Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series..

Includes bibliographical references and index.

Chapter 1. Software quality -- Chapter 2. Literature survey and scope of the present work -- Chapter 3. Overview of machine learning approaches -- Chapter 4. Methods of software quality prediction with similarity measures : as an expert system -- Chapter 5. Software quality measures as degree of excellence -- Chapter 6. Understanding the state of quality software -- Chapter 7. Estimation and evaluation of software quality at a particular stage of software development.

Restricted to subscribers or individual electronic text purchasers.

"This book presents some new ideas about estimation and evaluation of the quality of software and using a standard conversion method so that lines of code from any language may be compared and be used as a uniform metric. It covers different kinds of graphical shapes that may arise out of possible cases and gives their interpretations"--

ISBN: 9781522531869 (ebook)Subjects--Topical Terms:

3311064
Software failures
--Prevention

LC Class. No.: QA76.76.F34 / R37 2018e

Dewey Class. No.: 005.3028/7

Enhancing software fault prediction with machine learning = emerging research and opportunities /
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050 4 $a QA76.76.F34 $b R37 2018e
082 0 4 $a 005.3028/7 $2 23
100 1 $a Rashid, Ekbal, $d 1976- $e author. $3 3311063
245 1 0 $a Enhancing software fault prediction with machine learning $h [electronic resource] : $b emerging research and opportunities / $c by Ekbal Rashid.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xiv, 129 p.)
490 1 $a Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Software quality -- Chapter 2. Literature survey and scope of the present work -- Chapter 3. Overview of machine learning approaches -- Chapter 4. Methods of software quality prediction with similarity measures : as an expert system -- Chapter 5. Software quality measures as degree of excellence -- Chapter 6. Understanding the state of quality software -- Chapter 7. Estimation and evaluation of software quality at a particular stage of software development.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book presents some new ideas about estimation and evaluation of the quality of software and using a standard conversion method so that lines of code from any language may be compared and be used as a uniform metric. It covers different kinds of graphical shapes that may arise out of possible cases and gives their interpretations"-- $c Provided by publisher.
650 0 $a Software failures $x Prevention $x Data processing. $3 3311064
650 0 $a Computer software $x Quality control $x Data processing. $3 3311065
650 0 $a Software maintenance $x Data processing. $3 3311066
650 0 $a Computer system failures. $3 1530720
650 0 $a Computer software $x Reliability. $3 654217
650 0 $a Machine learning. $3 533906
830 0 $a Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series. $3 3311058
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3185-2