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Enhancing software fault prediction ...
~
Rashid, Ekbal, (1976-)
Enhancing software fault prediction with machine learningemerging research and opportunities /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Enhancing software fault prediction with machine learningby 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.)
Subject:
Software failuresPrevention
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 learningemerging research and opportunities /
Rashid, Ekbal,1976-
Enhancing software fault prediction with machine learning
emerging 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:
808097
Software failures
--Prevention
LC Class. No.: QA76.76.F34 / R37 2018e
Dewey Class. No.: 005.3028/7
Enhancing software fault prediction with machine learningemerging research and opportunities /
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Enhancing software fault prediction with machine learning
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[electronic resource] :
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emerging research and opportunities /
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by Ekbal Rashid.
260
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Hershey, Pennsylvania :
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IGI Global,
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[2018]
300
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1 online resource (xiv, 129 p.)
490
1
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Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series
504
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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"--
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Provided by publisher.
650
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Software failures
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Prevention
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Data processing.
$3
808097
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Computer software
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Quality control
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Data processing.
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808098
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Software maintenance
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Data processing.
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808099
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Computer system failures.
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Computer software
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Reliability.
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650
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Machine learning.
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Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series.
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808091
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3185-2
based on 0 review(s)
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電子館藏
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EB QA76.76.F34 R37 2018
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1 records • Pages 1 •
1
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-3185-2
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