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Enhancing software fault prediction ...
~
Rashid, Ekbal, (1976-)
Enhancing software fault prediction with machine learning : = emerging research and opportunities /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Enhancing software fault prediction with machine learning :/ Ekbal Rashid.
其他題名:
emerging research and opportunities /
作者:
Rashid, Ekbal,
出版者:
Hershey, PA :Engineering Science Reference, : c2018.,
面頁冊數:
xiv, 129 p. :ill. ; : 27 cm.;
附註:
"Research insights"--Cover.
標題:
Machine learning. -
ISBN:
9781522531852 :
Enhancing software fault prediction with machine learning : = emerging research and opportunities /
Rashid, Ekbal,1976-
Enhancing software fault prediction with machine learning :
emerging research and opportunities /Ekbal Rashid. - Hershey, PA :Engineering Science Reference,c2018. - xiv, 129 p. :ill. ;27 cm. - Advances in systems analysis, software engineering, and high performance computing (ASASEHPC) book series.
"Research insights"--Cover.
Includes bibliographical references (p. 108-127) and index.
Software quality -- Literature survey and scope of the present work -- Overview of machine learning approaches -- Methods of software quality prediction with similarity measures : as an expert system -- Software quality measures as degree of excellence -- Understanding the state of quality software -- Estimation and evaluation of software quality at a particular stage of software development -- Conclusions and future work.
"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: 9781522531852 :NT4958
LCCN: 2017015192Subjects--Topical Terms:
561253
Machine learning.
LC Class. No.: QA76.76.F34 / R37 2018
Dewey Class. No.: 005.3028/7
Enhancing software fault prediction with machine learning : = emerging research and opportunities /
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Software quality -- Literature survey and scope of the present work -- Overview of machine learning approaches -- Methods of software quality prediction with similarity measures : as an expert system -- Software quality measures as degree of excellence -- Understanding the state of quality software -- Estimation and evaluation of software quality at a particular stage of software development -- Conclusions and future work.
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