About this book
This book addresses software faults—a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.
A must-read for readers seeking a “one-stop” source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.
Number of Fault Prediction Ensemble Methods Software Engineering Software Fault Prediction Quality Assurance Testing Soft Computing and Machine Learning Learning Models
- DOI https://doi.org/10.1007/978-981-13-7131-8
- Copyright Information The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019
- Publisher Name Springer, Singapore
- eBook Packages Computer Science Computer Science (R0)
- Print ISBN 978-981-13-7130-1
- Online ISBN 978-981-13-7131-8
- Series Print ISSN 2191-5768
- Series Online ISSN 2191-5776
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