Titlebook: Software Fault Prediction; A Road Map Sandeep Kumar,Santosh Singh Rathore Book 2018 The Author(s) 2018 Software Engineering.Software Fault

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Evaluation of Techniques for the Prediction of Number of Faults,e development resources. The binary class classification of the software faults provides useful hints about the fault-proneness of the software modules. However, having the faulty or non-faulty information only about the software modules is not sufficient, when we need to prioritize the software tes

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Introduction,atching with the quality specifications and is reliable to use. The quality of the software determines its value and reliability ensures the failure-free operation of software for a specified period of time in the given environmental conditions. Quality and reliability of the software depend on the software faults.

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Software Fault Dataset, of reasonable quality fault data. However, obtaining quality software fault data is difficult as in general software development companies are not keen to share their software development information or they are not having any software repository in first place.

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Book 2018g chapters: Chapter 1 presents an introduction to the study and also introduces basic concepts of software fault prediction. Chapter 2 explains the generalized architecture of the software fault prediction process and discusses its various components. In turn, Chapter 3 provides detailed information

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Evaluation of Techniques for Binary Class Classification,ults. In this type of prediction, if a given software module has one or more faults, then it is classified as faulty; otherwise, it is classified as non-faulty. Most the studies available in the literature related to the software fault prediction have focused on the binary class classification of software faults.

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