Abstract
Software metrics have direct linkage with software quality and defect. Thus, for a software engineer, it becomes very hard to estimate the software quality and provide product assurance to the client. Most of the software becomes failure due to several kinds of defects. The software industry uses different kinds of software models such as SDLC for software product development, and it becomes very difficult to choose the correct software model for software development. The objective of this chapter is to show how we can use machine learning and data mining for software defect, quality and software model prediction. We analyse different kinds of machine learning algorithms for application in software engineering domain. This chapter reviews the various classifications used to predict software defects using software measurements in the literature. In this chapter, we perform a detailed analysis of application of data mining and machine learning approaches used for software quality, defect and quality analysis.
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