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World Journal of Engineering
Research and Technology

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

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Indexing

Abstract

A REVIEW ON SOFTWARE DEFECT PREDICTION USING DATA MINING TECHNIQUES

*Rakesh Kumar and Dr. Dharmendra Chourishi

ABSTRACT

The common software problems appear in a wide variety of applications and environments. Some software related problems arises in software project development i.e. software related problems are known as software defect in which Software bug is a major problem arises in the coding implementation. Software defect prediction has been one of the key areas of exploration in the domain of software quality. The ability of a model to learn from data that does not come from the same project or organization will help organizations that do not have sufficient training data or are going to start work on new projects. The findings of this research are useful not only to the software engineering domain, but also to the empirical studies, which mainly focus on symmetry as they provide steps-by-steps solutions for questions raised in the article. A typical software development process has several stages; each with its own significance and dependency on the other. Each stage is often complex and generates a wide variety of data. Using data mining techniques, Hidden patterns can be uncovered from this data, which measure the impact of each stage on the other and gather useful information to improve the software development process. The insights gained from the extracted knowledge patterns can help software engineers to predict, plan and comprehend the various intricacies of the project, allowing them to optimize future software development activities. As every stage in the development process entails a certain outcome or goal, it becomes crucial to select the best data mining techniques to achieve these goals efficiently.

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