Abstract
STUDY ON SOFTWARE DEFECT PREDICTION USING DATA MINING TECHNIQUES
*Rakesh Kumar, Dr. Dharmendra Chourishi, Prof. Anurag Srivastava
ABSTRACT
Software defect prediction has been one of the key areas of exploration in the domain of software quality. Software bug is a major problem arises in the coding implementation .There are no satisfied result found by project development team. The software bug problems mentationed in problem report and software engineer does not easily detect this software defect but by the help of data mining classification software engineers can easily classify software bug. The challenges encountered are difficulty in separating correct theories from the incorrect ones when the purpose of evaluation is in practice and difficulties in the identification of quality literature from quality lacking literature. Using data mining techniques, one can uncover hidden patterns from this data, 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. It has been also discussed that how data mining improves the software development process in terms of time, cost, resources, reliability and maintainability.
[Full Text Article] [Download Certificate]