A feature selection model for prediction of software defects
نویسندگان
چکیده
منابع مشابه
A Feature Selection Based Model for Software Defect Prediction
Software is a complex entity composed in various modules with varied range of defect occurrence possibility. Efficient and timely prediction of defect occurrence in software allows software project managers to effectively utilize people, cost, time for better quality assurance. The presence of defects in a software leads to a poor quality software and also responsible for the failure of a softw...
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Recently, software defect prediction is an important research topic in the software engineering field. The accurate prediction of defect prone software modules can help the software testing effort, reduce costs, and improve the software testing process by focusing on fault-prone module. Software defect data sets have an imbalanced nature with very few defective modules compared to defect-free o...
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Feature subset selection is the process of choosing a subset of good features with respect to the target concept. A clustering based feature subset selection algorithm has been applied over software defect prediction data sets. Software defect prediction domain has been chosen due to the growing importance of maintaining high reliability and high quality for any software being developed. A soft...
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Prediction the number of faults in software modules can be more helpful instead of predicting the modules being faulty or non-faulty. Some regression models have been used for predicting the number of faults. However, the software defect data may involve irrelevant and redundant module features, which will degrade the performance of these regression models. To address such issue, this paper pro...
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ژورنال
عنوان ژورنال: International Journal of Embedded Systems
سال: 2020
ISSN: 1741-1068,1741-1076
DOI: 10.1504/ijes.2020.108279