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Defect prediction approaches use software metrics and fault data to learn which software properties are associated with what kinds of software faults in programs. One trend of existing techniques is to predict the software defects in a program construct (file, class, method, and so on) rather than in a specific function scenario, while the latter is important for assessing software quality and tracking...
Defects in every software must be handled properly, and the number of defects directly reflects the quality of a software. In recent years, researchers have applied data mining and machine learning methods to predicting software defects. However, in their studies, the method in which the machine learning models are directly adopted may not be precise enough. Optimizing the machine learning models...
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