{"id":5962,"date":"2021-02-26T00:00:03","date_gmt":"2021-02-25T21:00:03","guid":{"rendered":"https:\/\/www.newworldai.com\/?p=5962"},"modified":"2021-08-03T15:31:18","modified_gmt":"2021-08-03T12:31:18","slug":"deep-learning-based-software-defect-prediction","status":"publish","type":"post","link":"https:\/\/www.newworldai.com\/deep-learning-based-software-defect-prediction\/","title":{"rendered":"Deep learning based software defect prediction"},"content":{"rendered":"
The complexity of modern software systems is increasing, and the resulting software applications often contain defects that can have severe negative impacts on the reliability and robustness of these applications. <\/span><\/strong><\/span><\/p>\n A software defect is commonly defined as a deviation from the software specifications or requirements. Such defects might lead to failures or produce unexpected results. To reduce failures and improve software quality, many software quality assurance activities (e.g., defect prediction, code review and unit testing) are employed. Such activities typically cost approximately 80% of the total budget of a project. To minimize the cost, software engineers want to know which software modules contain more defects and inspect such modules first. As a result, software defect prediction techniques have been proposed.<\/span><\/p>\n Software defect prediction techniques help identify software system modules that are more likely to contain defects. Defect prediction techniques can be used to build models that rank software modules by the predicted number of defects, defect probability, or classification results. This ranked list can reflect the priority for code inspection or unit testing and can thus be used to determine the order in which code should be inspected. Consequently, the developers can allocate the limited test resources to the code areas most likely to contain bugs. The resulting savings in labor and time costs can reduce the overall cost of maintenance activities and maximize company profits.<\/span><\/p>\n