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Predicting API-Related Faults Using Crowd Knowledge
, Ph.D. Dissertation Sharif University of Technology ; Heydarnoori, Abbas (Supervisor)
Abstract
Software quality assurance activities such as debugging are considered one of the most important and effective tasks in software development life cycle. However, these activities are tedious and time consuming. Consequently, wide variety of studies have been conduced around the process of software debugging, such as predicting defects,which is one of the most important topics in this area.In spite of the popularity of software libraries and frameworks, and the use of application programming interfaces (API), most of the studies in the defect prediction area have not focused on predicting defects related to API usages. However, due to the lack of documentation and complexity of the APIs...