Abstract
Code defect detection technology plays an increasingly important role in software testing, but the problem of large number of alarms and high false positive rate is common, thus, the efficiency and difficulty of manual confirmation has seriously hindered the development of this technology. This paper proposes a generation method of dominant alarm, which can effectively reduce the number of the human confirmations and improve validation efficiency. Firstly, by analyzing the feature function of the alarms, the alarms with the same data source can be classified as a collection called 'Equivalent class collection'. Then, the dominant alarm in the equivalent class collection is determined by examining the contextual relationship of the codes where the alarm exits in the collection. Finally, the confirmation of the alarms in the collection can be accomplished by confirming the dominant alarm only. The experiment results show that this method can effectively improve the human conformation efficiency of 20%-30%.
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