Mutation-aware fault prediction
作者： David Bowes , Tracy Hall , Mark Harman , Yue Jia , Federica Sarro
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摘要: We introduce mutation-aware fault prediction, which leverages additional guidance from metrics constructed in terms of mutants and the test cases that cover detect them. report results 12 sets experiments, applying 4 different predictive modelling techniques to 3 large real-world systems (both open closed source). The show our proposal can significantly (p ≤ 0.05) improve prediction performance. Moreover, mutation-based lie top 5% most frequently relied upon predictors 10 provide majority ten 9 experiments.
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