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Streamlining Mutation Testing: A machine learning-driven Approach for Improved Effectiveness

نویسندگان :

Zeinab Asghari¹ Bahman Arasteh² Abbas Koochari³

1- دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران 2- دانشگاه آزاد اسلامی واحد تبریز 3- دانشگاه آزاد اسلامی واحد علوم تحقیقات

کلمات کلیدی :

software testing،mutation testing،equivalent mutants،machine learning،mutation score

چکیده :

The wide variety of bugs that the software takes a look at statistics unearths within the application determines the effectiveness of that check information. A useful approach to assess the effectiveness of a check suite is the mutation take a look at. critical issues associated with mutation testing are value and time required. nearly 40% of the insects injected inside the mutation checking out system are useless (equivalent). Reducing the range of equal mutations and, as a result, lowering the generated mutations and reducing the time of the mutation take a look at are the principle dreams of this treatise. in this look at, seven standard benchmark packages had been examined. On this studies, a mistakes propagation aware mutation check technique is proposed based on machine learning algorithms. Detected instructions are not mutated without propagating an mistakes in the proposed mutation take a look at.