چکیده مقاله
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
کلیدواژهها
نویسندگان
Zeinab Asghari
Science and Research Branch, Islamic Azad University, Tehran, Iran;
Bahman Arasteh
Tabriz Branch, Islamic Azad University, Tabriz, Iran;
Abbas Koochari
Science and Research Branch, Islamic Azad University, Tehran, Iran;
شیوه ارجاع
Asghari, Zeinab and Arasteh, Bahman and Koochari, Abbas,1402,Streamlining Mutation Testing: A machine learning-driven Approach for Improved Effectiveness,5th International Conference on Software Computing,Rudsar
ارائهشده در
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