A Non-Parametric Statistical Debugging Technique with the Aid of Program Slicing (NPSS)
Автор: Farzaneh Zareie, Saeed Parsa
Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb
Статья в выпуске: 2 vol.5, 2013 года.
Бесплатный доступ
A method is introduced in this paper, which promotes automated bug localization. It is based on the combination of two bug localization techniques, Non-Parametric Statistical Debugging and Backward Slicing. The proposed method, computes some vectors (called execution vectors) based on the status of each basic-block’s execution in running of test-cases. According to the behavior of each basic-block in failed test-cases and passed ones, two likelihoods are computed and regards to them, basic-blocks become prioritized. At last static slice of program and dynamic backward slice for one failed test-case are computed. While seeking for faulty statement in ranked basic-blocks, the method either returns the basic-block’s statements in the static backward slice or the part of it presented in the computed dynamic backward slice. NPSS has been applied on the Siemens test suite, space, grep and gzip. Our experimental study shows the accuracy and effectiveness of the method in accurate bug localization.
Bug, Bug Localization, Program Backward Slicing, Statistical Debugging, Non-Parametric Statistical Relations
Короткий адрес: https://sciup.org/15013173
IDR: 15013173
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