The potential of omniscient debugging for aspect-oriented programming languages
Proceedings of the 1st workshop on Comprehension of complex systems
MZoltar: automatic debugging of Android applications
Proceedings of the 2013 International Workshop on Software Development Lifecycle for Mobile
HSFal: Effective fault localization using hybrid spectrum of full slices and execution slices
Journal of Systems and Software
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Effective debugging is crucial to producing dependable software. Manual debugging is becoming prohibitively expensive, especially due to the growing size and complexity of programs. Given that fault localization is one of the most expensive activities in program debugging, there has been a great demand for fault localization techniques that can help guide programmers to the locations of faults. In this paper a technique named DStar (D*), which has its origins rooted in similarity coefficient-based analysis, is proposed, which can identify suspicious locations for fault localization automatically without requiring any prior information on program structure or semantics. D* is evaluated across 21 programs and is compared to 16 different fault localization techniques. Both single-fault and multi-fault programs are used. Results indicate that D* is more effective at locating faults than all the other techniques it is compared to.