A critical evaluation of spectrum-based fault localization techniques on a large-scale software system
Conference Proceeding Article
In the past, spectrum-based fault localization (SBFL) techniques have been developed to pinpoint a fault location in a program given a set of failing and successful test executions. Most of the algorithms use similarity coefficients and have only been evaluated on established but small benchmark programs from the Software-artifact Infrastructure Repository (SIR). In this paper, we evaluate the feasibility of applying 33 state-of-the-art SBFL techniques to a large real-world project, namely ASPECTJ. From an initial set of 350 faulty version from the iBugs repository of ASPECTJ we manually classified 88 bugs where SBFL techniques are suitable. Notably, only 11 bugs of these bugs can be found after examining the 1000 most suspicious lines and on average 250 source code files need to be inspected per bug. Based on these results, the study showcases the limitations of current SBFL techniques on a larger program.
Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)
City or Country
Prague; Czech Republic
KELLER, Fabian; GRUNSKE, Lars; HEIDEN, Simon; FILIERI, Antonio; HOORN, Andre Van; and LO, David.
A critical evaluation of spectrum-based fault localization techniques on a large-scale software system. (2017). Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS). Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3837
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