hrcak mascot   Srce   HID

Journal of Communications Software and Systems, Vol.13 No.4 Prosinac 2017.

Izvorni znanstveni članak
https://doi.org/10.24138/jcomss.v13i4.402

Graph Mining for Software Fault Localization: An Edge Ranking based Approach

Marwa Gaber Abd El-Wahab ; Faculty of Computers and Information, Helwan University, Egypt
Amal Elsayed Aboutabl   ORCID icon orcid.org/0000-0002-7189-9274 ; Faculty of Computers and Information, Helwan University, Egypt
Wessam M.H. EL Behaidy ; Faculty of Computers and Information, Helwan University, Egypt

Puni tekst: engleski, pdf (1 MB) str. 178-188 preuzimanja: 186* citiraj
APA 6th Edition
Gaber Abd El-Wahab, M., Aboutabl, A.E. i EL Behaidy, W.M.H. (2017). Graph Mining for Software Fault Localization: An Edge Ranking based Approach. Journal of Communications Software and Systems, 13 (4), 178-188. https://doi.org/10.24138/jcomss.v13i4.402
MLA 8th Edition
Gaber Abd El-Wahab, Marwa, et al. "Graph Mining for Software Fault Localization: An Edge Ranking based Approach." Journal of Communications Software and Systems, vol. 13, br. 4, 2017, str. 178-188. https://doi.org/10.24138/jcomss.v13i4.402. Citirano 16.12.2018.
Chicago 17th Edition
Gaber Abd El-Wahab, Marwa, Amal Elsayed Aboutabl i Wessam M.H. EL Behaidy. "Graph Mining for Software Fault Localization: An Edge Ranking based Approach." Journal of Communications Software and Systems 13, br. 4 (2017): 178-188. https://doi.org/10.24138/jcomss.v13i4.402
Harvard
Gaber Abd El-Wahab, M., Aboutabl, A.E., i EL Behaidy, W.M.H. (2017). 'Graph Mining for Software Fault Localization: An Edge Ranking based Approach', Journal of Communications Software and Systems, 13(4), str. 178-188. doi: https://doi.org/10.24138/jcomss.v13i4.402
Vancouver
Gaber Abd El-Wahab M, Aboutabl AE, EL Behaidy WMH. Graph Mining for Software Fault Localization: An Edge Ranking based Approach. Journal of Communications Software and Systems [Internet]. 2017 [pristupljeno 16.12.2018.];13(4):178-188. doi: https://doi.org/10.24138/jcomss.v13i4.402
IEEE
M. Gaber Abd El-Wahab, A.E. Aboutabl i W.M.H. EL Behaidy, "Graph Mining for Software Fault Localization: An Edge Ranking based Approach", Journal of Communications Software and Systems, vol.13, br. 4, str. 178-188, 2017. [Online]. doi: https://doi.org/10.24138/jcomss.v13i4.402

Sažetak
Fault localization is considered one of the most challenging activities in the software debugging process. It is vital to guarantee software reliability. Hence, there has been a great demand for automated methods that can pinpoint faults for software developers. Various fault localization techniques that are based on graph mining have been proposed in the literature. These techniques rely on detecting discriminative sub-graphs between failing and passing traces. However, these approaches may not be applicable when the fault does not appear in a discriminative pattern. On the other hand, many approaches focus on selecting potentially faulty program components (statements or predicates) and then ranking these components according to their degree of suspiciousness. One of the difficulties encountered by such approaches is to understand the context of fault occurrence. To address these issues, this paper introduces an approach that helps in analyzing the context of execution traces based on control flow graphs. The proposed approach uses the edge-ranking of basic blocks in software programs using Dstar that proved to be more effective than many fault localization techniques. The proposed method helps in detecting some types of faults that could not be previously detected by many other approaches. Using Siemens benchmark, experiments show the effectiveness of the proposed technique compared to some well-known approaches such as Dstar, Tarantula, SOBER, Cause Transition and Liblit05. The percentage of localized faulty versions versus the percentage of code examined is taken as a measure. For instance, when the percentage of examined code is 30%, the proposed technique can localize nearly 81% of the faulty versions, which outperforms the other four techniques.

Ključne riječi
Bug localization; basic block; control flow graph; edge – ranking

Hrčak ID: 191337

URI
https://hrcak.srce.hr/191337

Posjeta: 281 *