DFL : Dual-Service Fault Localization

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Software Quality, Reliability and Security, QRS 2016
PublisherIEEE
Pages412-422
ISBN (Print)9781509041275
Publication statusPublished - 12 Oct 2016

Conference

Title2nd IEEE International Conference on Software Quality, Reliability and Security, QRS 2016
PlaceAustria
CityVienna
Period1 - 3 August 2016

Abstract

In engineering a service, software developers often construct and deploy a newer (forthcoming) version of the service to replace the current version. A forthcoming version is often placed online for users to consume and report feedback. In the case of observed failures, the forthcoming version should be debugged and further evolved. In this paper, we propose the model of dual-service fault localization (DFL) to aid this evolution process. Many prior research studies on spectrum-based fault localization (SBFL) consider each version separately. The DFL model correlates the dynamic execution spectra of the current and the forthcoming versions of the same service placed for live test of the forthcoming version, and dynamically generates an adaptive fault localization formula to estimate the code regions in the forthcoming service responsible for the observed failures. We report an experiment in which we initialized the DFL model into six instances, each using an ensemble technique dynamically composed from 11 existing SBFL formulas, and applied the model to four benchmarks. The results show that DFL is feasible and multiple instances are statistically more effective than, if not as effective as, the best of these individual SBFL formulas on each benchmark.

Research Area(s)

  • debugging, dual-service fault localization, ensemble techniques, spectrum-based fault localization

Citation Format(s)

DFL : Dual-Service Fault Localization. / Tang, C. M.; Keung, Jacky; Yu, Y. T.; Chan, W. K.

Proceedings - 2016 IEEE International Conference on Software Quality, Reliability and Security, QRS 2016. IEEE, 2016. p. 412-422 7589821.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)