DFL: Dual-Service Fault Localization

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.