Localising Faults in Test Execution Traces

With the advent of agile processes and their emphasis on continuous integration, automated tests became the prominent driver of the development process. When one of the thousands of tests fails, the corresponding fault should be localised as quickly as possible as development can only proceed when the fault is repaired. In this paper we propose a heuristic named SPEQTRA which mines the execution traces of a series of passing and failing tests, to localise the class which contains the fault. SPEQTRA produces ranking of classes that indicates the likelihood of classes to be at fault. We compare our spectrum based fault localisation heuristic with the state of the art (AMPLE) and demonstrate on a small yet representative case (NanoXML) that the ranking of classes proposed by SPEQTRA is significantly better than the one of AMPLE.