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When a fault occurs in the field, developers usually collect failure reports that contain function-call traces to uncover the root causes. Fault diagnosis in failure traces is an arduous task due to the volume and size of typical traces. Previously, we have conducted several research studies to diagnose faulty functions in function-call level traces of field failures. During our studies, we have found that different faults in closely related functions occur with similar function-call traces. We also infer from existing studies (including our previous work) that a classification or clustering algorithm can be trained on the function-call traces of a fault in a function and then be used to diagnose different faults in the traces where the same function appears. In this paper, we propose an emerging descriptive theory based on the propositions grounded in these empirical findings. There is scarcity of theorizing empirical findings in software engineering research and our work is a step towards filling this gap. The emerging theory is stated as: a fault in a function can be diagnosed from a function-call trace if the traces of the same or a different fault in that function are already known to a clustering or classification algorithm. We evaluate this theory using the criteria described in the literature. We believe that this emerging theory can help reduce the time spent in diagnosing the origin of faults in field traces.

Towards an emerging theory for the diagnosis of faulty functions in function-call traces