Fault localization for data-centric programs

Abstract

In this paper we present an automated technique for localizing faults in data-centric programs. Data-centric programs primarily interact with databases to get collections of content, process each entry in the collection(s), and output another collection or write it back to the database. One or more entries in the output may be faulty. In our approach, we gather the execution trace of a faulty program. We use a novel, precise slicing algorithm to break the trace into multiple slices, such that each slice maps to an entry in the output collection. We then compute the semantic difference between the slices that correspond to correct entries and those that correspond to incorrect ones. The "diff" helps to identify potentially faulty statements.