A Survey-driven Feature Model for Software Traceability Approaches

Abstract

Traceability is the capability to represent, understand and analyze the relationships between software artefacts. Traceability is at the core of many software engineering activities. This is a blessing in disguise as traceability research is scattered among various research subfields, which impairs a global view and integration of the different innovations around the recording, identification, evaluation and management of traces. This also limits the adoption of traceability solutions in industry. In this sense, the goal of this paper is to present a characterization of the traceability mechanism as a feature model depicting the shared and variable elements in any traceability proposal. The features in the model are derived from a survey of papers related to traceability published in the literature. We believe this feature model is useful to assess and compare different proposals and provide a common terminology and background. Beyond the feature model, the survey we conducted also help us to identify a number of challenges to be solved in order to move traceability forward, especially in a context where, due to the increasing importance of AI techniques in Software Engineering, traces are more important than ever in order to be able to reproduce and explain AI decisions.