In Vivo Evaluation of Large-Scale IR-Based Traceability Recovery

Abstract

Modern large-scale software development is a complex undertaking and coordinating various processes is crucial to achieve efficiency. The alignment between requirements and test activities is one very important aspect. Production and maintenance of software result in an ever-increasing amount of information. To be able to work efficiently under such circumstances, navigation in all available data needs support. Maintaining traceability links between software artifacts is one approach to structure the information space and support this challenge. Many researchers have proposed traceability recovery by applying information retrieval (IR) methods, utilizing the fact that artifacts often have textual content in natural language. Case studies have showed promising results, but no large-scale in vivo evaluations have been made. Currently, there is a trend among our industrial partners to move to a specific new software engineering tool. Their aim is to collect different pieces of information in one system. Our ambition is to develop an IR-based traceability recovery plug-in to this tool. From this position, right in the middle of a real industrial setting, many interesting observations could be made. This would allow a unique evaluation of the usefulness of the IR-based approach.