The building of traceability matrices by those other than the original developers is an arduous, error prone, prolonged, and labor intensive task. Thus, after-the-fact requirements tracing is a process where the right kind of automation can definitely assist an analyst. Recently, a number of researchers have studied the application of various methods, often based on information retrieval after-the-fact tracing. The studies are diverse enough to warrant a means for comparing them easily as well as for determining areas that require further investigation. To that end, we present here an experimental framework for evaluating requirements tracing and traceability studies. Common methods, metrics and measures are described. Recent experimental requirements tracing journal and conference papers are catalogued using the framework. We compare these studies and identify areas for future research. Finally, we provide suggestions on how the field of tracing and traceability research may move to a more nature level.
|Number of pages||31|
|Journal||International Journal of Software Engineering and Knowledge Engineering|
|State||Published - Oct 2005|
Bibliographical noteFunding Information:
Our work is funded by NASA under grant NAG5-11732. Our thanks to Ken McGill, Tim Menzies, Stephanie Ferguson, Mike Chapman and the Metrics Data Program, and the MODIS project for maintaining their website that provides such useful data. We also thank our current and former students James Osborne, Senthil Sun-daram, Ganapathy Chidambaram and Sarah Howard for their participation in the requirements tracing research. Without them, this work would not be possible. We also thank Massimiliano di Penta and Jonathan Maletic for enlightening discussions about their research and ours.
- Case study
- Informar tion retrieval
- Requirements tracing; traceability
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Graphics and Computer-Aided Design
- Artificial Intelligence