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Towards a Benchmark for Traceability

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Publication date 2011
Author Charrada Eya Ben, Caspar David, Jeanneret Cédric, Glinz Martin,
Project Managed Software Evolution
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Proceedings (peer-reviewed)

Title of proceedings Joint ERCIM Workshop on Software Evolution and the Int'l Workshop on Principles of SW Evolution
Place Szeged, Hungary
DOI http://dx.doi.org/10.1145/2024445.2024451

Abstract

Rigorously evaluating and comparing traceability link generation techniques is a challenging task. In fact, traceability is still expensive to implement and it is therefore difficult to find a complete case study that includes both a rich set of artifacts and traceability links among them. Consequently, researchers usually have to create their own case studies by taking a number of existing artifacts and creating traceability links for them. There are two major issues related to the creation of one's own example. First, creating a meaningful case study is time consuming. Second, the created case usually covers a limited set of artifacts and has a limited applicability (e.g., a case with traces from high-level requirements to low-level requirements cannot be used to evaluate traceability techniques that are meant to generate links from documentation to source code). We propose a benchmark for traceability that includes all artifacts that are typically produced during the development of a software system and with end-to-end traceability linking. The benchmark is based on an irrigation system that was elaborated in a book about software design. The main task considered by the benchmark is the generation of traceability links among different types of software artifacts. Such a traceability benchmark will help advance research in this field because it facilitates the evaluation and comparison of traceability techniques and makes the replication of experiments an easy task. As a proof of concept we used the benchmark to evaluate the precision and recall of a link generation technique based on the vector space model. Our results are comparable to those obtained by other researchers using the same technique.
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