Capturing custom link semantics among heterogeneous artifacts and tools

Abstract

Automated techniques aid in minimizing the overhead associated with the capture and maintenance of trace links. However, many challenges to automated traceability remain, such as linking heterogeneous artifacts and capturing custom link semantics. In this position paper, we propose a combination of techniques, including prospective link capture, open hypermedia, and rules, in order to address these challenges and complement current automated techniques. Our approach borrows ideas from e-Science, a domain in which tracing data plays a crucial role in the repeatability of experiments.