Traceability among requirements artifacts (and beyond, in certain cases all the way to actual implementation) has long been identified as a critical challenge in industrial practice. Manually establishing and maintaining such traces is a high-skill, labour-intensive job. It is often the case that the ideal person for the job also has other, highly critical tasks to take care of, so offering semi-automated support for the management of traces is an effective way of improving the efficiency of the whole development process. In this paper, we present a technique to exploit the information contained in previously defined traces, in order to facilitate the creation and ongoing maintenance of traces, as the requirements evolve. A case study on a reference dataset is employed to measure the effectiveness of the technique, compared to other proposals from the literature.
Supporting traceability through affinity mining
GERVASI, VINCENZO;
2014-01-01
Abstract
Traceability among requirements artifacts (and beyond, in certain cases all the way to actual implementation) has long been identified as a critical challenge in industrial practice. Manually establishing and maintaining such traces is a high-skill, labour-intensive job. It is often the case that the ideal person for the job also has other, highly critical tasks to take care of, so offering semi-automated support for the management of traces is an effective way of improving the efficiency of the whole development process. In this paper, we present a technique to exploit the information contained in previously defined traces, in order to facilitate the creation and ongoing maintenance of traces, as the requirements evolve. A case study on a reference dataset is employed to measure the effectiveness of the technique, compared to other proposals from the literature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
