Title :
Supporting traceability through affinity mining
Author :
Gervasi, Vincenzo ; Zowghi, Didar
Author_Institution :
Dipt. di Inf., Univ. di Pisa, Pisa, Italy
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.
Keywords :
data mining; software maintenance; systems analysis; affinity mining; critical tasks; industrial practice; labour-intensive job; reference dataset; requirements artifacts; semiautomated support; trace establishment; trace maintainance; trace management; traceability support; Context; Joining processes; Maintenance engineering; Pragmatics; Proposals; Semantics; Software;
Conference_Titel :
Requirements Engineering Conference (RE), 2014 IEEE 22nd International
Conference_Location :
Karlskrona
Print_ISBN :
978-1-4799-3031-9
DOI :
10.1109/RE.2014.6912256