Article ID Journal Published Year Pages File Type
549822 Information and Software Technology 2014 20 Pages PDF
Abstract

ContextThe intensive human effort needed to manually manage traceability information has increased the interest in using semi-automated traceability recovery techniques. In particular, Information Retrieval (IR) techniques have been largely employed in the last ten years to partially automate the traceability recovery process.AimPrevious studies mainly focused on the analysis of the performances of IR-based traceability recovery methods and several enhancing strategies have been proposed to improve their accuracy. Very few papers investigate how developers (i) use IR-based traceability recovery tools and (ii) analyse the list of suggested links to validate correct links or discard false positives. We focus on this issue and suggest exploiting link count information in IR-based traceability recovery tools to improve the performances of the developers during a traceability recovery process.MethodTwo empirical studies have been conducted to evaluate the usefulness of link count information. The two studies involved 135 University students that had to perform (with and without link count information) traceability recovery tasks on two software project repositories. Then, we evaluated the quality of the recovered traceability links in terms of links correctly and erroneously traced by the students.ResultsThe results achieved indicate that the use of link count information significantly increases the number of correct links identified by the participants.ConclusionsThe results can be used to derive guidelines on how to effectively use traceability recovery approaches and tools proposed in the literature.

Related Topics
Physical Sciences and Engineering Computer Science Human-Computer Interaction
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