Filtering of false positives from IR-based traceability links among software artifacts

Abstract

Correlation among software artifacts (also known as traceability links) of object oriented software plays a vital role in its maintenance. These traceability links are being commonly identified through Information Retrieval (IR) based techniques. But, it has been found that the resulting links from IR contain many false positives and some complementary approaches have been suggested for the purpose. Still, it usually requires manual verification of links which is neither desirable nor reliable. This paper suggests a new technique which can automatically filter out the false positives links (between requirement and source code) from IR and thus can help in reducing dependence as well as incorrectness of manual verification process. The proposed approach works on the basis of finding correlations among classes using either structural or co-changed dependency or both. A threshold is selected as a cut off on computed dependency values, to accept the presence of structural and co-changed dependency each. Now the traceability links are verified using these dependencies. If atleast one of the structural or co-change information validates the link obtained from IR approach, then that link is selected as candidate link, otherwise removed. Different thresholds have been experimented and comparison of results obtained from IR and the proposed approach is done. The results show that precision increases for all values of thresholds. Further analysis of results indicates that threshold in the range of 0.3 to 0.5 give better results. Hence, the proposed approach can be used as complementary to other Improved IR approaches to filter out false positives.