Analyzing Closeness Of Code Dependencies For Improving Ir-Based Traceability Recovery

Information Retrieval (IR) identifies trace links based on textual similarities among software artifacts. However, the vocabulary mismatch problem between different artifacts hinders the performance of IR-based approaches. A growing body of work addresses this issue by combining IR techniques with code dependency analysis such as method calls. However, so far the performance of combined approaches is highly dependent to the correctness of IR techniques and does not take full advantage of the code dependency analysis. In this paper, we combine IR techniques with closeness analysis to improve IR-based traceability recovery. Specifically, we quantify and utilize the "closeness" for each call and data dependency between two classes to improve rankings of traceability candidate lists. An empirical evaluation based on three real-world systems suggests that our approach outperforms three baseline approaches.