Abstract:
Bug localization and feature location in source code are software evolution tasks in which developers use information about a bug or feature present in a software system to locate the source code elements, such as classes or methods. These classes or methods must be modified either to correct the bug or implement a feature. Automating bug localization and feature location are necessary due to the size and complexity of modern software systems. Recently, researchers have developed static bug localization and feature location techniques using information retrieval techniques, such as latent semantic indexing (LSI), to model lexical information, such as identifiers and comments, from source code. This research presents a new technique, LSICG, which combines LSI modeling lexical information and call graphs to modeling structural information. The output is a list of methods ranked in descending order by likelihood of requiring modification to correct the bug or implement the feature under consideration. Three case studies including comparison of LSI and LSICG at method level and class level of granularity on 25 features in JavaHMO, 35 bugs in Rhino, 3 features and 6 bugs in jEdit demonstrate that The LSICG technique provides improved performance compared to LSI alone.
