Modern Information Retrieval
Locating Features in Source Code
IEEE Transactions on Software Engineering
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
SNIAFL: Towards a static noninteractive approach to feature location
ACM Transactions on Software Engineering and Methodology (TOSEM)
IEEE Transactions on Software Engineering
ASE '08 Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering
Improving feature location using structural similarity and iterative graph mapping
Journal of Systems and Software
Hi-index | 0.00 |
Locating the program element(s) relevant to a particular feature is an important step in efficient maintenance of a software system. The existing feature location techniques analyze each feature independently and perform a one-time analysis after being provided an initial input. As a result, these techniques are sensitive to the quality of the input, and they tend to miss the nonlocal interactions among features. In this paper, we propose to address the proceeding two issues in feature location using an iterative context-aware approach. The underlying intuition is that the features are not independent of each other, and the structure of source code resembles the structure of features. The distinguishing characteristics of the proposed approach are: 1) it takes into account the structural similarity between a feature and a program element to determine their relevance; 2) it employs an iterative process to propagate the relevance of the established mappings between a feature and a program element to the neighboring features and program elements. Our initial evaluation suggests the proposed approach is more robust and can significantly increase the recall of feature location with a slight decrease in precision.