Mediating Turf Battles! Prioritizing Shared Modules in Locating Multiple Features

• DOI

Abstract

Dynamic feature location techniques (DFLTs), which use execution profiles of scenarios that trigger a feature, are a promising approach to locating features in the source code. A sufficient set of scenarios is key to obtaining highly accurate results; however, its preparation is laborious and difficult in practice. In most cases, a scenario exercises not only the desired feature but also other features. We focus on the relationship between a module and multiple features that can be calculated with no extra scenarios, to improve the accuracy of locating the desired feature in the source code. In this paper, we propose a DFLT using the odds ratios of the multiple relationships between modules and features. We use the similarity coefficient, which is used in fault localization techniques, as a relationship. Our DFLT better orders shared modules compared with an existing DFLT. To reduce developer costs in our DFLT, we also propose a filtering technique that uses formal concept analysis. We evaluate our DFLT on the features of an open source software project with respect to developer costs and show that our DFLT outperforms the existing approach; the average cost of our DFLT is almost half that of the state-of-the-art DFLT.

BibTeX

@inproceedings{maaki-compsac2017,
    author = {Maaki Nakano and Kunihiro Noda and Shinpei Hayashi and Takashi Kobayashi},
    title = {Mediating Turf Battles! Prioritizing Shared Modules in Locating Multiple Features},
    booktitle = {Proceedings of the 41st IEEE Computer Society Signature Conference on Computers, Software and Applications},
    pages = {363--368},
    doi = {10.1109/COMPSAC.2017.167},
    year = 2017,
}