Augmenting bug localization with part-of-speech and invocation

Zhou, Yu, Tong, Yanxiang, Chen, Taolue and Han, Jin (2017) Augmenting bug localization with part-of-speech and invocation. International Journal of Software Engineering and Knowledge Engineering, 27 (06). pp. 925-949. ISSN 0128-1940 (doi:https://doi.org/10.1142/s0218194017500346)

[img]
Preview
PDF - Final accepted version (with author's formatting)
Download (451kB) | Preview

Abstract

Bug localization represents one of the most expensive, as well as time-consuming, activities during software maintenance and evolution. To alleviate the workload of developers, numerous methods have been proposed to automate this process and narrow down the scope of reviewing buggy files. In this paper, we present a novel buggy source-file localization approach, using the information from both the bug reports and the source files. We leverage the part-of-speech features of bug reports and the invocation relationship among source files. We also integrate an adaptive technique to further optimize the performance of the approach. The adaptive technique discriminates Top 1 and Top N recommendations for a given bug report and consists of two modules. One module is to maximize the accuracy of the first recommended file, and the other one aims at improving the accuracy of the fixed defect file list. We evaluate our approach on six large-scale open source projects, i.e. ASpectJ, Eclipse, SWT, Zxing, Birt and Tomcat. Compared to the previous work, empirical results show that our approach can improve the overall prediction performance in all of these cases. Particularly, in terms of the Top 1 recommendation accuracy, our approach achieves an enhancement from 22.73% to 39.86% for ASpectJ, from 24.36% to 30.76% for Eclipse, from 31.63% to 46.94% for SWT, from 40% to 55% for ZXing, from 7.97% to 21.99% for Birt, and from 33.37% to 38.90% for Tomcat.

Item Type: Article
Keywords (uncontrolled): Computer Networks and Communications, Software, Artificial Intelligence, Computer Graphics and Computer-Aided Design
Research Areas: A. > School of Science and Technology > Computer Science > Foundations of Computing group
Item ID: 27175
Notes on copyright: Electronic version of an article published asInternational Journal of Software Engineering and Knowledge Engineering 27 (6), pp. 925-950. https://doi.org/10.1142/S0218194017500346 © copyright World Scientific Publishing Company https://www.worldscientific.com/worldscinet/ijseke
Useful Links:
Depositing User: Jisc Publications Router
Date Deposited: 25 Jul 2019 11:21
Last Modified: 22 Aug 2019 19:09
URI: https://eprints.mdx.ac.uk/id/eprint/27175

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year