BIROn - Birkbeck Institutional Research Online

    Augmenting bug localization with part-of-speech and invocation

    Zhou, Y. and Tong, Y. and Chen, Taolue and Han, J. (2017) Augmenting bug localization with part-of-speech and invocation. International Journal of Software Engineering and Knowledge Engineering 27 (6), pp. 925-950. ISSN 0218-1940.

    This is the latest version of this item.

    [img]
    Preview
    Text
    19656.pdf - Author's Accepted Manuscript

    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.

    Metadata

    Item Type: Article
    Additional Information: Electronic version of an article. © World Scientific Publishing Company
    Keyword(s) / Subject(s): Software engineering, bug localization, information retrieval, bug report
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Dr Taolue Chen
    Date Deposited: 25 Sep 2017 07:51
    Last Modified: 01 Sep 2018 00:10
    URI: http://eprints.bbk.ac.uk/id/eprint/19656

    Available Versions of this Item

    • Augmenting bug localization with part-of-speech and invocation. (deposited 25 Sep 2017 07:51) [Currently Displayed]

    Statistics

    Downloads
    Activity Overview
    12Downloads
    59Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item