Mining expertise of developers from software repositories

被引:0
|
作者
Hammad, Maen [1 ]
Hijazi, Haneen [2 ]
Hammad, Mustafa [3 ]
Otoom, Ahmed Fawzi [1 ]
机构
[1] Hashemite Univ, Dept Software Engn, Zarqa, Jordan
[2] Hashemite Univ, Dept Comp Informat Syst, Zarqa, Jordan
[3] Mutah Univ, Dept Comp Sci, Mutah, Al Karak, Jordan
关键词
software maintenance and evolution; mining software repositories; expertise mining; ASSIGNMENT;
D O I
10.1504/IJCAT.2020.106581
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a technique to mine the developers' contributions to explore their expertise in open source projects. The technique analyses the keywords that appear in the textual content of commits. It is a lightweight technique since the text in commits is analysed without making any syntactic code differencing. Each developer is linked with a list of keywords, with their frequencies, that appeared in his commits. Based on these keywords, three types of expertise are defined: unique, common and frequent. The identified expertise can help in identifying topics or issues that are handled by specific or group of developers. A tool is developed to automatically mine and analyse committed code changes to support expertise identification. A case study is presented on three open source projects to show how the proposed techniques can be applied. The observations of the study showed that frequent terms provide useful information about developers' expertise.
引用
收藏
页码:227 / 239
页数:13
相关论文
共 50 条
  • [41] Predicting the objective and priority of issue reports in software repositories
    Maliheh Izadi
    Kiana Akbari
    Abbas Heydarnoori
    Empirical Software Engineering, 2022, 27
  • [42] Predicting the objective and priority of issue reports in software repositories
    Izadi, Maliheh
    Akbari, Kiana
    Heydarnoori, Abbas
    EMPIRICAL SOFTWARE ENGINEERING, 2022, 27 (02)
  • [43] When and Why Developers Adopt and Change Software Licenses
    Vendome, Christopher
    Linares-Vasquez, Mario
    Bavota, Gabriele
    Di Penta, Massimiliano
    German, Daniel M.
    Poshyvanyk, Denys
    2015 31ST INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME) PROCEEDINGS, 2015, : 31 - 40
  • [44] AI-Powered Knowledge and Expertise Mining in Healthcare from a Field Experiment
    Kauper, Julia
    Franke, Susanne
    Franke, Felix
    Grieshammer, Steven
    FIRST WORKING CONFERENCE ON ARTIFICIAL INTELLIGENCE DEVELOPMENT FOR A RESILIENT AND SUSTAINABLE TOMORROW, AI TOMORROW 2023, 2024, : 37 - 49
  • [45] Fostering Real-Time Software Analysis by Leveraging Heterogeneous and Autonomous Software Repositories
    Wijesiriwardana, Chaman
    Wimalaratne, Prasad
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2018, E101D (11): : 2730 - 2743
  • [46] Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories
    Gonzalez-Barahona, Jesus M.
    Robles, Gregorio
    INFORMATION AND SOFTWARE TECHNOLOGY, 2023, 164
  • [47] Mining student repositories to gain learning analytics An experience report
    Robles, Gregorio
    Gonzalez-Barahona, Jesus M.
    2013 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE (EDUCON), 2013, : 1249 - 1254
  • [48] CVExplorer: Identifying Candidate Developers by Mining and Exploring Their Open Source Contributions
    Greene, Gillian J.
    Fischer, Bernd
    2016 31ST IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE), 2016, : 804 - 809
  • [49] Assessment of Approaches for the Analysis of Refactoring Activity on Software Repositories An Empirical Study
    Orru, Matteo
    Marchesi, Michele
    PROCEEDINGS OF THE XP2016 SCIENTIFIC WORKSHOPS, 2016,
  • [50] A segmentation-based approach for temporal analysis of software version repositories
    Siy, Harvey
    Chundi, Parvathi
    Rosenkrantz, Daniel J.
    Subramaniam, Mahadevan
    JOURNAL OF SOFTWARE MAINTENANCE AND EVOLUTION-RESEARCH AND PRACTICE, 2008, 20 (03): : 199 - 222