ZHANG Wen, WANG Song, WANG Qing, “BAHA: A Novel Approach to Automatic Bug Report Assignment with Topic Modeling and Heterogeneous Network Analysis,” Chinese Journal of Electronics, vol. 25, no. 6, pp. 1011-1018, 2016, doi: 10.1049/cje.2016.08.012
Citation: ZHANG Wen, WANG Song, WANG Qing, “BAHA: A Novel Approach to Automatic Bug Report Assignment with Topic Modeling and Heterogeneous Network Analysis,” Chinese Journal of Electronics, vol. 25, no. 6, pp. 1011-1018, 2016, doi: 10.1049/cje.2016.08.012

BAHA: A Novel Approach to Automatic Bug Report Assignment with Topic Modeling and Heterogeneous Network Analysis

doi: 10.1049/cje.2016.08.012
Funds:  This work is supported by the National Natural Science Foundation of China (No.71101138, No.61379046, No.61432001), the Beijing Natural Science Fund (No.4122087), the Fundamental Research Fund for the Central Universities in BUCT.
  • Received Date: 2014-11-20
  • Rev Recd Date: 2015-11-19
  • Publish Date: 2016-11-10
  • We propose an approach called Bug report assignment with topic modeling and heterogeneous network analysis (BAHA) to automatically assign bug reports to developers. Existing studies adopt social network analysis to characterize the collaboration of developers. The networks used in these studies are all homogenous. In real practice of bug resolution, different developers collaborate on different bug reports that makes the homogenous network unable to capture this information. We use heterogeneous network to describe the relations between reporters, bug reports and developers to characterize developers' collaboration. Experiments on Eclipse JDT project show that BAHA outperforms the state of art methods on automatic bug report assignment.
  • loading
  • W. He, R. Zhao and Q. Zhu, "Integrating evolutionary testing with reinforcement learning for automated test generation of object-oriented software", Chinese Journal of Electronics, Vol.24, No.1, pp.38-45, 2015.
    E.S. Raymond, The Cathedral and the Bazaar, O'Reilly & Associates, Inc., Cambridge, Massachusetts, USA, 1999.
    C.R. Reis, R.P. de Mattos Fortes, R. Pontin and M. Fortes, "An overview of the software engineering process and tools in the Mozilla project", Proc. of the Open Source Software Development Workshop, pp.155-175, 2002.
    T. Bao, S. Liu and X. Wang, "Research on trustworthiness evaluation method for domain software based on actual evidence", Chinese Journal of Electronics, Vol.20, No.2, pp.195-199, 2011.
    X. Xie, W. Zhang, Y. Yang and Q. Wang, "DRETOM: Developer recommendation based on topic models for bug resolution", Proc. of the 8th International Conference on Predictive Models in Software Engineering, Lund, Sweden, pp.19-28, 2012.
    G. Jeong, S. Kim and T. Zimmermann, "Improving bug triage with bug tossing graphs", Proc. of the 7th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, pp.111-120, 2009.
    D. Cubranic and G.C. Murphy, "Automatic bug triage using text categorization", Proc. of the 16th International Conference on Software Engineering & Knowledge Engineering, pp.92-97, 2004.
    J. Anvik, L. Hiew and G.C. Murphy, "Who should fix this bug?", Proc. of the 28th International Conference on Software Engineering, Shanghai, China, pp.361-370, 2006.
    N. Bettenburg, T. Zimmermann, R. Premraj, S. Just, A. Schröter and C. Weiss., "What makes a good bug report?", IEEE Transactions on Software Engineering, Vol.36, pp.618- 643, 2010.
    P. Hooimeijer and W. Weimer, "Modeling bug report quality", Proc. of the 22nd IEEE/ACM International Conference on Automated Software Engineering, pp.34-43, 2007.
    P.J. Guo, T. Zimmermann, N. Nagappan and B. Murphy, "Not my bug and other reasons for software bug report reassignments", Proc. of the ACM 2011 Conference on Computer Supported Cooperative Work, pp.395-404, 2011.
    S.N. Ahsan, J. Ferzund and F. Wotawa, "Automatic software Bug triage system (BTS) based on latent semantic indexing and support vector machine", Proc. of the 4th International Conference on Software Engineering Advances, pp.216-221, 2009.
    J. Xuan, H. Jiang, Z. Ren and W. Zou, "Developer prioritization in bug repositories", Proc. of the 34th International Conference on Software Engineering, Zurich, Switzerland, pp.25-35, 2012.
    W. Wu, W. Zhang, Y. Yang and Q. Wang, "DREX: Developer recommendation with K-nearest-neighbor search and expertise ranking", Proc. of the 18th Asia-Pacific Software Engineering Conference, pp.389-396, 2011.
    D. Zhang and L. Gao, "Virtual network mapping through locality-aware topological potential and influence node ranking", Chinese Journal of Electronics, Vol.23, No.1, pp.61-64, 2014.
    J. Hopcroft, O. Khan, B. Kulis and B. Selman, "Tracking evolving communities in large linked networks", Proceedings of the National Academy of Sciences, Vol.101, pp.5249-5253, 2004.
    D.M. Blei, A.Y. Ng and M.I. Jordan, "Latent dirichlet allocation", The Journal of Machine Learning Research, Vol.3, pp.993-1022, 2003.
    J. Ouyang, Y. Liu, X. Li and X. Zhou, "Multi-grain sentiment/topic model based on LDA", Acta Electronica Sinica, Vol.43, No.9, pp.1875-1880, 2015. (In Chinese)
    Y. Sun, J. Han, P. Zhao, Z. Yin, H. Cheng and T. Wu, "RankClus: Integrating clustering with ranking for heterogeneous information network analysis", Proc. of the 12th International Conference on Extending Database Technology: Advances in Database Technology, pp.565-576, 2009.
    W. Zhang, Y. Yang and Q. Wang, "Network analysis of OSS evolution: An empirical study on ArgoUML project", Proc. of the 12th International Workshop on Principles of Software Evolution and the 7th Annual ERCIM Workshop on Software Evolution, pp.71-80, 2011.
    X.H. Phan and C.T. Nguyen, "GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation", available at http://gibbslda.sourceforge.net/,2007.
    M. Ji, J. Han and M. Danilevsky, "Ranking-based classification of heterogeneous information networks", Proc. of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.1298-1306, 2011.
    P. Bhattacharya and I. Neamtiu, "Fine-grained incremental learning and multi-feature tossing graphs to improve bug triaging", Proc. of the 26th IEEE International Conference on Software Maintenance, pp.1-10, 2010.
    M. Zhang and Z. Zhou, "ML-KNN: A lazy learning approach to multi-label learning", Pattern Recognition, Vol.40, No.7, pp.2038-2048, 2007.
    L. Jonsson, M. Borg, D. Broman, K. Sandal, S. Eldh and P. Runeson, "Automated bug assignment: Ensemble-based machine learning in large scale industrial contexts", Empirical Software Engineering, pp.1-46, 2015.
    R. Shokripour, J. Anvik, Z.M. Kasirun and S. Zamani, "Why so complicated? Simple term filtering and weighting for locationbased bug report assignment recommendation", Proc. of 10th IEEE Working Conference on Mining Software Repositories, pp.2-11, 2013.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (506) PDF downloads(513) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint