Multi-Feature Fused Software Developer Recommendation
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National Natural Science Foundation of China (61272178, 61572122); National Key Research and Development Program of China (2016YFB1000804)

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    Abstract:

    The capability evaluation and collaborative relationship recommendation of software developers is a hot topic in the field of software intelligent development in big data environment. By analyzing the internet developer community and the enterprise internal development environment, a developer ability model based on fuzzy comprehensive evaluation is designed in this paper. Subsequently, the three different dimensions of the dynamic interaction behavior, static matching, and developer capabilities are extracted by mining the dynamic interaction between the developer and the task. Furthermore, by combining matrix decomposition techniques, a multi-feature fusion enhanced method based on capability and behavior for collaborative filtering developer recommendation is proposed. The method ultimately solves the evaluation matrix sparseness and cold start problem of developer recommendation, and improves the personalized precision recommendation efficiency. From the system level, a prototype of multi feature fusion recommendation system suitable for big data environment is presented, and the optimization of existing open source technology framework is improved. Experiment is conducted based on the internet Q&A community StackOverflow and the internal institution GitLab environment. Finally, the possible issues and ideas for future research are addressed.

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谢新强,杨晓春,王斌,张霞,纪勇,黄治纲.一种多特征融合的软件开发者推荐.软件学报,2018,29(8):2306-2321

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History
  • Received:July 18,2017
  • Revised:September 28,2017
  • Adopted:
  • Online: March 14,2018
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