ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2016, Vol. 53 ›› Issue (12): 2768-2782.doi: 10.7544/issn1000-1239.2016.20160653

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  1. (大连理工大学软件学院 辽宁大连 116024) (
  • 出版日期: 2016-12-01
  • 基金资助: 

Mining Software Repositories: Contributors and Hot Topics

Jiang He, Chen Xin, Zhang Jingxuan, Han Xuejiao,Xu Xiujuan   

  1. (School of Software, Dalian University of Technology, Dalian, Liaoning 116024)
  • Online: 2016-12-01

摘要: 随着时间的推移,软件不断地更新和演化,软件仓库中累积了海量的数据,如何有效地收集、组织、利用软件工程中涌现的软件大数据是一个至关重要的问题.软件仓库挖掘(mining software repositories, MSR)通过挖掘软件仓库中繁杂多变的数据中蕴含的知识来提高软件的质量和生产效率.虽然一些研究工作详细阐述了MSR的背景、历史和前景,但现有的研究工作并未系统地呈现MSR领域中最有影响力的作者、机构、国家以及最受欢迎的研究主题和主题变迁等领域知识.因此,结合已有的经典的文献分析框架和算法来分析MSR相关文献,并呈现一些MSR基本领域知识.为了实现MSR 文献分析,建立了一个包含3个组件的MSR文献分析框架(MSR publication analysis framework, MSR-PAF),这3个组件分别被用来创建数据集、执行基础文献分析、实施合作模式分析.基础文献分析结果表明:最高产的作者、机构、国家地区分别是Ahmed E. Hassan,University of Victoria和美国,最有影响力作者是Ahmed E. Hassan,最频繁的关键词是software maintenance.合作模式分析的结果显示Abram Hindle是MSR领域最活跃的作者,open source project和software maintenance是最流行的研究主题.

关键词: 文献分析, 合作模式分析, 数据挖掘, 软件仓库挖掘, 大数据

Abstract: Software updates and evolves continuously over time, software repositories accumulate massive data. How to effectively collect, organize, and make use of these data has become a key problem in software engineering. Mining Software Repositories (MSR) aim to mine useful knowledge contained in complex and diversified data to improve the quality and productivity of software. Although some studies have elaborately summarized the background, history, and prospects about MSR, existing studies do not present systematically the most influential author, institution, and country as well as the major research topics and their transitions over time. Therefore, this study combines the existing classical publication analysis frameworks and algorithms to analyze the relationships among publications related to MSR, and presents some important domain knowledge for researchers in detail. To effectively tackle this task, we construct a framework named MSR Publication Analysis Framework (MSR-PAF). MSR-PAF consists of three components which can be used to create a dataset for the study, conduct a bibliography analysis, and implement a collaboration pattern analysis, respectively. The results of the bibliography analysis show that the most productive author, institution, and country are Ahmed E. Hassan, University of Victoria, and USA, respectively. The most frequent keyword is software maintenance and the most influential author is Abram Hindle. In addition, the results of the collaboration pattern analysis show that Abram Hindle is the most active author, and open source project and software maintenance are the most popular research topics.

Key words: publication analysis, collaboration pattern analysis, data mining, mining software repositories, big data