摘要:软件开发过程中，同一代码文件经常由多名开发者共同开发和维护，各个开发者向文件贡献了不同的代码量，使之形成特有的贡献组成.代码文件的贡献组成是否合理，直接影响开发者的任务分配，进而影响软件质量和开发效率.对于不同类型的代码文件，如何刻画并确定其合理的贡献组成模式，成为一个亟待解决的问题.协同开发支撑工具的成熟，使得开发人员的活动可被有效地记录，因此，其所产生的海量数据为数据驱动的智能化软件开发打下了基础.首先，基于代码所有权，从贡献组成的集中度、复杂度和稳定性这3个维度出发，提出刻画贡献组成的3个量度；其次，以OpenStack的核心项目Nova为研究案例，在其版本控制数据上建立贡献组成的量度，总结了12种通用文件类型，归纳出3种贡献组成模式；最后，结合邮件以及面对面访谈的方式，验证了量度的有效性以及贡献组成模式的合理性，并从贡献组成的角度，对软件开发过程给出了一些指导性建议.



Abstract:In the process of software development, one code file is often developed and maintained by more than one developer and each developer contributes different amount of code to the file, which forms a unique contribution composition. Whether the contribution of the code file is reasonable or not directly affects the task allocation, which in turn affects the quality of software and development efficiency. For different types of code files, how to measure and determine their contribution composition becomes an urgent problem to be solved. Due to the maturity of supporting tools in collaborative development, the activities of developers can be recorded effectively. Therefore, the huge amount of data generated by developers lays the foundation for data-driven intelligent software development. Firstly in this paper, based on code ownership, a set of metrics is established to describe the contribution composition of code files from the three dimensions:concentration, complexity and stability. Secondly, taking Nova (one of the OpenStack' core projects) as a case study with its' version control data and metrics, a measure of contribution composition is established to summarize 12 common file types, resulting in 3 contribution composition patterns. Finally, the validity of the metrics and the rationality of contribution composition patterns are verified by combining mail-in and in-person interviews, and some instructive suggestions for software development process are presented.



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