| The success of Open Source Software (OSS) has attracted increased interest in many research areas. Unlike proprietary closed software, OSS projects are developed in a distributed and decentralized way. The OSS community is largely composed of part-time developers. These developers have developed a substantial number of outstanding technical achievements. The behaviors of the developers such as project approval, discussion, evaluation, modification, testing, etc, are mainly achieved by communicating, discussing and consulting with each other on the Internet. Each member can both be user and developer, which can participate in multiple software development simultaneously. The developers' contribution to the project is not only reflected on the software product itself, but also embodied in every procedure of the project. A research study on how OSS developers interact with each other and how projects are developed will help researchers understand the success and failure of OSS projects. OSS developers can also benefit from this research, by being able to make more informed decisions for participating on OSS projects. We observe that crowd-based software developers and users are active in software collaboration development communities and knowledge sharing communities. In the emerging cloud computing era, collaborative software engineering has become an increasingly important approach to serve the urgent needs for mass software services. This dissertation focuses on modeling and analytical methods for interactive behaviors of collaborative software development based on empirical data analysis and data mining. Network intelligence is the enabling technology for this study.The main work and innovation of the paper include the following aspects:1. Address a framework of efficiently mining data from OSS repositories.First of all, after studying main forms of related data of information reflected in the process of the development of OSS on the Internet, the methods of positioning and automatic acquisition of various data which is based on the Internet were given; Then, according to the characteristics of OSS developer data on the Internet, a set of mining framework which can collect the two kinds of data--software development communities and knowledge sharing communities is proposed, The framework can collect, analyze, and acquire OSS development process information and mailing list information automatically,on the basis of which, it also analyzed the developers'behaviors of project participating in open source community,and also in knowledge sharing community. Finally, the feasibility and effectiveness of the framework is verified by experiment. The establishment of the framework helps users choose the right acquisition means of the development process information according to their own needs and the characteristics of the research data.2. Analyze developers'behaviors in OSS community using social network.Using social network analysis method, combined with the specific situation, we analyze developers'interactivity from the macro and micro perspectives. The developers'implicit regularities and rules are studied, including the knowledge sharing behaviors of developers in the community, the project participating behaviors, the contributing behaviors in the process of software development and the maintenance behaviors in the process of software maintenance. Applying these behavior researches to the process, we can optimize the OSS development, meanwhile provide some principles, and then, promote the OSS development efficiency and quality.3. Study the co-evolution of OSS developers and products.Although there exist some software maintenance techniques and tools, developers still play a key role in software maintenance. This study is to extract the relationships among developers and the source code they maintained, including the number of developers, the experience of developers and their impact on software maintenance. At last, we give possible reasons for the formation of the phenomenon. |
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