Using PageRank to Reveal Relevant Issues to Support Decision-Making on Open Source Projects
作者： Alessandro Caetano , Leonardo Leite , Paulo Meirelles , Hilmer Neri , Fabio Kon
DOI: 10.1007/978-3-319-92375-8_9
关键词:
摘要: Software release planning is crucial to software projects that adopt incremental development. Open source depend on their globally distributed maintainers’ communities who share project information, usually described in the repository as issues, plan contents and timing of next releases. This paper introduces an approach based issues support decision-making regarding open development activities such retrospectives. It uses PageRank algorithm suggest importance ranking dependencies topology. When a highly connected topology, leaders can use this rank input activities. The observation two indicates feasibility our approach.
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