TaskAllocator：敏捷软件开发中基于角色的任务分配推荐方法
TaskAllocator: A Recommendation Approach for Role-based Tasks Allocation in Agile Software Development
摘要：
在本文中，我们提出了一个推荐方法-- TaskAllocator --以预测传入的任务分配给潜在的合适的角色。建议的方法，确定团队的角色，而不是个人，允许项目经理执行更好的任务分配的情况下，个人开发人员被过度使用或转移到不同的角色/项目。我们对从Taiga.io资源库中获得的10个敏捷案例研究项目进行了评估。为了确定TaskAllocator的性能，我们通过将其与当代机器学习模型进行比较来进行基准研究。TaskAllocator的适用性通过一个插件进行了评估，该插件可以与JIRA集成，并在项目中添加新任务时提供有关合适角色的建议。最后，插件的源代码和所使用的数据集已经公开。
英文摘要：
In this paper, we propose a recommendation approach -- TaskAllocator -- in order to predict the assignment of incoming tasks to potential befitting roles. The proposed approach, identifying team roles rather than individual persons, allows project managers to perform better tasks allocation in case the individual developers are over-utilized or moved on to different roles/projects. We evaluated our approach on ten agile case study projects obtained from the Taiga.io repository. In order to determine the TaskAllocator's performance, we have conducted a benchmark study by comparing it with contemporary machine learning models. The applicability of the TaskAllocator was assessed through a plugin that can be integrated with JIRA and provides recommendations about suitable roles whenever a new task is added to the project. Lastly, the source code of the plugin and the dataset employed have been made public.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
