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Lightweight collection and storage of software repository data with DataRover

机译:使用DataRover轻量级收集和存储软件存储库数据

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The ease of setting up collaboration infrastructures for software engineering projects creates a challenge for researchers that aim to analyze the resulting data. As teams can choose from various available software-as-a-service solutions and can configure them with a few clicks, researchers have to create and maintain multiple implementations for collecting and aggregating the collaboration data in order to perform their analyses across different setups. The DataRover system presented in this paper simplifies this task by only requiring custom source code for API authentication and querying. Data transformation and linkage is performed based on mappings, which users can define based on sample responses through a graphical front end. This allows storing the same input data in formats and databases most suitable for the intended analysis without requiring additional coding. Furthermore, API responses are continuously monitored to detect changes and allow users to update their mappings and data collectors accordingly. A screencast of the described use cases is available at https: //youtu.be/mt4ztff4SfU.
机译:为软件工程项目建立协作基础架构的简便性给旨在分析结果数据的研究人员带来了挑战。由于团队可以从各种可用的软件即服务解决方案中进行选择,并且只需单击几下即可对其进行配置,因此研究人员必须创建并维护用于收集和汇总协作数据的多种实现,以便在不同的设置中执行其分析。本文介绍的DataRover系统仅需要用于API身份验证和查询的自定义源代码即可简化此任务。数据转换和链接基于映射执行,用户可以通过图形前端根据样本响应进行定义。这允许以最适合于预期分析的格式和数据库存储相同的输入数据,而无需其他编码。此外,将连续监视API响应以检测更改,并允许用户相应地更新其映射和数据收集器。 https://youtu.be/mt4ztff4SfU上提供了所描述用例的截屏视频。

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