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Exploratory Study of Slack QA Chats as a Mining Source for Software Engineering Tools

机译:Slack问答聊天作为软件工程工具挖掘资源的探索性研究

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Modern software development communities are increasingly social. Popular chat platforms such as Slack host public chat communities that focus on specific development topics such as Python or Ruby-on-Rails. Conversations in these public chats often follow a Q&A format, with someone seeking information and others providing answers in chat form. In this paper, we describe an exploratory study into the potential use-fulness and challenges of mining developer Q&A conversations for supporting software maintenance and evolution tools. We designed the study to investigate the availability of information that has been successfully mined from other developer communications, particularly Stack Overflow. We also analyze characteristics of chat conversations that might inhibit accurate automated analysis. Our results indicate the prevalence of useful information, including API mentions and code snippets with descriptions, and several hurdles that need to be overcome to automate mining that information.
机译:现代软件开发社区变得越来越社会化。流行的聊天平台(例如Slack)托管着公共聊天社区,这些社区专注于特定的开发主题(例如Python或Ruby-on-Rails)。这些公开聊天中的对话通常遵循问答的格式,其中有人寻求信息,而其他人则以对话形式提供答案。在本文中,我们描述了一项探究性研究,探讨了挖掘开发人员Q&A对话以支持软件维护和演化工具的潜在用途和挑战。我们设计了这项研究,以调查从其他开发人员通信(尤其是Stack Overflow)中成功获取的信息的可用性。我们还分析了聊天对话的特征,这些特征可能会妨碍准确的自动分析。我们的结果表明有用信息的普遍性,包括API提及和带有描述的代码段,以及自动挖掘该信息需要克服的几个障碍。

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