Exploratory study of slack Q&A chats as a mining source for software engineering tools

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Abstract

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.

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Chatterjee, P., Damevski, K., Pollock, L., Augustine, V., & Kraft, N. A. (2019). Exploratory study of slack Q&A chats as a mining source for software engineering tools. In IEEE International Working Conference on Mining Software Repositories (Vol. 2019-May, pp. 490–501). IEEE Computer Society. https://doi.org/10.1109/MSR.2019.00075

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