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MSRBot: Using bots to answer questions from software repositories

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Abstract

Software repositories contain a plethora of useful information that can be used to enhance software projects. Prior work has leveraged repository data to improve many aspects of the software development process, such as, help extract requirement decisions, identify potentially defective code and improve maintenance and evolution. However, in many cases, project stakeholders are not able to fully benefit from their software repositories due to the fact that they need special expertise to mine their repositories. Also, extracting and linking data from different types of repositories (e.g., source code control and bug repositories) requires dedicated effort and time, even if the stakeholder has the expertise to perform such a task. Therefore, in this paper, we use bots to automate and ease the process of extracting useful information from software repositories. Particularly, we lay out an approach of how bots, layered on top of software repositories, can be used to answer some of the most common software development/maintenance questions facing developers. We perform a preliminary study with 12 participants to validate the effectiveness of the bot. Our findings indicate that using bots achieves very promising results compared to not using the bot (baseline). Most of the participants (90.0%) find the bot to be either useful or very useful. Also, they completed 90.8% of the tasks correctly using the bot with a median time of 40 seconds per task. On the other hand, without the bot, the participants completed 25.2% of the tasks with a median time of 240 seconds per task. Our work has the potential to transform the MSR field by significantly lowering the barrier to entry, making the extraction of useful information from software repositories as easy as chatting with a bot.

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Notes

  1. Since we gave a maximum of 30 minutes for participants to complete a task, tasks that were not answered after 30 minutes were considered to be incomplete and also to have taken 30 minutes.

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Authors and Affiliations

  1. Data-Driven Analysis of Software (DAS) Lab, Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada

    Ahmad Abdellatif, Khaled Badran & Emad Shihab

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  1. Ahmad Abdellatif
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  2. Khaled Badran
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  3. Emad Shihab
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Correspondence to Ahmad Abdellatif.

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Communicated by: Sven Apel

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Abdellatif, A., Badran, K. & Shihab, E. MSRBot: Using bots to answer questions from software repositories. Empir Software Eng 25, 1834–1863 (2020). https://doi.org/10.1007/s10664-019-09788-5

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