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A GitHub-Based Voice Assistant for Software Developers and Teams

Software developers and teams typically rely on source code and tasks management tools for their projects. They tend to depend on different platforms such as GitHub, Azure DevOps, Bitbucket, and GitLab for task-tracking, feature-tracking, and bug-tracking to develop and maintain their software repositories. Individually, developers may lose concentration when having to navigate through numerous screens consisting of various platforms to perform daily tasks. Additionally, while in meetings (non-virtual), teams are often separate from their machines and often would have to rely on pure recollection of the tasks and issues related to their work. This can delay the decision-making process and take away valuable focus hours of developers. Although there is usually one person with their laptop to guide the meeting and has access to the source code management tools, this can take a lot of time as they are not familiar with all the developers’ independent works. Therefore, a new tool needs to be introduced to help accelerate individual and team meetings’ productivity. In this paper, we continued the work on Robin, a voice-assistant built to answer questions regarding GitHub issues and source code management. Robin has the ability to answer questions in addition to completing actions on the behalf of the developer. This thesis presents Robin's abilities, architecture, and implementation while also examining its usability through a user study. Our study suggests that some people love the idea of having a conversational agent for software development. However, a lot more research and iterations must be done to fully make Robin give the user experience we imagined. In this thesis, we were able to set the foundation of this idea and the lessons that we learned.

Identiferoai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3859
Date01 June 2021
CreatorsSereesathien, Siriwan
PublisherDigitalCommons@CalPoly
Source SetsCalifornia Polytechnic State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMaster's Theses

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