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Peer code reviews are crucial for maintaining the quality of the code insoftware repositories. Developers have introduced a number of software bots tohelp with the code review process. Despite the benefits of automating codereview tasks, many developers face challenges interacting with these bots dueto non-comprehensive feedback and disruptive notifications. In this paper, weanalyze how incorporating a bot in software development cycle will decreaseturnaround time of pull request. We created a bot called SUGGESTION BOT toautomatically review the code base using GitHub's suggested changesfunctionality in order to solve this issue. A preliminary comparative empiricalinvestigation between the utilization of this bot and manual review procedureswas also conducted in this study. We evaluate SUGGESTION BOT concerning itsimpact on review time and also analyze whether the comments given by the botare clear and useful for users. Our results provide implications for the designof future systems and improving human-bot interactions for code review.

Suggestion Bot: Analyzing the Impact of Automated Suggested Changes on Code Reviews