  Peer code reviews are crucial for maintaining the quality of the code in
software repositories. Developers have introduced a number of software bots to
help with the code review process. Despite the benefits of automating code
review tasks, many developers face challenges interacting with these bots due
to non-comprehensive feedback and disruptive notifications. In this paper, we
analyze how incorporating a bot in software development cycle will decrease
turnaround time of pull request. We created a bot called SUGGESTION BOT to
automatically review the code base using GitHub's suggested changes
functionality in order to solve this issue. A preliminary comparative empirical
investigation between the utilization of this bot and manual review procedures
was also conducted in this study. We evaluate SUGGESTION BOT concerning its
impact on review time and also analyze whether the comments given by the bot
are clear and useful for users. Our results provide implications for the design
of future systems and improving human-bot interactions for code review.
