Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review
<|reference_start|>Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review: Bots are software systems designed to support users by automating a specific process, task, or activity. When such systems implement a conversational component to interact with the users, they are also known as conversational agents. Bots, particularly in their conversation-oriented version and AI-powered, have seen their adoption increase over time for software development and engineering purposes. Despite their exciting potential, ulteriorly enhanced by the advent of Generative AI and Large Language Models, bots still need to be improved to develop and integrate into the development cycle since practitioners report that bots add additional challenges that may worsen rather than improve. In this work, we aim to provide a taxonomy for characterizing bots, as well as a series of challenges for their adoption for Software Engineering associated with potential mitigation strategies. To reach our objectives, we conducted a multivocal literature review, reviewing both research and practitioner's literature. Through such an approach, we hope to contribute to both researchers and practitioners by providing first, a series of future research routes to follow, second, a list of strategies to adopt for improving the use of bots for software engineering purposes, and third, enforce a technology and knowledge transfer from the research field to the practitioners one, that is one of the primary goal of multivocal literature reviews.<|reference_end|>
@article{lambiase2024motivations,,
    title={Motivations, Challenges, Best Practices, and Benefits for Bots and
  Conversational Agents in Software Engineering: A Multivocal Literature Review},
    author={Stefano Lambiase, Gemma Catolino, Fabio Palomba, Filomena Ferrucci},
    journal={arXiv preprint arXiv:2409.11864},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.11864},
    primaryClass={cs.SE}
}