{"title":"Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review","authors":"Stefano Lambiase, Gemma Catolino, Fabio Palomba, Filomena Ferrucci","doi":"arxiv-2409.11864","DOIUrl":null,"url":null,"abstract":"Bots are software systems designed to support users by automating a specific\nprocess, task, or activity. When such systems implement a conversational\ncomponent to interact with the users, they are also known as conversational\nagents. Bots, particularly in their conversation-oriented version and\nAI-powered, have seen their adoption increase over time for software\ndevelopment and engineering purposes. Despite their exciting potential,\nulteriorly enhanced by the advent of Generative AI and Large Language Models,\nbots still need to be improved to develop and integrate into the development\ncycle since practitioners report that bots add additional challenges that may\nworsen rather than improve. In this work, we aim to provide a taxonomy for\ncharacterizing bots, as well as a series of challenges for their adoption for\nSoftware Engineering associated with potential mitigation strategies. To reach\nour objectives, we conducted a multivocal literature review, reviewing both\nresearch and practitioner's literature. Through such an approach, we hope to\ncontribute to both researchers and practitioners by providing first, a series\nof future research routes to follow, second, a list of strategies to adopt for\nimproving the use of bots for software engineering purposes, and third, enforce\na technology and knowledge transfer from the research field to the\npractitioners one, that is one of the primary goal of multivocal literature\nreviews.","PeriodicalId":501278,"journal":{"name":"arXiv - CS - Software Engineering","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.