Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Stefano Lambiase, Gemma Catolino, Fabio Palomba, Filomena Ferrucci
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引用次数: 0

Abstract

Bots are software systems designed to support users by automating specific processes, tasks, or activities. When these systems implement a conversational component to interact with users, they are also known as conversational agents or chatbots . Bots—particularly in their conversation-oriented version and AI-powered—have seen increased adoption over time for software development and engineering purposes. Despite their exciting potential, which has been further enhanced by the advent of Generative AI and Large Language Models, bots still face challenges in terms of development and integration into the development cycle, as practitioners report that bots can add difficulties rather than provide improvements. In this work, we aim to provide a taxonomy for characterizing bots, as well as a series of challenges for their adoption in software engineering, accompanied by potential mitigation strategies. To achieve our objectives, we conducted a multivocal literature review , examining both research and practitioner literature. Through such an approach, we hope to contribute to both researchers and practitioners by providing (i) a series of future research directions to pursue, (ii) a list of strategies to adopt for improving the use of bots for software engineering purposes, and (iii) fostering technology and knowledge transfer from the research field to practice—one of the primary goals of multivocal literature reviews.
软件工程中机器人和对话式代理的动机、挑战、最佳实践和优势:多语种文献综述
机器人是一种软件系统,旨在通过自动化特定流程、任务或活动为用户提供支持。当这些系统采用对话组件与用户交互时,它们也被称为对话代理或聊天机器人。随着时间的推移,机器人--尤其是以对话为导向的机器人和人工智能机器人--在软件开发和工程中的应用越来越广泛。生成式人工智能和大型语言模型的出现进一步增强了机器人的潜力,尽管如此,机器人在开发和集成到开发周期方面仍然面临挑战,因为从业人员报告说,机器人可能会增加困难,而不是提供改进。在这项工作中,我们旨在提供一种用于描述机器人特征的分类方法,以及在软件工程中采用机器人所面临的一系列挑战,并辅以潜在的缓解策略。为了实现我们的目标,我们进行了多角度的文献综述,同时考察了研究文献和实践文献。通过这种方法,我们希望为研究人员和实践人员做出贡献,提供:(i) 一系列未来研究方向;(ii) 一系列改进软件工程中机器人使用的策略;(iii) 促进从研究领域到实践的技术和知识转移--这也是多声部文献综述的主要目标之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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