Towards Human-Bot Collaborative Software Architecting with ChatGPT

Aakash Ahmad, Muhammad Waseem, Peng Liang, M. Fahmideh, Mst Shamima Aktar, T. Mikkonen
{"title":"Towards Human-Bot Collaborative Software Architecting with ChatGPT","authors":"Aakash Ahmad, Muhammad Waseem, Peng Liang, M. Fahmideh, Mst Shamima Aktar, T. Mikkonen","doi":"10.1145/3593434.3593468","DOIUrl":null,"url":null,"abstract":"Architecting software-intensive systems can be a complex process. It deals with the daunting tasks of unifying stakeholders’ perspectives, designers’ intellect, tool-based automation, pattern-driven reuse, and so on, to sketch a blueprint that guides software implementation and evaluation. Despite its benefits, architecture-centric software engineering (ACSE) suffers from a multitude of challenges. ACSE challenges could stem from a lack of standardized processes, socio-technical limitations, and scarcity of human expertise etc. that can impede the development of existing and emergent classes of software. Software Development Bots (DevBots) trained on large language models can help synergise architects’ knowledge with artificially intelligent decision support to enable rapid architecting in a human-bot collaborative ACSE. An emerging solution to enable this collaboration is ChatGPT, a disruptive technology not primarily introduced for software engineering, but is capable of articulating and refining architectural artifacts based on natural language processing. We detail a case study that involves collaboration between a novice software architect and ChatGPT to architect a service-based software. Future research focuses on harnessing empirical evidence about architects’ productivity and explores socio-technical aspects of architecting with ChatGPT to tackle challenges of ACSE.","PeriodicalId":178596,"journal":{"name":"Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3593434.3593468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27

Abstract

Architecting software-intensive systems can be a complex process. It deals with the daunting tasks of unifying stakeholders’ perspectives, designers’ intellect, tool-based automation, pattern-driven reuse, and so on, to sketch a blueprint that guides software implementation and evaluation. Despite its benefits, architecture-centric software engineering (ACSE) suffers from a multitude of challenges. ACSE challenges could stem from a lack of standardized processes, socio-technical limitations, and scarcity of human expertise etc. that can impede the development of existing and emergent classes of software. Software Development Bots (DevBots) trained on large language models can help synergise architects’ knowledge with artificially intelligent decision support to enable rapid architecting in a human-bot collaborative ACSE. An emerging solution to enable this collaboration is ChatGPT, a disruptive technology not primarily introduced for software engineering, but is capable of articulating and refining architectural artifacts based on natural language processing. We detail a case study that involves collaboration between a novice software architect and ChatGPT to architect a service-based software. Future research focuses on harnessing empirical evidence about architects’ productivity and explores socio-technical aspects of architecting with ChatGPT to tackle challenges of ACSE.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用ChatGPT实现人机协作软件架构
构建软件密集型系统可能是一个复杂的过程。它处理统一涉众的观点、设计人员的智力、基于工具的自动化、模式驱动的重用等艰巨的任务,以绘制指导软件实现和评估的蓝图。尽管有很多好处,但以体系结构为中心的软件工程(ACSE)面临着许多挑战。ACSE的挑战可能源于标准化过程的缺乏、社会技术的限制,以及人类专业知识的缺乏等,这些都可能阻碍现有和新兴软件类别的开发。在大型语言模型上训练的软件开发机器人(DevBots)可以帮助将架构师的知识与人工智能决策支持协同起来,从而在人机协作ACSE中实现快速架构。支持这种协作的一个新兴解决方案是ChatGPT,这是一种破坏性的技术,主要不是为软件工程引入的,但是能够基于自然语言处理阐明和精炼体系结构工件。我们详细介绍了一个案例研究,其中涉及到新手软件架构师和ChatGPT之间的协作,以构建基于服务的软件。未来的研究重点是利用关于架构师生产力的经验证据,并利用ChatGPT探索架构的社会技术方面,以应对ACSE的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Classification-based Static Collection Selection for Java: Effectiveness and Adaptability Decentralised Autonomous Organisations for Public Procurement Analyzing the Resource Usage Overhead of Mobile App Development Frameworks Investigation of Security-related Commits in Android Apps Exploring the UK Cyber Skills Gap through a mapping of active job listings to the Cyber Security Body of Knowledge (CyBOK)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1