Towards Human-Bot Collaborative Software Architecting with ChatGPT
Paper
Paper/Presentation Title | Towards Human-Bot Collaborative Software Architecting with ChatGPT |
---|---|
Presentation Type | Paper |
Authors | Ahmad, Aakash, Waseem, Muhammad, Liang, Peng, Fahmideh, Mahdi, Aktar, Mst Shamima and Mikkonen, Tommi |
Journal or Proceedings Title | Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering (EASE 2023) |
Journal Citation | pp. 279-285 |
Number of Pages | 7 |
Year | 2023 |
Place of Publication | United States |
ISBN | 9798400700446 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3593434.3593468 |
Web Address (URL) of Paper | https://dl.acm.org/doi/abs/10.1145/3593434.3593468 |
Web Address (URL) of Conference Proceedings | https://dl.acm.org/doi/proceedings/10.1145/3593434 |
Conference/Event | 27th International Conference on Evaluation and Assessment in Software Engineering (EASE 2023) |
Event Details | 27th International Conference on Evaluation and Assessment in Software Engineering (EASE 2023) Parent International Conference on Evaluation and Assessment in Software Engineering Delivery In person Event Date 14 to end of 16 Jun 2023 Event Location Oulu, Finland Rank A A A A |
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. |
Keywords | Human-Bot; ChatGPT |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 460999. Information systems not elsewhere classified |
Byline Affiliations | Leipzig University, Germany |
University of Jyvaskyla, Finland | |
Wuhan University, China | |
School of Business |
https://research.usq.edu.au/item/z22x6/towards-human-bot-collaborative-software-architecting-with-chatgpt
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