Generative Artificial Intelligence for Software Engineering-A Research Agenda
Artikel i vetenskaplig tidskrift, 2025
Context Generative artificial intelligence (GenAI) tools have become increasingly prevalent in software development, offering assistance to various managerial and technical project activities. Notable examples of these tools include OpenAI's ChatGPT, GitHub Copilot, and Amazon CodeWhisperer.ObjectiveAlthough many recent publications have explored and evaluated the application of GenAI, a comprehensive understanding of the current development, applications, limitations, and open challenges remains unclear to many. Particularly, we do not have an overall picture of the current state of GenAI technology in practical software engineering usage scenarios.
Method We conducted a literature review and focus groups for a duration of five months to develop a research agenda on GenAI for software engineering.
Results We identified 78 open research questions (RQs) in 11 areas of software engineering. Our results show that it is possible to explore the adoption of GenAI in partial automation and support decision-making in all software development activities. While the current literature is skewed toward software implementation, quality assurance and software maintenance, other areas, such as requirements engineering, software design, and software engineering education, would need further research attention. Common considerations when implementing GenAI include industry-level assessment, dependability and accuracy, data accessibility, transparency, and sustainability aspects associated with the technology.
Conclusions GenAI is bringing significant changes to the field of software engineering. Nevertheless, the state of research on the topic still remains immature. We believe that this research agenda holds significance and practical value for informing both researchers and practitioners about current applications and guiding future research.
Method We conducted a literature review and focus groups for a duration of five months to develop a research agenda on GenAI for software engineering.
Results We identified 78 open research questions (RQs) in 11 areas of software engineering. Our results show that it is possible to explore the adoption of GenAI in partial automation and support decision-making in all software development activities. While the current literature is skewed toward software implementation, quality assurance and software maintenance, other areas, such as requirements engineering, software design, and software engineering education, would need further research attention. Common considerations when implementing GenAI include industry-level assessment, dependability and accuracy, data accessibility, transparency, and sustainability aspects associated with the technology.
Conclusions GenAI is bringing significant changes to the field of software engineering. Nevertheless, the state of research on the topic still remains immature. We believe that this research agenda holds significance and practical value for informing both researchers and practitioners about current applications and guiding future research.
Författare
Anh Nguyen-Duc
Universitetet i Sørøst-Norge
Norges teknisk-naturvitenskapelige universitet
Beatriz Cabrero-Daniel
Göteborgs universitet
Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering
Piotr Przybylek
Politechnika Gdańska
Chetan Arora
Monash University
Dron Khanna
Free University of Bozen-Bolzano
Tomas Herda
Österreichische Post
Usman Rafiq
Free University of Bozen-Bolzano
Jorge Melegati
Free University of Bozen-Bolzano
Eduardo Guerra
Free University of Bozen-Bolzano
Kai-Kristian Kemell
Helsingin Yliopisto
Mika Saari
Tampereen Yliopisto
Zheying Zhang
Tampereen Yliopisto
Huy Le
Ho Chi Minh City University of Technology (HCMUT)
Vietnam National University
Tho Quan
Ho Chi Minh City University of Technology (HCMUT)
Vietnam National University
Pekka Abrahamsson
Tampereen Yliopisto
Software - Practice and Experience
0038-0644 (ISSN) 1097-024X (eISSN)
Ämneskategorier (SSIF 2025)
Programvaruteknik
Datavetenskap (datalogi)
DOI
10.1002/spe.70005