Generative Artificial Intelligence for Software Engineering-A Research Agenda
Journal article, 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.
Author
Anh Nguyen-Duc
University of South-eastern Norway,
Norwegian University of Science and Technology (NTNU)
Beatriz Cabrero-Daniel
University of Gothenburg
Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering
Piotr Przybylek
Gdansk University of Technology
Chetan Arora
Monash University
Dron Khanna
Free University of Bozen-Bolzano
Tomas Herda
Austrian 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
University of Helsinki
Mika Saari
University of Tampere
Zheying Zhang
University of Tampere
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
University of Tampere
Software - Practice and Experience
0038-0644 (ISSN) 1097-024X (eISSN)
Subject Categories (SSIF 2025)
Software Engineering
Computer Sciences
DOI
10.1002/spe.70005