This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Anh Nguyen-Duc, University of South Eastern Norway, BøI Telemark, Norway3800 and Norwegian University of Science and Technology, Trondheim, Norway7012;
(2) Beatriz Cabrero-Daniel, University of Gothenburg, Gothenburg, Sweden;
(3) Adam Przybylek, Gdansk University of Technology, Gdansk, Poland;
(4) Chetan Arora, Monash University, Melbourne, Australia;
(5) Dron Khanna, Free University of Bozen-Bolzano, Bolzano, Italy;
(6) Tomas Herda, Austrian Post - Konzern IT, Vienna, Austria;
(7) Usman Rafiq, Free University of Bozen-Bolzano, Bolzano, Italy;
(8) Jorge Melegati, Free University of Bozen-Bolzano, Bolzano, Italy;
(9) Eduardo Guerra, Free University of Bozen-Bolzano, Bolzano, Italy;
(10) Kai-Kristian Kemell, University of Helsinki, Helsinki, Finland;
(11) Mika Saari, Tampere University, Tampere, Finland;
(12)  Zheying Zhang, Tampere University, Tampere, Finland;
(13) Huy Le, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam;
(14) Tho Quan, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam;
(15) Pekka Abrahamsson, Tampere University, Tampere, Finland. Table of Links Abstract and Introduction
Background
Research Approach
Research Agenda
Outlook and Conclusions
References 5. Outlook and Conclusions The field of GenAI in SE is an important and fast-moving SE research area, currently presenting opportunities as well as open challenges. GenAI has the power to redefine the way software is designed, developed, and maintained. The innovative capabilities of AI-driven systems promise to streamline processes, boost efficiency, and open up new avenues for creative problem-solving. However, there are also common challenges in adopting GenAI and specific challenges for SE activities, i.e., requirements engineering, software implementation, quality assurance, and SE education. Our research agenda, outlined in this paper, stands as one of the pioneering initiatives to systematically reveal the state of research as of Oct 2023. Software Engineering is a large spectrum that includes technical activities but also user-centric, process-driven and managerial aspects. A comprehensive view should consider insights and methodologies from research about software project development, software project management, professional competencies, software engineering education, and software businesses. Therefore, collaboration with experts from these diverse disciplines is essential to harness the full potential of this research area. In light of the evolving nature of GenAI research, significant work remains to establish GenAI in SE as a mature research area. Substantial theories must be developed to provide a solid theoretical underpinning for the practical applications. Technological advancements should be validated in a realistic project context. The adoption of GenAI in SE can also be combined with other active research areas, e.g., sustainability, trustworthy systems, and education. We acknowledge that this research agenda might still miss some important SE aspects where GenAI can be applied. RQs are presented to illustrate significant concerns in each SE area and are not meant to be exhaustive. The research agenda is open to additions of new tracks, topics, and RQs by other researchers interested in the research area. Through this collective effort and commitment from a diverse community of researchers, we can strengthen the foundations of GenAI in SE and ensure its relevance in a rapidly changing technological landscape. Declaration of Generative AI and AI-assisted technologies in the writing process During the preparation of this work, we used ChatGPT version 3.5 and Grammarly services to edit and improve our writing, i.e. rephrasing sentences and fixing typos and language mistakes. After using this tool/service, we reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. This paper is available on arxiv under CC 4.0 license. Authors: (1) Anh Nguyen-Duc, University of South Eastern Norway, BøI Telemark, Norway3800 and Norwegian University of Science and Technology, Trondheim, Norway7012; (2) Beatriz Cabrero-Daniel, University of Gothenburg, Gothenburg, Sweden; (3) Adam Przybylek, Gdansk University of Technology, Gdansk, Poland; (4) Chetan Arora, Monash University, Melbourne, Australia; (5) Dron Khanna, Free University of Bozen-Bolzano, Bolzano, Italy; (6) Tomas Herda, Austrian Post - Konzern IT, Vienna, Austria; (7) Usman Rafiq, Free University of Bozen-Bolzano, Bolzano, Italy; (8) Jorge Melegati, Free University of Bozen-Bolzano, Bolzano, Italy; (9) Eduardo Guerra, Free University of Bozen-Bolzano, Bolzano, Italy; (10) Kai-Kristian Kemell, University of Helsinki, Helsinki, Finland; (11) Mika Saari, Tampere University, Tampere, Finland; (12)  Zheying Zhang, Tampere University, Tampere, Finland; (13) Huy Le, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam; (14) Tho Quan, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam; (15) Pekka Abrahamsson, Tampere University, Tampere, Finland. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Anh Nguyen-Duc, University of South Eastern Norway, BøI Telemark, Norway3800 and Norwegian University of Science and Technology, Trondheim, Norway7012; (2) Beatriz Cabrero-Daniel, University of Gothenburg, Gothenburg, Sweden; (3) Adam Przybylek, Gdansk University of Technology, Gdansk, Poland; (4) Chetan Arora, Monash University, Melbourne, Australia; (5) Dron Khanna, Free University of Bozen-Bolzano, Bolzano, Italy; (6) Tomas Herda, Austrian Post - Konzern IT, Vienna, Austria; (7) Usman Rafiq, Free University of Bozen-Bolzano, Bolzano, Italy; (8) Jorge Melegati, Free University of Bozen-Bolzano, Bolzano, Italy; (9) Eduardo Guerra, Free University of Bozen-Bolzano, Bolzano, Italy; (10) Kai-Kristian Kemell, University of Helsinki, Helsinki, Finland; (11) Mika Saari, Tampere University, Tampere, Finland; (12)  Zheying Zhang, Tampere University, Tampere, Finland; (13) Huy Le, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam; (14) Tho Quan, Vietnam National University Ho Chi Minh City, Hochiminh City, Vietnam and Ho Chi Minh City University of Technology, Hochiminh City, Vietnam; (15) Pekka Abrahamsson, Tampere University, Tampere, Finland. Table of Links Abstract and Introduction Background Research Approach Research Agenda Outlook and Conclusions References Abstract and Introduction Abstract and Introduction Background Background Research Approach Research Approach Research Agenda Research Agenda Outlook and Conclusions Outlook and Conclusions References References 5. Outlook and Conclusions The field of GenAI in SE is an important and fast-moving SE research area, currently presenting opportunities as well as open challenges. GenAI has the power to redefine the way software is designed, developed, and maintained. The innovative capabilities of AI-driven systems promise to streamline processes, boost efficiency, and open up new avenues for creative problem-solving. However, there are also common challenges in adopting GenAI and specific challenges for SE activities, i.e., requirements engineering, software implementation, quality assurance, and SE education. Our research agenda, outlined in this paper, stands as one of the pioneering initiatives to systematically reveal the state of research as of Oct 2023. Software Engineering is a large spectrum that includes technical activities but also user-centric, process-driven and managerial aspects. A comprehensive view should consider insights and methodologies from research about software project development, software project management, professional competencies, software engineering education, and software businesses. Therefore, collaboration with experts from these diverse disciplines is essential to harness the full potential of this research area. In light of the evolving nature of GenAI research, significant work remains to establish GenAI in SE as a mature research area. Substantial theories must be developed to provide a solid theoretical underpinning for the practical applications. Technological advancements should be validated in a realistic project context. The adoption of GenAI in SE can also be combined with other active research areas, e.g., sustainability, trustworthy systems, and education. We acknowledge that this research agenda might still miss some important SE aspects where GenAI can be applied. RQs are presented to illustrate significant concerns in each SE area and are not meant to be exhaustive. The research agenda is open to additions of new tracks, topics, and RQs by other researchers interested in the research area. Through this collective effort and commitment from a diverse community of researchers, we can strengthen the foundations of GenAI in SE and ensure its relevance in a rapidly changing technological landscape. Declaration of Generative AI and AI-assisted technologies in the writing process During the preparation of this work, we used ChatGPT version 3.5 and Grammarly services to edit and improve our writing, i.e. rephrasing sentences and fixing typos and language mistakes. After using this tool/service, we reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

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Generative Artificial Intelligence for Software Engineering: Outlook and Conclusions

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