This paper studies Essence in an educational setting to evaluate its usefulness for software engineering students while also investigating barriers to its adoption in this context.
Kai-Kristian Kemell, Anh Nguyen-Duc, Xiaofeng Wang et al.· International Conference on...· 5 citations
This study designs a qualitative survey aimed at software startup educators at Universities, and gathers enough information so it can help the academic community in improving their own courses.
R. Chanin, Dron Khanna, Kai-Kristian Kemell et al.· Workshop on Software-intensi...· 4 citations
A conceptual model to explain for coop competition among software firms in OSS projects is proposed and shows two aspects of coopetition can be managed at the same time based on firm gatekeepers.
Anh Nguyen-Duc, D. Cruzes, Terje Snarby et al.· e-Informatica Software Engin...· 15 citations· ⚡2
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A multi-vocal literature review focusing on practitioner literature is conducted in order to compile a list of metrics used by software startups, intended to serve as a basis for further research in the area.
Kai-Kristian Kemell, Xiaofeng Wang, Anh Nguyen-Duc et al.· Workshop on Software-intensi...· 9 citations
This paper discusses a research framework for implementing AI ethics in industrial settings and presents a starting point for empirical studies into AI ethics but is still being developed further based on its practical utilization.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· Conference on Technology Eth...· 27 citations· ⚡3
An empirical study on the current state of practice in artificial intelligence ethics is conducted by means of a multiple case study of five case companies, which indicates a gap between research and practice in the area.
Ville Vakkuri, Kai-Kristian Kemell, Joni Kultanen et al.· arXiv.org· 56 citations· ⚡6
Software Engineers work using highly diverse methods and practices, and general theories in software engineering are lacking. A recent attempt at creating a common ground in the area of software engineering methodologies has been the Essence Theory of Software Engineering. Essence is a method-agnostic progress manageme...
Kai-Kristian Kemell, A. Evensen, Xiaofeng Wang et al.· EUROMICRO Conference on Soft...· 2 citations
This paper provides a baseline for ethics in AI based software development by reporting results from an industrial multiple case study on AI systems development in the health care sector, and explores the current state of practice out on the field in the absence of formal methods and tools for ethically aligned design.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· arXiv.org· 2 citations
It is found that the key conditions for making these blockchain-based solutions viable are attaining technological maturity and competences, ecosystem thinking and adequate governance of these ecosystems, and finally (3) achieving legal and regulatory predictability.
Taija Kolehmainen, Gabriella Laatikainen, Joni Kultanen et al.· International Conference on...· 9 citations
A holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requirements and Minimum Viable Products is described and a research agenda with seven questions for future studies is proposed.
Anh Nguyen-Duc, P. Abrahamsson· ESEC/SIGSOFT FSE· 9 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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