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Kari Smolander

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Software Engineering Artificial Intelligence eess.SY Systems and Control

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preprint2026arXiv

To Vibe Research or Not to Vibe Research? Generative AI in Qualitative Research

There has been intense debate among qualitative researchers about whether generative AI is suitable for qualitative research. In this paper, we summarize the broader ongoing discussion of generative AI in qualitative research and its implications for software engineering researchers. The qualitative research approach, small-q (positivist or post-positivist) or Big Q (non-positivist), is among the major criteria for determining whether generative AI can be used in qualitative research. In addition to research philosophy and research approach, skills, ethics, and personal preferences also play a role in researchers' decisions about whether to use AI in qualitative research.

preprint2020arXiv

Twenty-one key factors to choose an IoT platform: Theoretical framework and its applications

Internet of Things (IoT) refers to the interconnection of physical objects via the Internet. It utilises complex back-end systems which need different capabilities depending on the requirements of the system. IoT has already been used in various applications, such as agriculture, smart home, health, automobiles, and smart grids. There are many IoT platforms, each of them capable of providing specific services for such applications. Finding the best match between application and platform is, however, a hard task as it can difficult to understand the implications of small differences between platforms. This paper builds on previous work that has identified twenty-one important factors of an IoT platform, which were verified by Delphi method. We demonstrate here how these factors can be used to discriminate between five well known IoT platforms, which are arbitrarily chosen based on their market share. These results illustrate how the proposed approach provides an objective methodology that can be used to select the most suitable IoT platform for different business applications based on their particular requirements.

preprint2015arXiv

Observations of service identification from two enterprises

Service-oriented computing has created new requirements for information systems development processes and methods. The adoption of service-oriented development requires service identification methods matching the challenge in enterprises. A wide variety of service identification methods (SIM) have been proposed, but less attention has been paid to the actual requirements of the methods. This paper provides an ethnographical look at challenges in service identification based on data from 14 service identification sessions, providing insight into the practice of service identification. The findings identified two types of service identification sessions and the results can be used for selecting the appropriate SIM based on the type of the session.