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Ethical Interviews in Software Engineering
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Westermo Network Technologies AB, Västerås, Sweden.ORCID iD: 0000-0003-1688-6937
2019 (English)In: Empirical Software Engineering and Measurement, 13th International Symposium on ESEM19, 2019, article id 8870192Conference paper, Published paper (Refereed)
Abstract [en]

Background: Despite a long history, numerous laws and regulations, ethics remains an unnatural topic for many software engineering researchers. Poor research ethics may lead to mistrust of research results, lost funding and retraction of publications. A core principle for research ethics is confidentiality, and anonymization is a standard approach to guarantee it. Many guidelines for qualitative software engineering research, and for qualitative research in general, exist, but these do not penetrate how and why to anonymize interview data. Aims: In this paper we aim to identify ethical guidelines for software engineering interview studies involving industrial practitioners. Method: By learning from previous experiences and listening to the authority of existing guidelines in the more mature field of medicine as well as in software engineering, a comprehensive set of checklists for interview studies was distilled. Results: The elements of an interview study were identified and ethical considerations and recommendations for each step were produced, in particular with respect to anonymization. Important ethical principles are: consent, beneficence, confidentiality, scientific value, researcher skill, justice, respect for law, and ethical reviews. Conclusions: The most important contribution of this study is the set of checklists for ethical interview studies. Future work is needed to refine these guidelines with respect to legal aspects and ethical boards

Place, publisher, year, edition, pages
2019. article id 8870192
Keywords [en]
ethics, interviews, anonymization, qualitative data analysis, guidelines
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-45039DOI: 10.1109/ESEM.2019.8870192ISI: 000648806200029Scopus ID: 2-s2.0-85074257944ISBN: 9781728129686 (print)OAI: oai:DiVA.org:mdh-45039DiVA, id: diva2:1345207
Conference
13th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2019; Porto de Galinhas, Pernambuco; Brazil; 19 September 2019 through 20 September 2019
Projects
ITS ESS-H Industrial Graduate School in Reliable Embedded Sensor SystemsTESTMINE - Mining Test Evolution for Improved Software Regression Test Selection (KKS)Available from: 2019-08-23 Created: 2019-08-23 Last updated: 2022-11-09Bibliographically approved

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Strandberg, Per Erik

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