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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.
2019 (English)In: Empirical Software Engineering and Measurement, 13th International Symposium on ESEM19, 2019Conference 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.
Keywords [en]
ethics, interviews, anonymization, qualitative data analysis, guidelines
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-45039OAI: oai:DiVA.org:mdh-45039DiVA, id: diva2:1345207
Conference
Empirical Software Engineering and Measurement, 13th International Symposium on ESEM19, 19 Jun 2019, Porto de Galinhas, Brazil
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: 2019-08-23Bibliographically approved

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Strandberg, Per Erik

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf