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Challenges of applying ethnography to study software practices

Sammendrag


Ethnography is about the adoption of a cultural lens to observe and interpret events, actions, and behaviors, ensuring that they are placed in a relevant and meaningful context. Using this approach, it is possible to capture and analyze software development practices. Our aims are to illustrate the use of an ethnographic approach in a case study of agile software development adoption, to discuss the methodological challenges involved, and to provide support to others who conduct ethnographic studies of software practice. An ethnographic case study was conducted, employing participant observation, interviews, and document analysis. Difficulties and decisions were recorded and compared with those encountered in the literature. Finally, key challenges and guidelines to tackle them were discussed and documented. We identified five key challenges of applying ethnography to the study of software practices: (a) working in collaboration with and having something to offer to the participating company; (b) the insider/outsider dynamic of participant observation; (c) the balance between participant listening and participant observation; (d) the researcher's relationship with the participants; and (e) the rigor in qualitative work that involves the dilemma of the contextualization to be sufficiently broad and detailed. This study shows that ethnographic methods are indispensible when trying to understand software practice, and that the fundamental challenge for the researcher is to balance the role of participant observer with rigorous fieldwork.

Kategori

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Språk

Engelsk

Forfatter(e)

  • Carol Passos
  • Daniela Soares Cruzes
  • Tore Dybå
  • Manoel Mendonca

Institusjon(er)

  • Brasil
  • Norges teknisk-naturvitenskapelige universitet
  • SINTEF Digital / Software Engineering, Safety and Security

År

2012

Forlag

IEEE conference proceedings

Bok

ESEM '12. Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering and Measurement

ISBN

978-1-4503-1056-7

Side(r)

9 - 18

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