2026-10-05T21:32:39Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:28029 2026-10-05T06:44:05Z ddc:004 open_access

How Many Interviews Are Enough in a Software Engineering Study? Preliminary Findings on Sample Size and Saturation de Souza Santos, Ronnie Santos, Italo Lima, Mauricio Rodrigues Magalhães, Cleyton qualitative research interviews publications Background. Interview-based studies are widely used in empirical software engineering to investigate human, organizational, and socio-technical phenomena, yet interview sample adequacy and saturation are reported inconsistently across the literature. Aims. This paper investigates how interview sample adequacy and saturation are reported in empirical software engineering research. Method. We analyzed 427 papers published between 2016 and 2025 across major software engineering venues, focusing on interview sample sizes, saturation discussions, and sample adequacy justifications. Results. Preliminary findings indicate substantial variation in interview sample sizes, ranging from highly specialized small-sample studies to broader investigations involving large interview datasets. Studies involving 12 or fewer interviewees were common and frequently associated with specialized industrial contexts or constrained organizational access. However, the most common range was 13 to 24 interviewees, suggesting that moderate-sized samples represent the most common configuration in empirical software engineering research. Saturation and sample adequacy justifications were heterogeneous, with many studies relying on implicit or contextual reasoning rather than explicit methodological discussion. Conclusions. Our findings provide empirical insights into methodological reporting practices in interview-based software engineering research and contribute to ongoing discussions on qualitative rigor and transparency. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ronnie de Souza Santos and Italo Santos and Mauricio Rodrigues Lima and Cleyton Magalhães 2026 Is Part Of LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ESEM.2026.61 urn:nbn:de:0030-drops-280299 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.61 eng https://creativecommons.org/licenses/by/4.0/legalcode