Across three decades of software engineering research, statistical problems were common in a large sample, and expert reviewers often disagreed with the study authors' labels when judging short excerpts.
Lessons Learnt in Conducting Survey Research
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abstract
Context: Surveys constitute an valuable tool to capture a large-scale snapshot of the state of the practice. Apparently trivial to adopt, surveys hide, however, several pitfalls that might hinder rendering the result valid and, thus, useful. Goal: We aim at providing an overview of main pitfalls in software engineering surveys and report on practical ways to deal with them. Method: We build on the experiences we collected in conducting many studies and distill the main lessons learnt. Results: The eight lessons learnt we report cover different aspects of the survey process ranging from the design of initial research objectives to the design of a questionnaire. Conclusions: Our hope is that by sharing our lessons learnt, combined with a disciplined application of the general survey theory, we contribute to improving the quality of the research results achievable by employing software engineering surveys.
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A Call for Critically Rethinking and Reforming Data Analysis in Empirical Software Engineering
Across three decades of software engineering research, statistical problems were common in a large sample, and expert reviewers often disagreed with the study authors' labels when judging short excerpts.