The effectiveness of pair programming: A meta-analysis
Information and Software Technology
Applying empirical software engineering to software architecture: challenges and lessons learned
Empirical Software Engineering
Systematic literature reviews in software engineering - A tertiary study
Information and Software Technology
Perceived productivity threats in large agile development projects
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Refining the systematic literature review process--two participant-observer case studies
Empirical Software Engineering
Using mapping studies as the basis for further research - A participant-observer case study
Information and Software Technology
Empirical validation of a requirements engineering process guide
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
The value of mapping studies: a participantobserver case study
EASE'10 Proceedings of the 14th international conference on Evaluation and Assessment in Software Engineering
A gestural approach to presentation exploiting motion capture metaphors
Proceedings of the International Working Conference on Advanced Visual Interfaces
Proceedings of the 34th International Conference on Software Engineering
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Proceedings of the Second Edition of the International Workshop on Experiences and Empirical Studies in Software Modelling
The value of design rationale information
ACM Transactions on Software Engineering and Methodology (TOSEM) - In memoriam, fault detection and localization, formal methods, modeling and design
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Increased realism in software engineering experiments is often promoted as an important means to increase generalizability and industrial relevance. In this context, artificiality, e.g., the use of constructed tasks in place of realistic tasks, is seen as a threat. In this article, we examine the opposite view, that deliberately introduced artificial design elements may increase knowledge gain and enhance both generalizability and relevance. In the first part of the article, we identify and evaluate arguments and examples in favor of, and against, deliberately introducing artificiality into software engineering experiments. In the second part of the article, we summarize a content analysis of articles reporting software engineering experiments published over the ten-year period 1993-2002. The analysis reveals a striving for realism and external validity, but little awareness of for what and when, various degrees of artificiality and realism are appropriate. We conclude that an increased awareness and deliberation in these respects is essential. However, arguments in favor of artificial design elements should not be used to justify studies that are badly designed or that have research questions of low relevance.