Context.Several empirical studies have explored the benefits of software design patterns, but their collective results are highly inconsistent. Resolving the inconsistencies requires investigating moderators—i.e., variables that cause an effect to differ across contexts.Objectives.Replicate a design patterns experiment at multiple sites and identify sufficient moderators to generalize the results across prior studies.Methods.We perform a close replication of an experiment investigating the impact (in terms of time and quality) of design patterns (Decorator and Abstract Factory) on software maintenance. The experiment was replicated once previously, with divergent results. We execute our replication at four universities—spanning two continents and three countries—using a new method for performing distributed replications based on closely coordinated, small-scale instances (“joint replication”). We perform two analyses: 1) apost-hocanalysis of moderators, based on frequentist and Bayesian statistics; 2) ana priorianalysis of the original hypotheses, based on frequentist statistics.Results.The main effect differs across the previous instances of the experiment and across the sites in our distributed replication. Our analysis of moderators (including developer experience and pattern knowledge) resolves the differences sufficiently to allow for cross-context (and cross-study) conclusions. The final conclusions represent 126 participants from five universities and 12 software companies, spanning two continents and at least four countries.Conclusions.The Decorator pattern is found to be preferable to a simpler solution during maintenance, as long as the developer has at least some prior knowledge of the pattern. For Abstract Factory, the simpler solution is found to be mostly equivalent to the pattern solution. Abstract Factory is shown to require a higher level of knowledge and/or experience than Decorator for the pattern to be beneficial.

Context: Conventional wisdom, inspired in part by Eric Raymond, suggests that open source developers should---and primarily do---develop software for developers like themselves. We refer to the production of software primarily for the benefit of developers as reflexivity, and we evaluate the applicability of this concept to open source software (OSS) by studying SourceForge projects. Objective: The goal of this research is to test Eric Raymond's assertions with respect to OSS success factors. Method: We present four criteria by which to assess project reflexivity in SourceForge. These criteria are based on three specific indicators: intended audiences, relevant topics, and supported operating systems. Results: We show in this short paper that 68% of SourceForge projects are likely reflexive (in the sense described by Raymond). Further, 76% of projects exceeding one million downloads are reflexive, 79% for projects exceeding ten million downloads, and 89% for projects exceeding one hundred million downloads. Conclusion: These results tentatively support Raymond's assertions that 1) OSS projects tend to be reflexive and 2) reflexive OSS projects tend to be more successful than irreflexive projects. Causality, however, is not addressed.

The RESER workshop provides a venue in which empirical software engineering researchers can discuss the theoretical foundations and methods of replication, as well as present the results of specific replicated studies.

Coordination of project stakeholders is critical to timely and consistent software delivery. In this short paper we present the problem of private information as a guiding framework or lens through which to interpret coordination dynamics within software organizations. We provide evidence of this problem in the form of specific challenges, collected via interviews from a diverse set of extended (i.e., non-development) stakeholders in a globally distributed software development organization.

The RESER 2010 workshop provides a venue in which empirical Software Engineering researchers may present and discuss theoretical foundations and methods of replication, as well as the results of replicated studies.

We present the results of a study in which author entropy was used to characterize author contributions per file. Our analysis reveals three patterns: banding in the data, uneven distribution of data across bands, and file size dependent distributions within bands. Our results suggest that when two authors contribute to a file, large files are more likely to have a dominant author than smaller files.