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The article examines the effectiveness of pair programming (PP) with the help of empirical evidence. Fifteen studies were conducted, out of which eleven compared the effectiveness of isolated pairs. Duration was reported either as the total time a subject took to complete all the assigned programming tasks or as the total time taken to produce code that was assessed as having reached a certain quality standard. For comparisons between pairs and solo programmers, pair effort was reported as twice the duration of each individual in the pair. Quality typically was reported as the number of test cases passed or number of correct solutions of programming tasks. The study reveals that PP leads to increased quality.

The article presents information on Evidence-Based Software Engineering (EBSE) used by the practitioners. EBSE aims to improve decision making related to software development and maintenance by integrating current best evidence from research with practical experience and human values. This means one does not expect a technology to be universally good or universally bad, only more appropriate in some circumstances and for some organizations. Furthermore, practitioners will need to accumulate empirical research about a technology of interest and evaluate the research from the viewpoint of their specific circumstances. This aim is decidedly ambitious, particularly because the gap between research and practice can be wide. EBSE seeks to close this gap by encouraging a stronger emphasis on methodological rigor while focusing on relevance for practice. This is important because rigor is necessary in any research that purports to be relevant. Moreover, because most software engineering (SE) research has not influenced industrial practice, there's also a pressing need to prevent SE research from remaining an ivory tower activity that emphasizes academic rigor over relevance to practice. INSETS: Asking the Right Question.;Useful Information Sources.;Evidenced-Based Software Engineering QSA..

An overview of how context affects empirical software engineering research and how to better contextualize empirical evidence proposes a contextual framework that answers journalism's "Five Ws": What, Who, Where, When, and Why. [ABSTRACT FROM PUBLISHER]

A close look at the evidence underpinning the original concept of lean production and its popular interpretation reveals the inherent challenges of measuring and interpreting evidence for performance differences. [ABSTRACT FROM PUBLISHER]

Empirically based theories are generally perceived as foundational to science. However, in many disciplines, the nature, role and even the necessity of theories remain matters for debate, particularly in young or practical disciplines such as software engineering. This article reports a systematic review of the explicit use of theory in a comprehensive set of 103 articles reporting experiments, from of a total of 5,453 articles published in major software engineering journals and conferences in the decade 1993-2002. Of the 103 articles, 24 use a total of 40 theories in various ways to explain the cause-effect relationship(s) under investigation. The majority of these use theory in the experimental design to justify research questions and hypotheses, some use theory to provide post hoc explanations of their results, and a few test or modify theory. A third of the theories are proposed by authors of the reviewed articles. The interdisciplinary nature of the theories used is greater than that of research in software engineering in general. We found that theory use and awareness of theoretical issues are present, but that theory-driven research is, as yet, not a major issue in empirical software engineering. Several articles comment explicitly on the lack of relevant theory. We call for an increased awareness of the potential benefits of involving theory, when feasible. To support software engineering researchers who wish to use theory, we show which of the reviewed articles on which topics use which theories for what purposes, as well as details of the theories' characteristics. [ABSTRACT FROM AUTHOR]