According to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. In order to begin investigating such claims, we examine data from two major open source projects, the Apache web server and the Mozilla browser. By using email archives of source code change history and problem reports we quantify aspects of developer participation, core team size, code ownership, productivity, defect density, and problem resolution intervals for these OSS projects. We develop several hypotheses by comparing the Apache project with several commercial projects. We then test and refine several of these hypotheses, based on an analysis of Mozilla data. We conclude with thoughts about the prospects for high-performance commercial/open source process hybrids.

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Global software development is rapidly becoming the norm for technology companies. Previous qualitative research suggests that distributed development may increase development cycle time for individual work items (modification requests). We use both data from the source code change management system and survey data to model the extent of delay in a distributed software development organization and explore several possible mechanisms for this delay. One key finding is that distributed work items appear to take about two and one-half times as long to complete as similar items where all the work is colocated. The data strongly suggest a mechanism for the delay, i.e., that distributed work items involve more people than comparable same-site work items, and the number of people involved is strongly related to the calendar time to complete a work item. We replicate the analysis of change data in a different organization with a different product and different sites and confirm our main findings. We also report survey results showing differences between same-site and distributed social networks, testing several hypotheses about characteristics of distributed social networks that may be related to delay. We discuss implications of our findings for practices and collaboration technology that have the potential for dramatically speeding distributed software development.

AbstractÐA central feature of the evolution of large software systems is that changeÐwhich is necessary to add new functionality, accommodate new hardware, and repair faultsÐbecomes increasingly difficult over time. In this paper, we approach this phenomenon, which we term code decay, scientifically and statistically. We define code decay and propose a number of measurements (code decay indices) on software and on the organizations that produce it, that serve as symptoms, risk factors, and predictors of decay. Using an unusually rich data set (the fifteen-plus year change history of the millions of lines of software for a telephone switching system), we find mixed, but on the whole persuasive, statistical evidence of code decay, which is corroborated by developers of the code. Suggestive indications that perfective maintenance can retard code decay are also discussed.

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