Quantitative analysis of open source projects on SourceForge

Abstrac

A Tool for Identifying Swarm Intelligence on a Free/Open Source Software Mailing List

A software tool designed using the concepts of swarm intelligence and text mining is proposed as an aid in the analysis of free/open source software (FOSS) development communities. A prototype of the tool collects textual data from an electronic mailing list, a primary mode of FOSS developer communication. The tool enables a user to compare patterns of discussion topics found in the text with patterns of swarm intelligence. The research of this design is congruent with Madey et al.‟s (2002) observation that the open source software development phenomenon shows an emergent behavior and can be modeled after agent-based, biologically-inspired swarms. The goal of a tool for identifying emergent intelligence on FOSS mailing lists is to increasing the user‟s understanding of a given FOSS development community

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)

Discussion of a large-scale open source data collection methodology

This paper discusses in detail a possible methodology for collecting repository data on a large number of open source software projects from a single project hosting and community site. The process of data retrieval is described along with the possible metrics that can be computed and which can be used for further analyses. Example research areas to be addressed with the available data and first results are given. Then, both advantages and disadvantages of the proposed methodology are discussed together with implications for future approaches. 1