Modeling history to analyze software evolution: Research Articles
Journal of Software Maintenance and Evolution: Research and Practice
Adapting the "staged model for software evolution" to free/libre/open source software
Ninth international workshop on Principles of software evolution: in conjunction with the 6th ESEC/FSE joint meeting
Identifying and Improving Reusability Based on Coupling Patterns
ICSR '08 Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems
Identifying exogenous drivers and evolutionary stages in FLOSS projects
Journal of Systems and Software
Using Meta-Model Transformation to Model Software Evolution
Electronic Notes in Theoretical Computer Science (ENTCS)
The Linux kernel as a case study in software evolution
Journal of Systems and Software
From "community" to "commercial" FLOSS: the case of Moodle
Proceedings of the 3rd International Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development
Perpetual development: A model of the Linux kernel life cycle
Journal of Systems and Software
Users and developers: an agent-based simulation of open source software evolution
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
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Software evolution and maintenance is largely basedon data gathered through years of experience:understanding and improving software is often amatter of how much data is available. Open Sourcesoftware offers the opportunity to analyze closely allthe phases in the evolution of a project. What's more,data regarding its evolution is generally available forinspections. Based on simply code analyses, lots ofquestions about its efficiencies can't be resolved. Itwould be necessary to study the process from theinside, understanding who or what drove whatimprovement and so on. Still a quantitative analysisgives several insights about how much code is createdand evolved by developers. This study takes a sampleof 12 open source projects and gives some statistics toanalyze their evolution. The purpose is here tocompare what is commonly know in software evolutionin traditional environments, and what happens insteadin open environments.