On feature traceability in object oriented programs
TEFSE '05 Proceedings of the 3rd international workshop on Traceability in emerging forms of software engineering
An evaluation of code similarity identification for the grow-and-prune model
Journal of Software Maintenance and Evolution: Research and Practice - Special Issue on the 12th Conference on Software Maintenance and Reengineering (CSMR 2008)
Comparison and evaluation of code clone detection techniques and tools: A qualitative approach
Science of Computer Programming
Perpetual development: A model of the Linux kernel life cycle
Journal of Systems and Software
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Large multi-platform, multi-million lines of codes software systems evolve to cope with new platform or to meet user ever changing needs. While there has been several studies focused on the similarity of code fragments or modules, few studies addressed the need to monitor the overall system evolution. Meanwhile, the decision to evolve or to refactor a large software system needs to be supported by high level information, representing the system overall picture, abstracting from unnecessary details.This paper proposes to extend the concept of similarity of code fragments to quantify similarities at the release/system level. Similarities are captured by four software metricsrepresentative of the commonalities and differences within and among software artifacts.To show the feasibility of characterizing large software system with the new metrics, 365 releases of the Linux kernel were analyzed. The metrics, the experimental results as well as the lessons learned are presented in the paper.