A unified framework for expressing software subsystem classification techniques
Journal of Systems and Software
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
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Journal of the ACM (JACM)
Component-based software engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Locating Features in Source Code
IEEE Transactions on Software Engineering
An improved graph-theoretic model for the circuit layout problem
DAC '74 Proceedings of the 11th Design Automation Workshop
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ACDC: An Algorithm for Comprehension-Driven Clustering
WCRE '00 Proceedings of the Seventh Working Conference on Reverse Engineering (WCRE'00)
Applying Webmining Techniques to Execution Traces to Support the Program Comprehension Process
CSMR '05 Proceedings of the Ninth European Conference on Software Maintenance and Reengineering
Software Systems as Complex Networks
COGINF '07 Proceedings of the 6th IEEE International Conference on Cognitive Informatics
Scale-free fully informed particle swarm optimization algorithm
Information Sciences: an International Journal
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Complex-network theory is a new approach in studying different types of large systems in both the physical and the abstract worlds. In this paper, we have studied two kinds of network from software engineering: the component dependence network and the sorting comparison network (SCN). It is found that they both show the same scale-free property under certain conditions as complex networks in other fields. These results suggest that complex-network theory can be a useful approach to the study of software systems. The special properties of SCNs provide a more repeatable and deterministic way to study the evolution and optimization of complex networks. They also suggest that the closer a sorting algorithm is to the theoretical optimal limit, the more its SCN is like a scale-free network. This may also indicate that, to store and retrieve information efficiently, a concept network might need to be scale-free.