A proposal for measuring the structural complexity of programs
Journal of Systems and Software
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
Sorting out software complexity
Communications of the ACM
Measurement of the Cognitive Functional Complexity of Software
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
The Structural Complexity of Software: An Experimental Test
IEEE Transactions on Software Engineering
An Experiment on Unit Increase in Problem Complexity
IEEE Transactions on Software Engineering
Power-Laws in a Large Object-Oriented Software System
IEEE Transactions on Software Engineering
An Exploration of Power-Law in Use-Relation of Java Software Systems
ASWEC '08 Proceedings of the 19th Australian Conference on Software Engineering
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The Matthew effect widely exists in natural and artificial systems. This paper studies the Matthew effect emerging from large information systems by investigating their topological complexity. The Matthew effect of the topological complexity reveals scale-free behavior that can be characterized by the general scale-free model [Physics Letters A 303 (2002) 337-344]. The poor-rich demarcation of the Matthew effect is analyzed to classify modules of information systems based on ABC analysis that is consistent with the ABC classification of human resources. Thus the Matthew effect is applied to envisage the critical fusion of high performance and low cost in software engineering. Finally, the Matthew effect of two typical open-source software systems written in Java and C/C++ languages is also investigated.