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On the Cognitive Complexity of Software and its Quantification and Formal Measurement

On the Cognitive Complexity of Software and its Quantification and Formal Measurement

Yingxu Wang
Copyright: © 2009 |Volume: 1 |Issue: 2 |Pages: 23
ISSN: 1942-9045|EISSN: 1942-9037|ISSN: 1942-9045|EISBN13: 9781615204212|EISSN: 1942-9037|DOI: 10.4018/jssci.2009040103
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MLA

Wang, Yingxu. "On the Cognitive Complexity of Software and its Quantification and Formal Measurement." IJSSCI vol.1, no.2 2009: pp.31-53. http://doi.org/10.4018/jssci.2009040103

APA

Wang, Y. (2009). On the Cognitive Complexity of Software and its Quantification and Formal Measurement. International Journal of Software Science and Computational Intelligence (IJSSCI), 1(2), 31-53. http://doi.org/10.4018/jssci.2009040103

Chicago

Wang, Yingxu. "On the Cognitive Complexity of Software and its Quantification and Formal Measurement," International Journal of Software Science and Computational Intelligence (IJSSCI) 1, no.2: 31-53. http://doi.org/10.4018/jssci.2009040103

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Abstract

The quantification and measurement of functional complexity of software are a persistent problem in software engineering. Measurement models of software complexities have been studied in two facets in computing and software engineering, where the former is machine-oriented in the small; while the latter is humanoriented in the large. The cognitive complexity of software presented in this paper is a new measurement for cross-platform analysis of complexities, functional sizes, and cognition efforts of software code and specifications in the phases of design, implementation, and maintenance in software engineering. This paper reveals that the cognitive complexity of software is a product of its architectural and operational complexities on the basis of deductive semantics. A set of ten Basic Control Structures (BCS’s) are elicited from software architectural and behavioral modeling and specifications. The cognitive weights of the BCS’s are derived and calibrated via a series of psychological experiments. Based on this work, the cognitive complexity of software systems can be rigorously and accurately measured and analyzed. Comparative case studies demonstrate that the cognitive complexity is highly distinguishable for software functional complexity and size measurement in software engineering.

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