Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Software unit test coverage and adequacy
ACM Computing Surveys (CSUR)
Measuring Dynamic Program Complexity
IEEE Software
Dynamic Metrics for Object Oriented Designs
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Dynamic Coupling Measurement for Object-Oriented Software
IEEE Transactions on Software Engineering
Efficient incremental algorithms for dynamic detection of likely invariants
Proceedings of the 12th ACM SIGSOFT twelfth international symposium on Foundations of software engineering
Pseudo dynamic metrics [software metrics]
AICCSA '05 Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications
Refining the axiomatic definition of internal software attributes
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Comparing internal and external software quality measurements
Proceedings of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering
A probability-based approach for measuring external attributes of software artifacts
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
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The quantification of several software attributes (e.g., size, complexity, cohesion, coupling) is usually carried out in a static fashion, and several hundreds of measures have been defined to this end. However, static measurement may only be an approximation for the measurement of these attributes during software use. The paper proposes a theoretical framework based on Axiomatic Approaches for the definition of sensible dynamic software measures that can dynamically capture these attributes. Dynamic measures based on this framework are defined for dynamically quantifying size and coupling. In this paper, we also compare dynamic measures of size and coupling against well-known static measures by correlating them with fault-pronenesses of four case studies.