Using Experiments to Build a Body of Knowledge
PSI '99 Proceedings of the Third International Andrei Ershov Memorial Conference on Perspectives of System Informatics
Identifying and characterizing change-prone classes in two large-scale open-source products
Journal of Systems and Software
Deriving an approximation algorithm for automatic computation of ripple effect measures
Information and Software Technology
Studying software evolution using artefacts' shared information content
Science of Computer Programming
Positive vectors clustering using inverted Dirichlet finite mixture models
Expert Systems with Applications: An International Journal
Complexity measures for assembly language programs
Journal of Systems and Software
Studying volatility predictors in open source software
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
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A family of syntactic complexity metrics is defined that generates several metrics commonly occurring in the literature. The paper uses the family to answer some questions about the relationship of these metrics to error-proneness and to each other. Two derived metrics are applied; slope which measures the relative skills of programmers at handling a given level of complexity and r square which is indirectly related to the consistency of performance of the programmer or team. The study suggests that individual differences have a large effect on the significance of results where many individuals are used. When an individual is isolated, better results are obtainable. The metrics can also be used to differentiate between projects on which a methodology was used and those on which it was not.