An Undergraduate Course in Software Maintenance and Enhancement
CSEET '97 Proceedings of the 10th Conference on Software Engineering Education and Training
A proposed additional property to the Weyuker's existing properties
International Journal of Information Technology and Management
Modified cognitive complexity measure
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Statistical data analysis for software metrics validation
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Complexity measures for assembly language programs
Journal of Systems and Software
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The desire to predict the effort in developing or explain the quality of software has led to the proposal of several metrics in the literature. As a step toward validating these metrics, the Software Engineering Laboratory has analyzed the Software Science metrics, cyclomatic complexity, and various standard program measures for their relation to 1) effort (including design through acceptance testing), 2) development errors (both discrete and weighted according to the amount of time to locate and frix), and 3) one another. The data investigated are collected from a production Fortran environment and examined across several projects at once, within individual projects and by individual programmers across projects, with three effort reporting accuracy checks demonstrating the need to validate a database. When the data come from individual programmers or certain validated projects, the metrics' correlations with actual effort seem to be strongest. For modules developed entirely by individual programmers, the validity ratios induce a statistically significant ordering of several of the metrics' correlations. When comparing the strongest correlations, neither Software Science's E metric, cyclomatic complexity nor source lines of code appears to relate convincingly better with effort than the others