Comparing Uniform and Flexible Policies for Software Maintenance and Replacement
IEEE Transactions on Software Engineering
An architecture-centric software maintainability assessment using information theory
Journal of Software Maintenance and Evolution: Research and Practice
Predicting faults using the complexity of code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
A state-based approach to traceability maintenance
Proceedings of the 6th ECMFA Traceability Workshop
Advances in Software Engineering - Special issue on new generation of software metrics
Towards a model to support in silico studies of software evolution
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
International Journal of Open Source Software and Processes
How changes affect software entropy: an empirical study
Empirical Software Engineering
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Software systems are affected by degradation as an effect of continuous change. Since late interventions are too much onerous, software degradation should be detected early in the software lifetime. Software degradation is currently detected by using many different complexity metrics, but their use to monitor maintenance activities is costly. These metrics are difficult to interpret, because each emphasizes a particular aspect of degradation and the aspects shown by different metrics are not orthogonal. The purpose of our research is to measure the entropy of a software system to assess its degradation. In this paper, we partially validate the entropy class of metrics by a case study, replicated on successive releases of a set of software systems. The validity is shown through direct measures of software quality such as the number of detected defects, the maintenance effort and the number of slipped defects.