Methodology for Validating Software Metrics
IEEE Transactions on Software Engineering
Improving Software Maintenance at Martin Marietta
IEEE Software
Predicting Fault-Prone Software Modules in Telephone Switches
IEEE Transactions on Software Engineering
Software Maintenance Metrics: A Case Study
ICSM '94 Proceedings of the International Conference on Software Maintenance
Detection of Fault-Prone Software Modules During a Spiral Life Cycle
ICSM '96 Proceedings of the 1996 International Conference on Software Maintenance
Measurements for managing software maintenance
ICSM '96 Proceedings of the 1996 International Conference on Software Maintenance
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Evaluation and Application of Complexity-Based Criticality Models
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Maintainability measurements on industrial source code maintenance activities
ICSM '95 Proceedings of the International Conference on Software Maintenance
Software quality control and prediction model for maintenance
Annals of Software Engineering
Uncertain Classification of Fault-Prone Software Modules
Empirical Software Engineering
A Classification Scheme for Studies on Fault-Prone Components
PROFES '01 Proceedings of the Third International Conference on Product Focused Software Process Improvement
Proceedings of the 25th International Conference on Software Engineering
Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques
Empirical Software Engineering
Predicting Deviations in Software Quality by Using Relative Critical Value Deviation Metrics
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
Software Reliability and Maintenance Concept Used for Automatic Call Distributor MEDIO ACD
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Improving Tree-Based Models of Software Quality with Principal Components Analysis
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
On the Repeatability of Metric Models and Metrics across Software Builds
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Analogy-Based Practical Classification Rules for Software Quality Estimation
Empirical Software Engineering
The Effects of Fault Counting Methods on Fault Model Quality
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Assessment of a New Three-Group Software Quality Classification Technique: An Empirical Case Study
Empirical Software Engineering
A New Challenge for Applying Time Series Metrics Data to Software Quality Estimation
Software Quality Control
Resource-oriented software quality classification models
Journal of Systems and Software
An approach to the measurement of software evolution: Research Articles
Journal of Software Maintenance and Evolution: Research and Practice - 2003 International Conference on Software Maintenance: The Architectural Evolution of Systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Calculation and optimization of thresholds for sets of software metrics
Empirical Software Engineering
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A model is developed that is used to validate and apply metrics for quality control and quality prediction, with the objective of using metrics as early indicators of software quality problems. Metrics and quality factor data from the Space Shuttle flight software are used as an example. Our approach is to integrate quality control and prediction in a single model and to validate metrics with respect to a quality factor. Boolean discriminant functions (BDFs) were developed for use in the quality control and quality prediction process. BDFs provide good accuracy for classifying low quality software because they include additional information for discriminating quality: critical values. Critical values are threshold values of metrics that are used to either accept or reject modules when the modules are inspected during the quality control process. A series of nonparametric statistical methods is also used in the method presented. It is important to perform a marginal analysis when making a decision about how many metrics to use in the quality control and prediction process. We found that certain metrics are dominant in their effects on classifying quality and that additional metrics are not needed to accurately classify quality. This effect is called dominance. Related to the property of dominance is the property of concordance, which is the degree to which a set of metrics produces the same result in classifying software quality. A high value of concordance implies that additional metrics will not make a significant contribution to accurately classifying quality; hence, these metrics are redundant.