Learning from Examples: Generation and Evaluation of Decision Trees for Software Resource Analysis
IEEE Transactions on Software Engineering - Special Issue on Artificial Intelligence in Software Applications
Methodology for Validating Software Metrics
IEEE Transactions on Software Engineering
A Pattern Recognition Approach for Software Engineering Data Analysis
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Improving Software Maintenance at Martin Marietta
IEEE Software
Selected papers of the sixth annual Oregon workshop on Software metrics
System acquisition based on software product assessment
Proceedings of the 18th international conference on Software engineering
How reuse influences productivity in object-oriented systems
Communications of the ACM
A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
A Procedure for Analyzing Unbalanced Datasets
IEEE Transactions on Software Engineering
Which software modules have faults which will be discovered by customers?
Journal of Software Maintenance: Research and Practice
Prediction of software quality using classification tree modeling
Prediction of software quality using classification tree modeling
Emerald: Software Metrics and Models on the Desktop
IEEE Software
Data Mining and Knowledge Discovery: Making Sense Out of Data
IEEE Expert: Intelligent Systems and Their Applications
Using Classification Trees for Software Quality Models: Lessons Learned
HASE '98 The 3rd IEEE International Symposium on High-Assurance Systems Engineering
Application of a Usage Profile in Software Quality Models
CSMR '99 Proceedings of the Third European Conference on Software Maintenance and Reengineering
A tree-based classification model for analysis of a military software system
HASE '96 Proceedings of the 1996 High-Assurance Systems Engineering Workshop
An Integrated Process and Product Model
METRICS '98 Proceedings of the 5th International Symposium on Software Metrics
Assessing Uncertain Predictions of Software Quality
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Preparing Measurements of Legacy Software for Predicting Operational Faults
ICSM '99 Proceedings of the IEEE International Conference on Software Maintenance
Integrating metrics and models for software risk assessmen
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Building Software Quality Classification Trees: Approach, Experimentation, Evaluation
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
Exploring Defect Data from Development and Customer Usage on Software Modules over Multiple Releases
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
ARMOR: Analyzer for Reducing Module Operational Risk
FTCS '95 Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing
The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
IEEE Transactions on Software Engineering
Object-oriented metrics: A review of theory and practice
Advances in software engineering
Controlling Overfitting in Classification-Tree Models ofSoftware Quality
Empirical Software Engineering
Prioritizing software security fortification throughcode-level metrics
Proceedings of the 4th ACM workshop on Quality of protection
Accuracy and efficiency comparisons of single- and multi-cycled software classification models
Information and Software Technology
Combining classifiers in software quality prediction: a neural network approach
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
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Software quality models are tools for focusing software enhancement efforts. Such efforts are essential for mission-critical embedded software, such as telecommunications systems, because customer- discovered faults have very serious consequences and are very expensive to repair. This paper presents an empirical study that evaluated software quality models over several releases to address the question, "How long will a model yield useful predictions?"This paper also introduces the Classification And Regression Trees ( cart ) algorithm to software reliability engineering practitioners. We present our method for exploiting cart features to achieve a preferred balance between the two types of misclassification rates. This is desirable because misclassifications of fault-prone modules often have much more severe consequences than misclassifications of those that are not fault-prone.We developed two classification-tree models based on four consecutive releases of a very large legacy telecommunications system. Forty-two software product, process, and execution metrics were candidate predictors. The first software quality model used measurements of the first release as the training data set and measurements of the subsequent three releases as evaluation data sets. The second model used measurements of the second release as the training data set and measurements of the subsequent two releases as evaluation data sets. Both models had accuracy that would be useful to developers. One might suppose that software quality models lose their value very quickly over successive releases due to evolution of the product and the underlying development processes. We found the models remained useful over all the releases studied.Much of the software metrics literature has shown that software product metrics can be significant predictors of fault-prone modules. This case study showed that process and execution metrics can also be significant predictors.