An Empirical Study of Software Metrics
IEEE Transactions on Software Engineering
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
Analyzing Error-Prone System Structure
IEEE Transactions on Software Engineering
Cyclomatic Complexity Density and Software Maintenance Productivity
IEEE Transactions on Software Engineering
Estimating the Probability of Failure When Testing Reveals No Failures
IEEE Transactions on Software Engineering
The Detection of Fault-Prone Programs
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
Semantic metrics for software testability
Journal of Systems and Software - Special issue on the Oregon Metric Workshop
Predicting Fault-Prone Software Modules in Telephone Switches
IEEE Transactions on Software Engineering
Experiments of the effectiveness of dataflow- and controlflow-based test adequacy criteria
ICSE '94 Proceedings of the 16th international conference on Software engineering
Further empirical studies of test effectiveness
SIGSOFT '98/FSE-6 Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Defining and Validating Measures for Object-Based High-Level Design
IEEE Transactions on Software Engineering
An empirical study of regression test application frequency
Proceedings of the 22nd international conference on Software engineering
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Provable Improvements on Branch Testing
IEEE Transactions on Software Engineering
Machine Learning
Implications of Evolution Metrics on Software Maintenance
ICSM '98 Proceedings of the International Conference on Software Maintenance
Toward a Software Testing and Reliability Early Warning Metric Suite
Proceedings of the 26th International Conference on Software Engineering
Static analysis tools as early indicators of pre-release defect density
Proceedings of the 27th international conference on Software engineering
A new approach for software testability analysis
Proceedings of the 28th international conference on Software engineering
Predicting component failures at design time
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
Exploring the relationship of history characteristics and defect count: an empirical study
DEFECTS '08 Proceedings of the 2008 workshop on Defects in large software systems
Accuracy and efficiency comparisons of single- and multi-cycled software classification models
Information and Software Technology
Predicting build failures using social network analysis on developer communication
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Software testing by active learning for commercial games
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Information and Software Technology
Predicting aging-related bugs using software complexity metrics
Performance Evaluation
Data stream mining for predicting software build outcomes using source code metrics
Information and Software Technology
A comparative study of models for predicting fault proneness in object-oriented systems
International Journal of Computer Applications in Technology
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The effectiveness of the software testing process is a key issue for meeting the increasing demand of quality without augmenting the overall costs of software development. The estimation of software fault-proneness is important for assessing costs and quality and thus better planning and tuning the testing process. Unfortunately, no general techniques are available for estimating software fault-proneness and the distribution of faults to identify the correct level of test for the required quality. Although software complexity and testing thoroughness are intuitively related to the costs of quality assurance and the quality of the final product, single software metrics and coverage criteria provide limited help in planning the testing process and assuring the required quality.By using logistic regression, this paper shows how models can be built that relate software measures and software fault-proneness for classes of homogeneous software products. It also proposes the use of cross-validation for selecting valid models even for small data sets.The early results show that it is possible to build statistical models based on historical data for estimating fault-proneness of software modules before testing, and thus better planning and monitoring the testing activities.