IEEE Transactions on Software Engineering
Field experiments with local software quality metrics
Software—Practice & Experience
Applications of a relative complexity metric for software project management
Journal of Systems and Software - An Oregon workshop on software metrics
Design metrics: an empirical analysis
Software Engineering Journal - Special issue: on software reliability and metrics
Journal of Systems and Software - Special issue of the best papers from the Oregon Workshop on Software Metrics, 1993
Journal of Systems and Software
Selected papers of the sixth annual Oregon workshop on Software metrics
Artificial Neural Networks: A Tutorial
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
Software metrics for reliability assessment
Handbook of software reliability engineering
Software Complexity: Measures and Methods
Software Complexity: Measures and Methods
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Using Neural Networks in Reliability Prediction
IEEE Software
Measuring Dynamic Program Complexity
IEEE Software
Towards a Framework for Software Measurement Validation
IEEE Transactions on Software Engineering
Software project risk analysis models with application to embedded systems
Software project risk analysis models with application to embedded systems
A lightweight approach to technical risk estimation via probabilistic impact analysis
Proceedings of the 2006 international workshop on Mining software repositories
Inference of power plant quake-proof information based on interactive data mining approach
Advanced Engineering Informatics
Quantitative software security risk assessment model
Proceedings of the 2007 ACM workshop on Quality of protection
Applying machine learning to software fault-proneness prediction
Journal of Systems and Software
Analysing Bug Prediction Capabilities of Static Code Metrics in Open Source Software
IWSM/Metrikon/Mensura '08 Proceedings of the International Conferences on Software Process and Product Measurement
Feature weighting heuristics for analogy-based effort estimation models
Expert Systems with Applications: An International Journal
Multiple classifier application to credit risk assessment
Expert Systems with Applications: An International Journal
Analysis of the Risk Assessment Methods --- A Survey
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Empirical Evaluation of Hunk Metrics as Bug Predictors
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Genetic algorithm based software integration with minimum software risk
Information and Software Technology
Cost-sensitive boosting neural networks for software defect prediction
Expert Systems with Applications: An International Journal
Structural health assessing by interactive data mining approach in nuclear power plant
JSAI'06 Proceedings of the 20th annual conference on New frontiers in artificial intelligence
Ensemble missing data techniques for software effort prediction
Intelligent Data Analysis
Countermeasure graphs for software security risk assessment: An action research
Journal of Systems and Software
Software project risk analysis using Bayesian networks with causality constraints
Decision Support Systems
Applications of fuzzy integrals for predicting software fault-prone
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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An enhanced technique for risk categorization is presented. This technique, PCA-ANN, provides an improved capability to discriminate high-risk software. The approach draws on the combined strengths of pattern recognition, multivariate statistics and neural networks. Principal component analysis is utilized to provide a means of normalizing and orthogonalizing the input data, thus eliminating the ill effects of multicollinearity. A neural network is used for risk determination/classification. A significant feature of this approach is a procedure, herein termed cross-normalization. This procedure provides the technique with capability to discriminate data sets that include disproportionately large numbers of high-risk software modules.