Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Software testing techniques (2nd ed.)
Software testing techniques (2nd ed.)
Constraint-Based Automatic Test Data Generation
IEEE Transactions on Software Engineering
Self-organizing maps
Testing object-oriented systems: models, patterns, and tools
Testing object-oriented systems: models, patterns, and tools
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
On the Use of Neural Networks to Guide Software Testing Activities
Proceedings of the IEEE International Test Conference on Driving Down the Cost of Test
On the automated generation of program test data (Abstract only)
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Data flow analysis techniques for test data selection
ICSE '82 Proceedings of the 6th international conference on Software engineering
The application of error-sensitive testing strategies to debugging
SIGSOFT '83 Proceedings of the ACM SIGSOFT/SIGPLAN software engineering symposium on High-level debugging
ANN model for predicting software function point metric
ACM SIGSOFT Software Engineering Notes
Software reusability assessment using soft computing techniques
ACM SIGSOFT Software Engineering Notes
An automated framework for software test oracle
Information and Software Technology
Neural networks based automated test oracle for software testing
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Radial basis function neural network based approach to test oracle
ACM SIGSOFT Software Engineering Notes
Attribute reduction based expected outputs generation for statistical software testing
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Artificial neural networks as multi-networks automated test oracle
Automated Software Engineering
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In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as Test Oracle. The triangle classification problem has been used as a case study. Results for the usage of unsupervised artificial networks indicate that they are not suitable for this purpose. The Feed-forward back propagation neural networks are demonstrated to be suitable.