The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Testing object-oriented systems: models, patterns, and tools
Testing object-oriented systems: models, patterns, and tools
Test Case Prioritization: A Family of Empirical Studies
IEEE Transactions on Software Engineering
Finite-State Testing and Analysis of Graphical User Interfaces
ISSRE '01 Proceedings of the 12th International Symposium on Software Reliability Engineering
Test prioritization for pairwise interaction coverage
A-MOST '05 Proceedings of the 1st international workshop on Advances in model-based testing
Software Testing, Verification & Reliability
Test minimization for human-computer interaction
Applied Intelligence
| Hi-index | 0.00 |
Graph-based algorithms are commonly used to automatically gener ate test cases for coverage-oriented testing of software systems. Because of time and cost constraints, the entire set of test cases generated by those algorithms cannot be run. It is then essential to prioritize the test cases in sense of a rank ing, i.e., to order them according to their significance which usually is given by several attributes of relevant events entailed. This paper suggests unsupervised neural network clustering of test cases for forming preference groups, where adaptive competitive learning algorithm is applied for training the neural net work used. A case study demonstrates and validates the approach.