Formal Methods for Protocol Testing: A Detailed Study
IEEE Transactions on Software Engineering
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The Unified Modeling Language user guide
The Unified Modeling Language user guide
An extended-UIO-based method for protocol conformance testing
Journal of Systems Architecture: the EUROMICRO Journal
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Testing Finite-State Machines: State Identification and Verification
IEEE Transactions on Computers
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
Automated Unique Input Output Sequence Generation for Conformance Testing of FSMs
The Computer Journal
Testing Software Design Modeled by Finite-State Machines
IEEE Transactions on Software Engineering
A study on the extended unique input/output sequence
Information Sciences: an International Journal
| Hi-index | 0.09 |
Object-oriented software is composed of classes. Their behaviors are usually modeled with state diagrams or finite state machines (FSMs). Testing classes is regarded as testing FSMs in which unique input/output (UIO) sequences are widely applied. The generation of UIO sequences is shown to be an undecidable problem. For these problems, genetic algorithms (GAs) may offer much promise. This paper reports some primary results of on-going research on evolutionary testing classes. First, we explain how to define UIO sequence generation as a search problem, and then describe adapting genetic algorithms to generating UIO sequences. Special issues of using genetic algorithms such as solution representation, validity checking and fitness definition are discussed in detail. Primary experiments confirm the applicability and feasibility of applying GAs to UIO sequence generation.