The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Computer Networks and ISDN Systems - Special Issue: Protocol Specification and Testing
Learning causal relationships: an integration of empirical and explanation-based learning methods
Learning causal relationships: an integration of empirical and explanation-based learning methods
Explanation-based learning: a survey of programs and perspectives
ACM Computing Surveys (CSUR)
Proceedings of the sixth international workshop on Machine learning
Combining empirical and analytical learning with version spaces
Proceedings of the sixth international workshop on Machine learning
Finding new rules for incomplete theories: explicit biases for induction with contextual information
Proceedings of the sixth international workshop on Machine learning
Learning procedural knowledge in the EBG context
Proceedings of the sixth international workshop on Machine learning
Art of Software Testing
Explanation-Based Generalization: A Unifying View
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
Proceedings of the IFIP WG6.1 Fifth International Conference on Protocol Specification, Testing and Verification V
Derivation of Useful Execution Trees from LOTOS by using an Interpreter
Proceedings of the First International Conference on Formal Description Techniques
| Hi-index | 0.01 |
A method that employs a machine learning technique for the semiautomatic generation of protocol-conformance test-sequence requirements is described. Given a protocol knowledge representation and some high-level nonexecutable descriptions of protocol behavior, a learning algorithm based on extended explanation-based generalization produces conformance test-sequence requirements for a protocol implementation under test. The role of learning is to compile relevant parts of protocol knowledge into behaviors, consequently inferring executable protocol behaviors. This inference makes explicit constraints that are implicit in both the protocol knowledge and the behaviors. It is shown that the approach facilitates the derivation of new operational constraints on protocol behavior. The new constraints lead to new types of protocol behavior, thereby yielding potentially valuable new conformance test cases. An application of the method to the Alternating Bit Protocol (ABP) (a canonical example in protocols research literature) is described.