We present essential concepts of a model-based testing framework for probabilistic systems with continuous time. Markov automata are used as an underlying model. Key result of the work is the solid core of a probabilistic test theory, that incorporates real-time stochastic behaviour. We connect ioco theory and hypothesis testing to infer about trace probabilities. We show that our conformance relation conservatively extends ioco and discuss the meaning of quiescence in the presence of exponentially distributed time delays.
|Workshop||7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016|
|Period||18/11/16 → 18/11/16|
|Other||18 November 2016|
- FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS
- Markov Automata
- Model-Based Testing