Hyppotest: Hypothesis Testing Toolkit For Uncertain Service-Based Web Applications

INTEGRATED FORMAL METHODS, IFM 2019(2019)

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摘要
This paper introduces a model-based testing framework and associated toolkit, so called HYPpOTesT, for uncertain service-based web applications specified as probabilistic systems with non-determinism. The framework connects input/output conformance theory with hypothesis testing in order to assess if the behavior of the application under test corresponds to its probabilistic formal specification. The core component is a (on-the-fly) model-based testing algorithm able to automatically generate, execute and evaluate test cases from a Markov Decision Process specification. The testing activity feeds a Bayesian inference process that quantifies and mitigates the system uncertainty by calibrating probability values in the initial specification. This paper illustrates the structure, features, and usage of HYPpOTesT using the UStore exemplar, i.e., a web-based e-commerce application that exhibits uncertain behavior.
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关键词
Model-based testing, Probabilistic systems, Service-based web applications, Bayesian inference, Uncertainty quantification
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