Model-Based Testing of Stochastic Systems with IOCO Theory

Marcus Gerhold; Mariëlle Ida Antoinette Stoelinga

doi:10.1145/2994291.2994298

Model-Based Testing of Stochastic Systems with IOCO Theory

Marcus Gerhold, Mariëlle Ida Antoinette Stoelinga

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

109 Downloads (Pure)

Abstract

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.

Original language	Undefined
Title of host publication	Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016
Place of Publication	New York
Publisher	Association for Computing Machinery
Pages	45-51
Number of pages	7
ISBN (Print)	978-1-4503-4401-2
DOIs	https://doi.org/10.1145/2994291.2994298
Publication status	Published - 18 Nov 2016
Event	7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016 - Seattle, WA, USA Duration: 18 Nov 2016 → 18 Nov 2016

Publication series

Name
Publisher	ACM

Workshop

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

Keywords

FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS
EWI-27399
Markov Automata
IR-102861
IOCO
METIS-320887
Model-Based Testing

Access to Document

10.1145/2994291.2994298

p45-gerhold

https://doi.org/10.1145/2994291.2994298

Cite this

@inproceedings{ff279e5c7cc24cc5b8a50cef8049a0df,

title = "Model-Based Testing of Stochastic Systems with IOCO Theory",

abstract = "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.",

keywords = "FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS, EWI-27399, Markov Automata, IR-102861, IOCO, METIS-320887, Model-Based Testing",

author = "Marcus Gerhold and Stoelinga, {Mari{\"e}lle Ida Antoinette}",

note = "10.1145/2994291.2994298 ; null ; Conference date: 18-11-2016 Through 18-11-2016",

year = "2016",

month = nov,

day = "18",

doi = "10.1145/2994291.2994298",

language = "Undefined",

isbn = "978-1-4503-4401-2",

publisher = "Association for Computing Machinery",

pages = "45--51",

booktitle = "Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016",

}

Gerhold, M & Stoelinga, MIA 2016, Model-Based Testing of Stochastic Systems with IOCO Theory. in Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016. Association for Computing Machinery, New York, pp. 45-51, 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016, 18/11/16. https://doi.org/10.1145/2994291.2994298

Model-Based Testing of Stochastic Systems with IOCO Theory. / Gerhold, Marcus ; Stoelinga, Mariëlle Ida Antoinette.

Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016. New York : Association for Computing Machinery, 2016. p. 45-51.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - 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.

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