Model-Based Testing IoT Communication via Active Automata Learning

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

Abstract

This paper presents a learning-based approach to detecting failures in reactive systems. The technique is based on inferring models of multiple implementations of a common specification which are pair-wise cross-checked for equivalence. Any counterexample to equivalence is flagged as suspicious and has to be analysed manually. Hence, it is possible to find possible failures in a semi-automatic way without prior modelling. We show that the approach is effective by means of a case study. For this case study, we carried out experiments in which we learned models of five implementations of MQTT brokers/servers, a protocol used in the Internet of Things. Examining these models, we found several violations of the MQTT specification. All but one of the considered implementations showed faulty behaviour. In the analysis, we discuss effectiveness and also issues we faced.
Originalspracheenglisch
Titel2017 IEEE International Conference on Software Testing, Verification and Validation (ICST)
Seiten276-287
Seitenumfang12
DOIs
PublikationsstatusVeröffentlicht - 2017
Veranstaltung10th IEEE International Conference on Software Testing, Verification and Validation - Tokyo, Japan
Dauer: 13 Mär 201717 Mär 2017
http://aster.or.jp/conference/icst2017/

Konferenz

Konferenz10th IEEE International Conference on Software Testing, Verification and Validation
KurztitelICST 2017
LandJapan
OrtTokyo
Zeitraum13/03/1717/03/17
Internetadresse

Schlagwörter

    Fields of Expertise

    • Information, Communication & Computing

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  • Dieses zitieren

    Tappler, M., Aichernig, B. K., & Bloem, R. (2017). Model-Based Testing IoT Communication via Active Automata Learning. in 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) (S. 276-287) https://doi.org/10.1109/ICST.2017.32