A model-based testing framework with reduced set of test cases for programmable controllers

Canlong Ma, Julien Provost

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In testing of programmable controllers, manual selection of test cases is still the most common method in practice. This is however tailor-made, time consuming and error-prone. Traditional model-based methods can hardly handle industrial scale systems which usually possess a significant number of states, and signals of sensors and actuators. In this paper, we propose a model-based testing framework that utilizes simplified plant features to reduce the number of test cases, and at the same time also guarantees a full coverage of nominal behavior of system under test. The proposed framework has been illustrated on a case study.

Original languageEnglish
Title of host publication2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
PublisherIEEE Computer Society
Pages944-949
Number of pages6
ISBN (Electronic)9781509067800
DOIs
StatePublished - 1 Jul 2017
Event13th IEEE Conference on Automation Science and Engineering, CASE 2017 - Xi'an, China
Duration: 20 Aug 201723 Aug 2017

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2017-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference13th IEEE Conference on Automation Science and Engineering, CASE 2017
Country/TerritoryChina
CityXi'an
Period20/08/1723/08/17

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