The test space of mechatronic control software is huge, due to large number of product variants/configurations, large variability in the environments in which products are used and large variability in the behavior of humans interacting with the mechatronic product. Companies are looking for pragmatic ways to incrementally and efficiently improve their current set of mechatronic controller test cases.
In this project, we will investigate such a pragmatic way of ‘test case prioritization’ allowing to deal with legacy test-suites and incrementally improving them, by exploring effective ways to detect anomalies detected in the field and use those anomalies in order to create new tests, in an efficient manner, that extend existing test suites.
The objective of the project is to create a method and supporting tools to support the V&V team in creating new tests from anomalies detected in the field, during field testing, or in the operational phase of the system. In scope: Mechatronic controller testing, black box testing and Unit/Subsystem/Integration testing.
A second part of the project is to leverage plant and environment models as an alternative to the physical system for test prioritization purposes, pushing expensive and time consuming HiL tests of the control software to more favorable, MiL tests and enabling us to prioritize and select most effective test scenarios, consequently reducing the cost of testing. These techniques can be employed using models developed in the model-based design process as well as using digital twins created when the systems are in operation.
TestStrategyforSWcontrol_ICON is an Industrial Research ICON project. We are looking for companies to join the User Group and work with us on the valorisation of the project.
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