Generation of Monitoring Functions in Production Automation Using Test Specifications (bibtex)
by Cha, Suhyun, Ulewicz, Sebastian, Weigl, Alexander, Ulbrich, Mattias, Beckert, Bernhard and Vogel-Heuser, Birgit
Abstract:
High requirements regarding quality are set for automated production systems (aPS) as malfunctions can harm humans or cause severe financial loss. These malfunctions can be caused by faults in the control software of the aPS or its inability to correctly identify and handle unintended situations and errors in the technical process or hardware behavior. To achieve more dependable control software, software testing and formal verification can be used to find faults in the software, but require to make assumptions about possible situations (inputs) occurring in the aPS during runtime and often only allow the validation of specific cases. Monitoring individual functions within the control software during runtime can help to identify unspecified situations and raise warnings of the uncertainty about the suitability of a reaction. Yet, the design of reliable monitoring functions requires extensive experience and resources. For this reason, we propose a method for generating monitoring functions from available testing and verification specifications initially used for validating a control software function. Through this, it is possible to continuously assess the behavior of individual software functions and to identify and warn about a) violations of the test specification during runtime and b) unintended situations in which correct software behavior was never tested. Thus, the approach can help to assess and improve both the control software and specification quality through observation and behavior assessment far beyond the testing phase by efficiently reusing existing test specifications for runtime monitoring.
Reference:
Generation of Monitoring Functions in Production Automation Using Test Specifications (Cha, Suhyun, Ulewicz, Sebastian, Weigl, Alexander, Ulbrich, Mattias, Beckert, Bernhard and Vogel-Heuser, Birgit), In 15th IEEE International Conference on Industrial Informatics (INDIN), 2017.
Bibtex Entry:
@inproceedings{ChUlWe2017,
title = {Generation of Monitoring Functions in Production Automation Using Test Specifications},
author = {Cha, Suhyun and Ulewicz, Sebastian and Weigl, Alexander and Ulbrich, Mattias and Beckert, Bernhard and Vogel-Heuser, Birgit},
year = 2017,
month = July,
address = {Emden, Germany},
pages = {339--344},
booktitle = {15th IEEE International Conference on Industrial Informatics (INDIN)},
doi = {10.1109/INDIN.2017.8104795},
abstract = {High requirements regarding quality are set for automated production systems (aPS) as malfunctions can harm humans or cause severe financial loss. These malfunctions can be caused by faults in the control software of the aPS or its inability to correctly identify and handle unintended situations and errors in the technical process or hardware behavior. To achieve more dependable control software, software testing and formal verification can be used to find faults in the software, but require to make assumptions about possible situations (inputs) occurring in the aPS during runtime and often only allow the validation of specific cases. Monitoring individual functions within the control software during runtime can help to identify unspecified situations and raise warnings of the uncertainty about the suitability of a reaction. Yet, the design of reliable monitoring functions requires extensive experience and resources. For this reason, we propose a method for generating monitoring functions from available testing and verification specifications initially used for validating a control software function. Through this, it is possible to continuously assess the behavior of individual software functions and to identify and warn about a) violations of the test specification during runtime and b) unintended situations in which correct software behavior was never tested. Thus, the approach can help to assess and improve both the control software and specification quality through observation and behavior assessment far beyond the testing phase by efficiently reusing existing test specifications for runtime monitoring.},
}
Powered by bibtexbrowser