TY - GEN
T1 - Generation of monitoring functions in production automation using test specifications
AU - Cha, Suhyun
AU - Ulewicz, Sebastian
AU - Vogel-Heuser, Birgit
AU - Weigl, Alexander
AU - Ulbrich, Mattias
AU - Beckert, Bernhard
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/10
Y1 - 2017/11/10
N2 - High quality requirements 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.
AB - High quality requirements 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.
KW - automatic testing
KW - manufacturing automation
KW - model-driven development
KW - system testing
UR - http://www.scopus.com/inward/record.url?scp=85030154409&partnerID=8YFLogxK
U2 - 10.1109/INDIN.2017.8104795
DO - 10.1109/INDIN.2017.8104795
M3 - Conference contribution
AN - SCOPUS:85030154409
T3 - Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
SP - 339
EP - 344
BT - Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Industrial Informatics, INDIN 2017
Y2 - 24 July 2017 through 26 July 2017
ER -