Signature-based detection of behavioural deviations in flight simulators - Experiments on FlightGear and JSBSim

17 Flight simulators are systems composed of numerous off-the-shelf components 18 that allow pilots and maintenance crew to prepare for common and emer19 gency flight procedures for a given aircraft model. A simulator must follow 20 severe safety specifications to guarantee correct behaviour and requires an 21 extensive series of prolonged manual tests to identify bugs or safety issues. 22 In order to reduce the time required to test a new simulator version, this 23 paper presents rule-based models able to automatically identify unexpected 24 behaviour (deviations). The models represent signature trends in the be25 haviour of a successful simulator version that are compared to the behaviour 26 of a new simulator version. Empirical analysis on nine types of injected faults 27 in the popular FlightGear and JSBSim open source simulators shows that 28 our approach does not miss any deviating behaviour considering faults which 29 Preprint submitted to PeerJ Computer Science December 23, 2016 PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2670v1 | CC BY 4.0 Open Access | rec: 23 Dec 2016, publ: 23 Dec 2016 change the flight environment, and that we are able to find all the injected 30 deviations in 4 out 7 functional faults and 75% of the deviations in 2 other 31 faults. 32