Sankt Gallen, Univ., Diss., 2008. / Zsfassung in engl. Sprache.

In the recent trends, automated systems are increasingly seen to be embedded in human life with the increase of human dependence on software to perform safetycritical tasks like airbag deployment in automobiles to real-time mission planning in UAVs (Unmanned Aircraft Vehicles). The safety-critical nature of the aerospace domain demands for a software without any errors to perform these tasks. Therefore the field of computer science needs to address these challenges by providing necessary formalisms, techniques, and tools that will ensure the correctness of systems despite their complexity. DO-178C/EC-12C is a standard that governs the certification of software for airborne systems in commercial aircraft. The additional supplement DO- 333 enables us to use the formal methods in our technique of verifying the autonomous behaviour of UAV’s. The Mission Manager system is primarily responsible for the execution of behaviour sequence in online and offline mission planning of UAV. This work presents the process of software verification by making use of formal modelling using model checking of the Mission Manager component of ARTIS (Autonomous Rotorcraft Testbed for Intelligent Systems) UAV by gaining advantages from a generic modelling approach. The main idea is to make use of the designed generic models into specific cases like ARTIS in our case. The generic models are designed using the ALFU(R)S (Autonomy Levels For Unmanned Rotorcraft System) framework that delineates the commonalities of several UAVs considered around the world which also includes the ARTIS UAV. Furthermore this work walks through every process involved in model checking like requirements extraction and documentation using a template based method, requirements specification using the temporal logics like LTL and CTL, developing a formal model using NuSMV as a model checking tool to analyze the requirements against the model for the Mission Manager component of MiPlEx (Mission Planning and Execution). Additionally as a validation approach, test sequences are generated by using trap properties or negation properties. This aids for a test generation approach by harnessing counterexample generating capabilities of the NuSMV Model Checker.

In the recent trends, automated systems are increasingly seen to be embedded in human life with the increase of human dependence on software to perform safetycritical tasks like airbag deployment in automobiles to real-time mission planning in UAVs (Unmanned Aircraft Vehicles). The safety-critical nature of the aerospace domain demands for a software without any errors to perform these tasks. Therefore the field of computer science needs to address these challenges by providing necessary formalisms, techniques, and tools that will ensure the correctness of systems despite their complexity. DO-178C/EC-12C is a standard that governs the certification of software for airborne systems in commercial aircraft. The additional supplement DO- 333 enables us to use the formal methods in our technique of verifying the autonomous behaviour of UAV’s. The Mission Manager system is primarily responsible for the execution of behaviour sequence in online and offline mission planning of UAV. This work presents the process of software verification by making use of formal modelling using model checking of the Mission Manager component of ARTIS (Autonomous Rotorcraft Testbed for Intelligent Systems) UAV by gaining advantages from a generic modelling approach. The main idea is to make use of the designed generic models into specific cases like ARTIS in our case. The generic models are designed using the ALFU(R)S (Autonomy Levels For Unmanned Rotorcraft System) framework that delineates the commonalities of several UAVs considered around the world which also includes the ARTIS UAV. Furthermore this work walks through every process involved in model checking like requirements extraction and documentation using a template based method, requirements specification using the temporal logics like LTL and CTL, developing a formal model using NuSMV as a model checking tool to analyze the requirements against the model for the Mission Manager component of MiPlEx (Mission Planning and Execution). Additionally as a validation approach, test sequences are generated by using trap properties or negation properties. This aids for a test generation approach by harnessing counterexample generating capabilities of the NuSMV Model Checker.