Preemptive priority-based scheduling: an appropriate engineering approach
Advances in real-time systems
Synthesis and Stochastic Assessment of Schedules for Lacquer Production
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
Statistical probabilistic model checking with a focus on time-bounded properties
Information and Computation
Task automata: Schedulability, decidability and undecidability
Information and Computation
The Ins and Outs of the Probabilistic Model Checker MRMC
QEST '09 Proceedings of the 2009 Sixth International Conference on the Quantitative Evaluation of Systems
Schedulability analysis of AADL models
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Schedulability analysis using Uppaal: Herschel-Planck case study
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part II
Statistical model checking: an overview
RV'10 Proceedings of the First international conference on Runtime verification
Time for statistical model checking of real-time systems
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Statistical model checking for networks of priced timed automata
FORMATS'11 Proceedings of the 9th international conference on Formal modeling and analysis of timed systems
Checking and distributing statistical model checking
NFM'12 Proceedings of the 4th international conference on NASA Formal Methods
Statistical model checking, refinement checking, optimization, … for stochastic hybrid systems
FORMATS'12 Proceedings of the 10th international conference on Formal Modeling and Analysis of Timed Systems
Quantitative modelling and analysis
ISoLA'12 Proceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: applications and case studies - Volume Part II
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Schedulability analysis is a main concern for several embedded applications due to their safety-critical nature. The classical method of response time analysis provides an efficient technique used in industrial practice. However, the method is based on conservative assumptions related to execution and blocking times of tasks. Consequently, the method may falsely declare deadline violations that will never occur during execution. This paper is a continuation of previous work of the authors in applying extended timed automata model checking (using the tool UPPAAL) to obtain more exact schedulability analysis, here in the presence of non-deterministic computation times of tasks given by intervals [BCET,WCET]. Considering computation intervals makes the schedulability of the resulting task model undecidable. Our contribution is to propose a combination of model checking techniques to obtain some guarantee on the (un)schedulability of the model even in the presence of undecidability. Two methods are considered: symbolic model checking and statistical model checking. Symbolic model checking allows to conclude schedulability --- i.e. absence of deadline violations --- for varying sizes of BCET. However, the symbolic model checking technique is over-approximating for the considered task model and can therefore not be used for disproving schedulability. As a remedy, we show how statistical model checking may be used to generate concrete counter examples witnessing non-schedulability. In addition, we apply statistical model checking to obtain more informative performance analysis --- e.g. expected response times --- when the system is schedulable. The methods are demonstrated on a complex satellite software system yielding new insights useful for the company.