Theoretical Computer Science
The complexity of probabilistic verification
Journal of the ACM (JACM)
IEEE Spectrum
IEEE Transactions on Software Engineering - Special issue on formal methods in software practice
Symbolic model checking using SAT procedures instead of BDDs
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Model-checking continuous-time Markov chains
ACM Transactions on Computational Logic (TOCL)
Performance Analysis of Communication Systems with Non-Markovian Stochastic Petri Nets
Performance Analysis of Communication Systems with Non-Markovian Stochastic Petri Nets
Performance of Computer Communication Systems: A Model-Based Approach
Performance of Computer Communication Systems: A Model-Based Approach
MoDeST - A Modelling and Description Language for Stochastic Timed Systems
PAPM-PROBMIV '01 Proceedings of the Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Model-Checking for Probabilistic Real-Time Systems (Extended Abstract)
ICALP '91 Proceedings of the 18th International Colloquium on Automata, Languages and Programming
Verifying Quantitative Properties of Continuous Probabilistic Timed Automata
CONCUR '00 Proceedings of the 11th International Conference on Concurrency Theory
PRISM: Probabilistic Symbolic Model Checker
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Model checking for probability and time: from theory to practice
LICS '03 Proceedings of the 18th Annual IEEE Symposium on Logic in Computer Science
Probabilistic symbolic model checking with PRISM: a hybrid approach
International Journal on Software Tools for Technology Transfer (STTT) - Special section on tools and algorithms for the construction and analysis of systems
Automatic verification of probabilistic concurrent finite state programs
SFCS '85 Proceedings of the 26th Annual Symposium on Foundations of Computer Science
Symbolic analysis for GSMP models with one stateful clock
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Fixed-delay events in generalized semi-Markov processes revisited
CONCUR'11 Proceedings of the 22nd international conference on Concurrency theory
Performance evaluation of schedulers in a probabilistic setting
FORMATS'11 Proceedings of the 9th international conference on Formal modeling and analysis of timed systems
As soon as probable: optimal scheduling under stochastic uncertainty
TACAS'13 Proceedings of the 19th international conference on Tools and Algorithms for the Construction and Analysis of Systems
A maximal entropy stochastic process for a timed automaton,
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
Transient analysis of networks of stochastic timed automata using stochastic state classes
QEST'13 Proceedings of the 10th international conference on Quantitative Evaluation of Systems
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Model checking is a popular algorithmic verification technique for checking temporal requirements of mathematical models of systems. In this paper, we consider the problem of verifying bounded reachability properties of stochastic real-time systems modeled as generalized semi-Markov processes (GSMP). While GSMPs is a rich model for stochastic systems widely used in performance evaluation, existing model checking algorithms are applicable only to subclasses such as discrete-time or continuous-time Markov chains. The main contribution of the paper is an algorithm to compute the probability that a given GSMP satisfies a property of the form “can the system reach a target before time T within k discrete events, while staying within a set of safe states”. For this, we show that the probability density function for the remaining firing times of different events in a GSMP after k discrete events can be effectively partitioned into finitely many regions and represented by exponentials and polynomials. We report on illustrative examples and their analysis using our techniques.