On-the-fly verification of finite transition systems
Formal Methods in System Design - Special issue on computer-aided verification: general methods
Communicating and mobile systems: the &pgr;-calculus
Communicating and mobile systems: the &pgr;-calculus
Communicating sequential processes
Communications of the ACM
Introduction to algorithms
Verisim: Formal Analysis of Network Simulations
IEEE Transactions on Software Engineering
Bounded Model Checking Using Satisfiability Solving
Formal Methods in System Design
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Partial-Order Methods for the Verification of Concurrent Systems: An Approach to the State-Explosion Problem
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Symbolic Model Checking without BDDs
TACAS '99 Proceedings of the 5th International Conference on Tools and Algorithms for Construction and Analysis of Systems
TAPSOFT '95 Proceedings of the 6th International Joint Conference CAAP/FASE on Theory and Practice of Software Development
All from One, One for All: on Model Checking Using Representatives
CAV '93 Proceedings of the 5th International Conference on Computer Aided Verification
Proceedings of the Conference on Logic of Programs
International Journal on Software Tools for Technology Transfer (STTT) - Special section on high-level test of complex systems
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Principles of Model Checking (Representation and Mind Series)
Principles of Model Checking (Representation and Mind Series)
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Simulation modeling for analysis
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A simulation-oriented formalization for a psychological theory
FASE'07 Proceedings of the 10th international conference on Fundamental approaches to software engineering
Requirements analysis of agent-based simulation platforms: state of the art and new prospects
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
The good, the bad, and the ugly, but how ugly is ugly?
RV'07 Proceedings of the 7th international conference on Runtime verification
A formal environment model for multi-agent systems
SBMF'10 Proceedings of the 13th Brazilian conference on Formal methods: foundations and applications
The simulation-based multi-objective evolutionary optimization (SIMEON) framework (Work-in-Progress)
Proceedings of the 2011 Symposium on Theory of Modeling & Simulation: DEVS Integrative M&S Symposium
On-the-fly verification of discrete event simulations by means of simulation purposes
Proceedings of the 2011 Symposium on Theory of Modeling & Simulation: DEVS Integrative M&S Symposium
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Discrete event simulations can be used to analyze natural and artificial phenomena. To this end, one provides models whose behaviors are characterized by discrete events in a discrete timeline. By running such a simulation, one can then observe its properties. This suggests the possibility of applying on-the-fly verification procedures during simulations. In this work we propose a method by which this can be accomplished. It consists of modeling the simulation as a transition system (implicitly), and the property to be verified as another transition system (explicitly). The latter we call a simulation purpose and it is used both to verify the success of the property and to guide the simulation. Algorithmically, this corresponds to building a synchronous product of these two transitions systems on-the-fly and using it to operate a simulator. By the end of such an algorithm, it may deliver either a conclusive or inconclusive verdict. If conclusive, it becomes known whether the simulation model satisfies the simulation purpose. If inconclusive, it is possible to adjust certain parameters and try again. The precise nature of simulation purposes, as well as the corresponding satisfiability relations and verification algorithms, are largely determined by methodological considerations important for the analysis of simulations, whose computational characteristics we compare with empirical scientific procedures. We provide a number of ways in which such a satisfiability relation can be defined formally, the related algorithms, and mathematical proofs of soundness, completeness and complexities. Two application examples are given to illustrate the approach.