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NuSMV 2: An OpenSource Tool for Symbolic Model Checking
This paper describes version 2 of the NuSMV tool, a state-of-the-art symbolic model checker designed to be applicable in technology transfer projects and is robust and close to industrial systems standards.
NUSMV: A New Symbolic Model Verifier
NUSMV, a new symbolic model checker developed as a joint project between Carnegie Mellon University and Istituto per la Ricerca Scientifica e Tecnolgica (IRST), is described, a well structured, open, flexible and documented platform for model checking.
NUSMV: a new symbolic model checker
- A. Cimatti, E. Clarke, Fausto Giunchiglia, Marco Roveri
- Computer ScienceInternational Journal on Software Tools for…
- 1 March 2000
A new symbolic model checker, called NuSMV, developed as part of a joint project between CMU and IRST, and a detailed description of its functionalities, architecture, and implementation is described.
Weak, strong, and strong cyclic planning via symbolic model checking
Nusmv version 2: an opensource tool for symbolic model checking
The nuXmv Symbolic Model Checker
The nuXmv symbolic model checker for finite- and infinite-state synchronous transition systems is described, which complements the basic verification techniques of nu Xmv with state-of-the-art verification algorithms.
Specifying and analyzing early requirements in Tropos
- A. Fuxman, Lin Liu, J. Mylopoulos, Marco Roveri, P. Traverso
- Computer ScienceRequirements Engineering
- 1 May 2004
We present a framework that supports the formal verification of early requirements specifications. The framework is based on Formal Tropos, a specification language that adopts primitive concepts for…
Planning in Nondeterministic Domains under Partial Observability via Symbolic Model Checking
An algorithm is proposed that searches through a (possibly cyclic) and-or graph induced by the domain and generates conditional plans that are guaranteed to achieve the goal despite of the uncertainty in the initial condition, the uncertain effects of actions, and the partial observability of the domain.
Strong planning under partial observability
Conformant Planning via Symbolic Model Checking
This paper presents a general planning algorithm for conformant planning, which applies to fully nondeterministic domains, with uncertainty in the initial condition and in action effects, and presents the most effective approach, CMBP (Conformant Model Based Planner), an efficient implementation of the data structures and algorithm directly based on BDD manipulations.