of states. We describe a general method that represents the state space symbolical/y instead of explicitly. The generality of our method comes from using a dialect of the Mu-Calculus as the primary specification language. We describe a model checking algorithm for Mu-Calculus formulas that uses Bryant’s

the problem of automating unit testing with memory graphs as inputs. The approach used builds on previous work combining symbolic and concrete execution, and more specifically, using such a combination to generate test inputs to explore all feasible execution paths. The current work develops a method

We introduce program shepherding, a method for monitoring control flow transfers during program execution to enforce a security policy. Program shepherding provides three techniques as building blocks for security policies. First, shepherding can restrict execution privileges on the basis of code

approaches. First, we de ne a source to source translation to instrument a program, which enables standard model checkers to perform symbolic execution of the program. Second, we give a novel symbolic execution algorithm that handles dynamically allocated structures (e.g., lists and trees), method

Abstract. We describe a sound method for automatically proving Hoare triples for loop-free code in Separation Logic, for certain preconditions and postconditions (symbolic heaps). The method uses a form of symbolic execution, a decidable proof theory for symbolic heaps, and extraction of frame

such systems against specifications written in the probabilistic temporal logics PCTL and CSL. The tool features three model checking engines: one symbolic, using BDDs (binary decision diagrams) and MTBDDs (multi-terminal BDDs); one based on sparse matrices; and one which combines both symbolic and sparse

This paper presents an original method to compare two synchronous sequential machines. The method consists in a breadth first traversal of the product machine during which symbolic expressions of its observable behaviour are computed. The method uses formal manipulations on boolean functions

in the recognized action sequence is analyzed, which results in a hierarchical task plan describing the higher level structure of the task. In another workspace with a different initial state, the system re-instantiates and executes the task plan to accomplish an equivalent goal. The effectiveness of our method

, and the importance of random number generator numerical resolution in stochastic simulation. Availability: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel), and Sun Solaris (SPARC), as well as the full source code under an open source license from

Abstract. A method of symbolic model checking is introduced that uses conjunctive normal form (CNF) rather than binary decision diagrams (BDD’s) and uses a SAT-based approach to quantifier elimination. This method is compared to a traditional BDD-based model checking approach using a set