On computing the fixpoint of a set of boolean equations

This paper presents a method for computing a least fixpoint of a system of equations over booleans. The resulting computation can be significantly shorter than the result of iteratively evaluating the entire system until a fixpoint is reached.Comment: 15 page

A SAT characterization of boolean-program correctness

Boolean programs, imperative programs where all variables have type boolean, have been used effectively as abstractions of device drivers (in Ball and Rajamani's SLAM project). To find errors in these boolean programs, SLAM uses a model checker based on binary decision diagrams (BDDs). As an alternative checking method, this paper defines the semantics of boolean programs by weakest solutions of recursive weakest-precondition equations. These equations are then translated into a satisfiability (SAT) problem. The method uses both BDDs and SAT solving, and it allows an on-the-fly trade-off between symbolic and explicit-state representation of the program's initial state

A SAT Characterization of Boolean-Program Correctness

Boolean programs, imperative programs where all variables have type boolean, have been used effectively as abstractions of device drivers (in Ball and Rajamani’s SLAM project). To find errors in these boolean programs, SLAM uses a model checker based on binary decision diagrams (BDDs). As an alternative checking method, this paper defines the semantics of procedure-less boolean programs by weakest solutions of recursive weakest-precondition equations. These equations are then translated into a satisfiability (SAT) problem. The method uses both BDDs and SAT solving, and it allows an on-the-fly trade-off between symbolic and explicit-state representation of the program’s initial state