Predicate Abstraction via Symbolic Decision Procedures

Predicate Abstraction via Symbolic Decision Procedures

We present a new approach for performing predicate abstraction based on symbolic decision procedures. Intuitively, a symbolic decision procedure for a theory takes a set of predicates in the theory and symbolically executes a decision procedure on all the subsets over the set of predicates. The result of the symbolic decision procedure is a shared expression (represented by a directed acyclic g...

Deriving Invariants by Algorithmic Learning, Decision Procedures, and Predicate Abstraction

By combining algorithmic learning, decision procedures, and predicate abstraction, we present an automated technique for finding loop invariants in propositional formulae. Given invariant approximations derived from preand post-conditions, our new technique exploits the flexibility in invariants by a simple randomized mechanism. The proposed technique is able to generate invariants for some Lin...

Inferring Quantified Invariants via Algorithmic Learning, Decision Procedures, and Predicate Abstraction

By combining algorithmic learning, decision procedures, predicate abstraction, and simple templates, we present an automated technique for finding quantified loop invariants. Our technique can find arbitrary first-order invariants (modulo a fixed set of atomic propositions and an underlying SMT solver) in the form of the given template and exploits the flexibility in invariants by a simple rand...

A Symbolic Approach to Predicate Abstraction

IC3 Modulo Theories via Implicit Predicate Abstraction

We present a novel approach for generalizing the IC3 algorithm for invariant checking from finite-state to infinite-state transition systems, expressed over some background theories. The procedure is based on a tight integration of IC3 with Implicit (predicate) Abstraction, a technique that expresses abstract transitions without computing explicitly the abstract system and is incremental with r...