First-order logic has proved to be a versatile and expressive tool as the basis of abstract modeling languages. Used to verify complex systems with unbounded domains, such as heap-manipulating programs and distributed protocols, first-order logic, and specifically uninterpreted functions and quantifiers, strike a balance between expressiveness and amenity to automation. However, first-order logic semantics may differ in important ways from the intended semantics of the modeled system, due to the inability to distinguish between finite and infinite first-order structures, for example, or the undefinability of well-founded relations in first-order logic. This semantic gap may give rise to spurious states and unreal behaviors, which only exist as an artifact of the first-order abstraction and impede the verification process.

In this paper we take a step towards bridging this semantic gap. We present an approach for soundly refining the first-order abstraction according to either well-founded semantics or finite-domain semantics, utilizing induction axioms for an abstract order relation, a common primitive in verification. We first formalize sound axiom schemata for each of the aforementioned semantics, based on well-founded induction. Second, we show how to use spurious counter-models, which are necessarily infinite, to guide the instantiation of these axiom schemata. Finally, we present a sound and complete reduction of well-founded semantics and finite-domain semantics to standard semantics in the recently discovered Ordered Self-Cycle (OSC) fragment of first-order logic, and prove that satisfiability under these semantics is decidable in OSC.

We implement a prototype tool to evaluate our approach, and test it on various examples where spurious models arise, from the domains of distributed protocols and heap-manipulating programs. Our tool quickly finds the necessary axioms to refine the semantics, and successfully completes the verification process, eliminating the spurious system states that blocked progress.