We introduce ICE, a robust learning paradigm for synthesizing invariants, that learns using
examples, counter-examples, and implications, and show that it admits honest teachers and …

Symbolic model checking is an important tool for finding bugs (or proving the absence of
bugs) in modern system designs. Because of this, improving the ease of use, scalability, and …

We describe a general framework c2i for generating an invariant inference procedure from
an invariant checking procedure. Given a checker and a language of possible invariants, c2i …

We present Universal Property Directed Reachability (PDR∀), a property-directed semi-
algorithm for automatic inference of invariants in a universal fragment of first-order logic …

In recent times, satisfiability modulo theories (SMT) techniques gained increasing attention
and obtained remarkable success in model-checking infinite-state systems. Still, we believe …

Automated program verification is a difficult problem. It is undecidable even for transition
systems over Linear Integer Arithmetic (LIA). Extending the transition system with theory of …

We propose a novel lazy bounded model checking (BMC) algorithm, Trace Inlining, that
identifies relevant behaviors of the program to compute partial proofs as procedural …

Abstract Model Completeness is a classical topic in model-theoretic algebra, and its
inspiration sources are areas like algebraic geometry and field theory. Yet, recently, there …

Verifying safety and liveness over array systems is a highly challenging problem. Array
systems naturally capture parameterized systems such as distributed protocols with an …

We propose a new automaton model, called quantified data automata over words, that can
model quantified invariants over linear data structures, and build poly-time active learning …