  Answer Set Programming (ASP) is a powerful declarative programming paradigm
commonly used for solving challenging search and optimization problems. The
modeling languages of ASP are supported by sophisticated solving algorithms
(solvers) that make the solution search efficient while enabling the programmer
to model the problem at a high level of abstraction. As an approach to
Knowledge Representation and Reasoning, ASP benefits from its simplicity,
conciseness and rigorously defined semantics. These characteristics make ASP a
straightforward way to develop formally verifiable programs. In the context of
artificial intelligence (AI), the clarity of ASP programs lends itself to the
construction of explainable, trustworthy AI. In support of these goals, my
research is concerned with extending the theory and tools supporting the
verification of ASP progams.
