Functional Logic Programming (FLP) is a paradigm that extends higher-order functional programming with nondeterministic choice, logical variables, and equational constraints. Starting from the observation that these constructs can be presented as algebraic effects, we rationally reconstruct a core calculus for FLP that is based on call-by-push-value, and supports higher-order functions and recursion. We show how to execute its programs through an abstract machine that implements narrowing. Finally, we present a domain-theoretic semantics based on the lower powerdomain, which we prove to be sound, adequate, and fully abstract with respect to the machine. This leads to an exploration of the limitations of domain theory in modelling FLP.

The monadic shallow linear (MSL) class is a decidable fragment of first-order Horn clauses that was discovered and rediscovered around the turn of the century, with applications in static analysis and verification. We propose a new class of higher-order Horn constraints which extend MSL to higher-order logic and develop a resolution-based decision procedure. Higher-order MSL Horn constraints can quite naturally capture the complex patterns of call and return that are possible in higher-order programs, which make them well suited to higher-order program verification. In fact, we show that the higher-order MSL satisfiability problem and the HORS model checking problem are interreducible, so that higher-order MSL can be seen as a constraint-based approach to higher-order model checking. Finally, we describe an implementation of our decision procedure and its application to verified socket programming.

We propose a new cyclic proof system for automated, equational reasoning about the behaviour of pure functional programs. The key to the system is the way in which cyclic proofs and equational reasoning are mediated by the use of contextual substitution as a cut rule. We show that our system, although simple, already subsumes several of the approaches to implicit induction variously known as “inductionless induction”, “rewriting induction”, and “proof by consistency”. By restricting the form of the traces, we show that global correctness in our system can be verified incrementally, taking advantage of the well-known size-change principle, which leads to an efficient implementation of proof search. Our CycleQ tool, implemented as a GHC plugin, shows promising results on a number of standard benchmarks.

The pattern-match safety problem is to verify that a given functional program will never crash due to non-exhaustive patterns in its function definitions. We present a refinement type system that can be used to solve this problem. The system extends ML-style type systems with algebraic datatypes by a limited form of structural subtyping and environment-level intersection. We describe a fully automatic, sound and complete type inference procedure for this system which, under reasonable assumptions, is worst-case linear-time in the program size. Compositionality is essential to obtaining this complexity guarantee. A prototype implementation for Haskell is able to analyse a selection of packages from the Hackage database in a few hundred milliseconds.