Many computational problems require reasoning about relational structures. Examples include high-level system design, architectural configuration of network systems, reasoning about ontologies, and verification of programs with linked data structures. Traditionally, relational models are translated to propositional formulas and then solved by leveraging SAT solvers. However, SAT solvers can only reason about problems within a finite scope, i.e, concrete cardinality bounds on the relations involved. SMT solvers, on the other hand, are efficient tools that can check automatically the satisfiability of complex constraints over several domains without scope restrictions. They are used as the back-end solvers in many verification tools. To break the limitation of bounded analysis, this thesis presents a many-sorted relational logic in SMT where relations of arity n are defined as sets of n-tuples with parametrized sorts for tuple elements. We define a version of this logic as a first-order theory of finite relations where relation terms are built from relation constants and variables, set operators, and relational operators such as join, transpose, product, and transitive closure. We also present a deductive calculus for that theory and provide proofs of refutation soundness and model soundness of our calculus. In addition, we implement the calculus as a relational solver in the SMT solver CVC4, expanding its already large set of built-in theories, and evaluate the relational solver in two applications: Alloy and Ontology, showing promising results. Moreover, with the goal of improving the performance of SMT solvers in general, we present a symmetry detection algorithm to detect symmetries in SMT formulas and present a symmetry breaking algorithm to generate blocking constraints that eliminate those symmetries. We then discuss an experimental evaluation of our implementation of these algorithms in CVC4 against SMT-LIB benchmarks.

A semigroup is simply a set with an associative binary operation; computational semigroup theory is the branch of mathematics concerned with developing techniques for computing with semigroups, as well as investigating semigroups with the help of computers. This thesis explores both sides of computational semigroup theory, across several topics, especially in the finite case. The central focus of this thesis is computing and describing maximal subsemigroups of finite semigroups. A maximal subsemigroup of a semigroup is a proper subsemigroup that is contained in no other proper subsemigroup. We present novel and useful algorithms for computing the maximal subsemigroups of an arbitrary finite semigroup, building on the paper of Graham, Graham, and Rhodes from 1968. In certain cases, the algorithms reduce to computing maximal subgroups of finite groups, and analysing graphs that capture information about the regular I-classes of a semigroup. We use the framework underpinning these algorithms to describe the maximal subsemigroups of many families of finite transformation and diagram monoids. This reproduces and greatly extends a large amount of existing work in the literature, and allows us to easily see the common features between these maximal subsemigroups. This thesis is also concerned with direct products of semigroups, and with a special class of semigroups known as Rees 0-matrix semigroups. We extend known results concerning the generating sets of direct products of semigroups; in doing so, we propose techniques for computing relatively small generating sets for certain kinds of direct products. Additionally, we characterise several features of Rees 0-matrix semigroups in terms of their underlying semigroups and matrices, such as their Green's relations and generating sets, and whether they are inverse. In doing so, we suggest new methods for computing Rees 0-matrix semigroups.