We develop an explicit two level system that allows programmers to reason about the behavior of effectful programs. The first level is an ordinary ML-style type system, which confers standard properties on program behavior. The second level is a conservative extension of the first that uses a logic of type refinements to check more precise properties of program behavior. Our logic is a fragment of intuitionistic linear logic, which gives programmers the ability to reason locally about changes of program state. We provide a generic resource semantics for our logic as well as a sound, decidable, syntactic refinement-checking system. We also prove that refinements give rise to an optimization principle for programs. Finally, we illustrate the power of our system through a number of examples.

We develop a theory of program specification using the notion of refinement type. This provides a notion of structured specification, useful for verification and program development. We axiomatise the satisfaction of specifications by programs as a generalised typing relation and give rules for refining specifications. A per semantics based on Henkin models is given, for which the system is proven to be sound and complete. Keywords Specification, refinement, verification, type theory, Henkin models 1

Abstract. Refinement is a method to derive correct programs from specifications. A rich type language is another way to ensure program correctness. In this paper, we propose a wide-spectrum language mixing both approaches for the ML language. Mainly, base types are simply included into expressions, introducing underdeterminism and dependent types. We focus on the semantic aspects of such a language. We study three different semantics: a denotational, a deterministic operational and a nondeterministic operational semantics. We prove their equivalence. We show that this language is a conservative extension of ML. 1

Abstract. Refinement is a method to derive correct programs from specifications. A rich type language is another way to ensure program correctness. In this paper, we propose a wide-spectrum language mixing both approaches for the ML language. Mainly, base types are simply included into expressions, introducing underdeterminism and dependent types. We focus on the semantic aspects of such a language. We study three different semantics: a denotational, a deterministic operational and a nondeterministic operational semantics. We prove their equivalence. We show that this language is a conservative extension of ML. 1

Abstract. Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting, and dynamic programming-based algorithms, etc.), and difficult arithmetic programs. 1