In this paper we present an extension to basic type theory to allow a uniform construction of abstract data types (ADTs) having many of the properties of objects, including abstraction, subtyping, and inheritance. The extension relies on allowing type dependencies for function types to range over a well-founded domain. Using the propositions--as--types correspondence, abstract data types can be identified with logical theories, and proofs of the theories are the objects that inhabit the corresponding ADT. 1 Introduction In the past decade, there has been considerable progress in developing formal account of a theory of objects. One property of object oriented languages that make them popular is that they attack the problem of scale: all object oriented languages provide mechanisms for providing software modularity and reuse. In addition, the mechanisms are intuitive enough to be followed easily by novice programmers. During the same decade, the body of formal mathematics has be...

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The topic of this thesis is the extraction of efficient and readable programs from formal constructive proofs of decidability. The proof methods employed to generate the efficient code are new and result in clean and readable Nuprl extracts for two non-trivial programs. They are based on the use of Nuprl's set type and techniques for extracting efficient programs from induction principles. The constructive formal theories required to express the decidability theorems are of independent interest. They formally circumscribe the mathematical knowledge needed to understand the derived algorithms. The formal theories express concepts that are taught at the senior college level. The decidability proofs themselves, depending on this material, are of interest and are presented in some detail. The proof of decidability of classical propositional logic is relative to a semantics based on Kleene's strong three-valued logic. The constructive proof of intuitionistic decidability presented here is the first machine formalization of this proof. The exposition reveals aspects of the Nuprl tactic collection relevant to the creation of readable proofs; clear extracts and efficient code are illustrated in the discussion of the proofs.