Abstract. In this paper, we show how Miquel’s Implicit Calculus of Constructions (ICC) can be used as a programming language featuring dependent types. Since this system has an undecidable type-checking, we introduce a more verbose variant, called ICC ∗ which fixes this issue. Datatypes and program specifications are enriched with logical assertions (such as preconditions, postconditions, invariants) and programs are decorated with proofs of those assertions. The point of using ICC ∗ rather than the Calculus of Constructions (the core formalism of the Coq proof assistant) is that all of the static information (types and proof objects) is transparent, in the sense that it does not affect the computational behavior. This is concretized by a built-in extraction procedure that removes this static information. We also illustrate the main features of ICC ∗ on classical examples of dependently typed programs. 1

Abstract. In this paper we use the Epigram language to define the universe of regular tree types—closed under empty, unit, sum, product and least fixpoint. We then present a generic decision procedure for Epigram’s in-built equality at each type, taking a complementary approach to that of Benke, Dybjer and Jansson [7]. We also give a generic definition of map, taking our inspiration from Jansson and Jeuring [21]. Finally, we equip the regular universe with the partial derivative which can be interpreted functionally as Huet’s notion of ‘zipper’, as suggested by McBride in [27] and implemented (without the fixpoint case) in Generic Haskell by Hinze, Jeuring and Löh [18]. We aim to show through these examples that generic programming can be ordinary programming in a dependently typed language. 1

Abstract. This paper considers the use of dependent types to capture information about dynamic resource usage in a static type system. Dependent types allow us to give (explicit) proofs of properties with a program; we present a dependently typed core language ��, and define a framework within this language for representing size metrics and their properties. We give several examples of size bounded programs within this framework and show that we can construct proofs of their size bounds within ��. We further show how the framework handles recursive higher order functions and sum types, and contrast our system with previous work based on sized types. 1

We exhibit the rationale behind the design of Epigram, a dependently typed programming language and interactive program development system, using refinements of a well known program—merge sort—as a running example. We discuss its relationship with other proposals to introduce aspects of dependent types into functional programming languages and sketch some topics for further work in this area. 1.

Abstract. We introduce Erasure Pure Type Systems, anextensionto Pure Type Systems with an erasure semantics centered around a type constructor ∀ indicating parametric polymorphism. The erasure phase is guided by lightweight program annotations. The typing rules guarantee that well-typed programs obey a phase distinction between erasable (compile-time) and non-erasable (run-time) terms. The erasability of an expression depends only on how its value is used in the rest of the program. Despite this simple observation, most languages treat erasability as an intrinsic property of expressions, leading to code duplication problems. Our approach overcomes this deficiency by treating erasability extrinsically. Because the execution model of EPTS generalizes the familiar notions of type erasure and parametric polymorphism, we believe functional programmers will find it quite natural to program in such a setting. 1

Dependent types allow a programmer to express invariant properties of functions, such as the relationship between the input and output lengths of a list. Several “lightweight” approaches to dependent types have been proposed for existing systems, such as Haskell’s Generalised Algebraic Data Types or Type Families. Such approaches are lightweight in the sense that they require minimal modifications to existing systems. However, while these extensions are apparently simple, we find that we often run into limitations fairly quickly. In this paper we will explore these limitations, and show that a full dependent type system allows more straightforward implementation of simple invariants without restricting expressivity.

This paper is part of a line of work on using the logical techniques of polarity and focusing to design a dependent programming language, with particular emphasis on programming with deductive systems such as programming languages and proof theories. Polarity emphasizes the distinction between positive types, which classify data, and negative types, which classify computation. In previous work, we showed how to use Zeilberger’s higher-order formulation of focusing to integrate a positive function space for representing variable binding, an essential tool for specifying logical systems, with a standard negative computational function space. However, our previous work considers only a simply-typed language. The central technical contribution of the present paper is to extend higher-order focusing with a form of dependency that we call positively dependent types: We allow dependency on positive data, but not negative computation, and we present the syntax of dependent pair and function types using an iterated inductive definition, mapping positive data to types, which gives an account of type-level computation. We construct our language inside the dependently typed programming language Agda 2, making essential use of coinductive types and induction-recursion.

We present an implementation in Haskell of a dependently-typed lambda calculus that can be used as the core of a programming language. We show that a dependently-typed lambda calculus is no more difficult to implement than other typed lambda calculi. In fact, our implementation is almost as easy as an implementation of the simply typed lambda calculus, which we emphasize by discussing the modifications necessary to go from one to the other. We explain how to add data types and write simple programs in the core language, and discuss the steps necessary to build a full-fledged programming language on top of our simple core.

Dependently typed programmers are encouraged to use inductive families to integrate constraints with data construction. Different constraints are used in different contexts, leading to different versions of datatypes for the same data structure. For example, sequences might be constrained by length or by an ordering on elements, giving rise to different datatypes “vectors ” and “sorted lists ” for the same underlying data structure of sequences. Modular implementation of common operations for these structurally similar datatypes has been a longstanding problem. We propose a datatype-generic solution, in which we axiomatise a family of isomorphisms between datatypes and their more refined versions as datatype refinements, and show that McBride’s ornaments can be translated into such refinements. With the ornamentinduced refinements, relevant properties of the operations can be separately proven for each constraint, and after the programmer selects several constraints to impose on a basic datatype and synthesises a new datatype incorporating those constraints, the operations can be routinely upgraded to work with the synthesised datatype. 1

Dependent types and multi stage programming have both been used, separately, as implementation techniques for programming languages. Each technique has its own advantages — with dependent types, we can verify aspects of interpreters and compilers such as type safety and stack invariants. Multi stage programming, on the other hand, can give the implementor access to underlying compiler technology; a staged interpreter is a translator. In this paper, we investigate how we might combine these techniques to implement a compiler for a resource-safe functional programming language for embedded systems. 1