In this paper, we explore an extension to Haskell type classes that allows a type class declaration to define data types as well as values (or methods). Similarly, an instance declaration gives a witness for such data types, as well as a witness for each method. It turns out that this extension directly supports the idea of a type-indexed type, and is useful in many applications, especially for self-optimising libraries that adapt their data representations and algorithms in a type-directed manner.

Constraint Handling Rules (CHR) is a high-level rule-based programming language which is increasingly used for general purposes. We introduce the CHR machine, a model of computation based on the operational semantics of CHR. Its computational power and time complexity properties are compared to those of the well-understood Turing machine and Random Access Memory machine. This allows us to prove the interesting result that every algorithm can be implemented in CHR with the best known time and space complexity. We also investigate the practical relevance of this result and the constant factors involved. Finally we expand the scope of the discussion to other (declarative) programming languages.

A heterogeneous collection is a datatype that is capable of storing data of different types, while providing operations for look-up, update, iteration, and others. There are various kinds of heterogeneous collections, differing in representation, invariants, and access operations. We describe HLIST — a Haskell library for strongly typed heterogeneous collections including extensible records. We illustrate HLIST’s benefits in the context of type-safe database access in Haskell. The HLIST library relies on common extensions of Haskell 98. Our exploration raises interesting issues regarding Haskell’s type system, in particular, avoidance of overlapping instances, and reification of type equality and type unification.

Functional dependencies are a popular and useful extension to Haskell style type classes. In this paper, we give a reformulation of functional dependencies in terms of Constraint Handling Rules (CHRs). In previous work, CHRs have been employed for describing user-programmable type extensions in the context of Haskell style type classes. Here, we make use of CHRs to provide for the first time a concise result that under some sufficient conditions, functional dependencies allow for sound and decidable type inference. The sucient conditions imposed on functional dependencies can be very limiting. We show how to safely relax these conditions.

Google’s MapReduce programming model serves for processing large data sets in a massively parallel manner. We deliver the first rigorous description of the model including its advancement as Google’s domain-specific language Sawzall. To this end, we reverse-engineer the seminal papers on MapReduce and Sawzall, and we capture our findings as an executable specification. We also identify and resolve some obscurities in the informal presentation given in the seminal papers. We use typed functional programming (specifically Haskell) as a tool for design recovery and executable specification. Our development comprises three components: (i) the basic program skeleton that underlies MapReduce computations; (ii) the opportunities for parallelism in executing MapReduce computations; (iii) the fundamental characteristics of Sawzall’s aggregators as an advancement of the MapReduce approach. Our development does not formalize the more implementational aspects of an actual, distributed execution of MapReduce computations.

Abstract. There are a number of extended forms of algebraic data types such as type classes with existential types and generalized algebraic data types. Such extensions are highly useful but their interaction has not been studied formally so far. Here, we present a unifying framework for these extensions. We show that the combination of type classes and generalized algebraic data types allows us to express a number of interesting properties which are desired by programmers. We support type checking based on a novel constraint solver. Our results show that our system is practical and greatly extends the expressive power of languages such as Haskell and ML. 1

A session type is an abstraction of a set of sequences of heterogeneous values sent and received over a communication channel. Session types can be used for specifying stream-based Internet protocols.

Constraint Handling Rules (CHRs) are a high-level rule-based programming language commonly used to define constraint solvers. We present a method for automatic implication checking between constraints of CHR solvers. Supporting implication is important for implementing extensible solvers and reification, and for building hierarchical CHR constraint solvers. Our method does not copy the entire constraint store, but performs the check in place using a trailing mechanism. The necessary code enhancements can be done by automatic program transformation based on the rules of the solver. We extend our method to work for hierarchically organized modular CHR solvers. We show the soundness of our method and its completeness for a restricted class of canonical solver as well as for specific existing non-canonical CHR solvers. We evaluate our trailing method experimentally by comparing with the copy approach: runtime is almost halved.

Constraint Handling Rules (CHR) is a high-level programming language based on multiheaded multiset rewrite rules. Originally designed for writing user-defined constraint solvers, it is now recognized as an elegant general purpose language. CHR-related research has surged during the decade following the previous survey by Frühwirth (1998). Covering more than 180 publications, this new survey provides an overview of recent results in a wide range of research areas, from semantics and analysis to systems, extensions and applications.

Abstract. CHR is a popular high-level language for implementing constraint solvers and other general purpose applications. It has a wellestablished operational semantics and quite a number of different implementations, prominently in Prolog. However, there is still much room for exploring the compilation of CHR to Prolog. Nearly all implementations rely on attributed variables. In this paper, we explore a different implementation target for CHR: B-Prolog’s Action Rules (ARs). As a rule-based language, it is a good match for particular aspects of CHR. However, the strict adherence to CHR’s refined operational semantics poses some difficulty. We report on our work in progress: a novel compilation schema, required changes to the AR language and the preliminary benchmarks and experiences. 1