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<italic>Domain-specific embedded languages (DSELs) expressed in higher-order, typed (HOT) languages provide a composable framework for domain-specific abstractions. Such a framework is of greater utility than a collection of stand-alone domain-specific languages. Usually, embedded domain specific languages are build on top of a set of domain specific(More)
Helium is a user-friendly compiler designed especially for learning the functional programming language Haskell. The quality of the error messages has been the main concern both in the choice of the language features and in the implementation of the compiler. Helium implements almost full Haskell, where the most notable difference is the absence of type(More)
The MLF type system by Le Botlan and R&#233;my is a natural extension of Hindley-Milner type inference that supports full first-class polymorphism, where types can be of higher-rank and impredicatively instantiated. Even though MLF is theoretically very attractive, it has not seen widespread adoption. We believe that this partly because it is unclear how(More)
HMF is a conservative extension of Hindley-Milner type inference with first-class polymorphism. In contrast to other proposals, HML uses regular System F types and has a simple type inference algorithm that is just a small extension of the usual Damas-Milner algorithm W. Given the relative simplicity and expressive power, we feel that HMF can be an(More)
The increasing popularity of component-based programming tools offer a big opportunity to designers of advanced programming languages, such as Haskell. If we can package our programs as software components, then it is easy to integrate them into applications written in other languages.In earlier work we described a preliminary integration of Haskell with(More)
Mobile devices commonly access shared data stored on a server. To ensure responsiveness, many applications maintain local replicas of the shared data that remain instantly accessible even if the server is slow or temporarily unavailable. Despite its apparent simplicity and commonality, this scenario can be surprisingly challenging. In particular, a correct(More)
Parallel or incremental versions of an algorithm can significantly outperform their counterparts, but are often difficult to develop. Programming models that provide appropriate abstractions to decompose data and tasks can simplify parallelization. We show in this work that the same abstractions can enable both parallel and incremental execution. We present(More)
Building applications that are responsive and can exploit parallel hardware while remaining simple to write, understand, test, and maintain, poses an important challenge for developers. In particular, it is often desirable to enable various tasks to read or modify shared data concurrently without requiring complicated locking schemes that may throttle(More)