Severely resource-constrained devices present a confounding challenge to the functional programmer: we are used to having powerful abstraction facilities at our fingertips, but how can we make use of these tools on a device with an 8- or 16-bit CPU and at most tens of kilobytes of RAM? Motivated by this challenge, we have developed Flask, a domain specific language embedded in Haskell that brings the power of functional programming to sensor networks, collections of highly resource-constrained devices. Flask consists of a staging mechanism that cleanly separates node-level code from the meta-language used to generate node-level code fragments; syntactic support for embedding standard sensor network code; a restricted subset of Haskell that runs on sensor networks and constrains program space and time consumption; a higher-level “data stream ” combinator library for quickly constructing sensor network programs; and an extensible runtime that provides commonly-used services. We demonstrate Flask through several small code examples as well as a compiler that generates node-level code to execute a network-wide query specified in a SQL-like language. We show how using Flask ensures constraints on space and time behavior. Through microbenchmarks and measurements on physical hardware, we demonstrate that Flask produces programs that are efficient in terms of CPU and memory usage and that can run effectively on existing sensor network hardware.

Abstract. We propose a novel, comonadic approach to dataflow (streambased) computation. This is based on the observation that both general and causal stream functions can be characterized as coKleisli arrows of comonads and on the intuition that comonads in general must be a good means to structure context-dependent computation. In particular, we develop a generic comonadic interpreter of languages for context-dependent computation and instantiate it for stream-based computation. We also discuss distributive laws of a comonad over a monad as a means to structure combinations of effectful and context-dependent computation. We apply the latter to analyse clocked dataflow (partial stream based) computation. 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 propose a novel, comonadic approach to dataflow (stream-based) computation. This is based on the observation that both general and causal stream functions can be characterized as coKleisli arrows of comonads and on the intuition that comonads in general must be a good means to structure context-dependent computation. In particular, we develop a generic comonadic interpreter of languages for contextdependent computation and instantiate it for stream-based computation. We also discuss distributive laws of a comonad over a monad as a means to structure combinations of effectful and context-dependent computation. We apply the latter to analyse clocked dataflow (partial stream based) computation. 1

monads are promiscuous

monads are promiscuous

The ForSyDe (Formal System Design) methodology is targeted at modelling systems, with the goal of using a high level of abstraction in the specification of its models. Although it is a general system modelling methodology, the initial scope of ForSyDe has specifically been Synchronous Systems (systems in which a global clock is used to synchronize the different parts of the system). A well-known type of such system is synchronous hardware, which is the main subject of this thesis. A synchronous system in ForSyDe is based on the concept of processes which “map input signals onto output signals”. Currently, the software implementation of ForSyDe is based upon the Haskell programming language. The designer specifies the system model in Haskell as a network of cooperating process constructors with the assistance of the ForSyDe Library. Until now, there has not been an automated way to synthesize ForSyDe models (i.e. generate an equivalent low-level implementation from which to