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Monadic effect systems provide a unified way of tracking effects of computations, but there is no unified mechanism for tracking how computations rely on the environment in which they are executed. This is becoming an important problem for modern software – we need to track where distributed computations run, which resources a program uses and how they use(More)
A fully automatic, compiler-driven approach to parallelisation can result in unpredictable time and space costs for compiled code. On the other hand, a fully manual approach to parallelisation can be long, tedious, prone to errors, hard to debug, and often architecture-specific. We present a declarative domain-specific language, Ypnos, for expressing(More)
Many of the computer models used in scientific research have been developed in Fortran over many years. This evolutionary process means these models often use deprecated language features and idioms that impede software maintenance, understandability, extension, and verification. To mitigate this, we built CamFort, an open-source automatic refactoring tool(More)
Scientific models are often expressed as large and complicated programs. These programs embody numerous assumptions made by the developer (e.g., for differential equations, the discretization strategy and resolution). The complexity and pervasiveness of these assumptions means that often the only true description of the model is the software itself. This(More)
The notion of <i>context</i> in functional languages no longer refers just to variables in scope. Context can capture additional properties of variables (usage patterns in linear logics; caching requirements in dataflow languages) as well as additional resources or properties of the execution environment (rebindable resources; platform version in a(More)