Running Pegasus Autocode Programs on Mercury

Making Mercury programs tail recursiveExtended

Making Mercury Programs Tail Recursive

We present two optimizations for making Mercury programs tail recursive. Both operate by taking computations that occur after a recursive call and moving them before the recursive call, modifying them as necessary. The first optimization moves calls to associative predicates; it is a pure source to source transformation. The second optimization moves construction unifications; it required exten...

Running Probabilistic Programs Backwards

Many probabilistic programming languages allow programs to be run under constraints in order to carry out Bayesian inference. Running programs under constraints could enable other uses such as rare event simulation and probabilistic verification—except that all such probabilistic languages are necessarily limited because they are defined or implemented in terms of an impoverished theory of prob...

Simulink Models for Autocode Generation∗

Suppose that you have developed a Simulink model of a virtual world, such as a wall or spring-mass system. We have seen how to choose the parameters of the virtual world so that it has desired properties. For example, we have seen how to choose the spring constant and inertia of the virtual spring-mass system so that it has a desired frequency of oscillation and satisfies a maximum torque limit...

Dependable and ubiquitous Autocode Generation

“Automatic Code Generation” is a process of deriving programs directly from a design representation. Many commercial tools provide this capability. Whilst these tools provide greater flexibility and responsiveness in design, the market is technology-focussed and immature. No infrastructure or established theory exists which could be used to deploy the technology across large projects whilst uph...