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Juvix empowers developers to write code in a high-level, functional language, compile it to gas-efficient output VM instructions, and formally verify the safety of their contracts prior to deployment and execution.
7db74442d4
* Closes #3028 * Detects fully-applied expressions of the form ``` f a (\{ x1 .. xk := body }) a' ``` where `f` is a recursive function which does not modify its function argument (the one for which a lambda is provided), i.e., passes it to recursive invocations unchanged (it's the second argument in the above example). A function `f` satisfying this requirement implements some kind of loop with the lambda-expression usually being the loop body / action. Let e.g. `body = g x1 .. xk b1 b2` where `b1`, `b2` do not contain any variables bound in the lambda (`x1`,..,`xk`). If `b1`, `b2` are non-trivial (require computation), then these loop-invariant subexpressions are hoisted outside of the loop, obtaining: ``` let y1 := b1; y2 := b2; in f a (\{ x1 .. xk := g x1 .. xk y1 y2) a' ``` * Adds a volatility info in Core which prevents the lets created by loop-invariant expression hoisting from being folded back. * Removes potential duplication in the specialization optimization. * Adds another optimization phase before lambda-lifting where hoisting of loop-invariant subexpressions is performed. This allows to reduce the number of iterations in the main optimization phase after lambda-lifting. |
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Juvix
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This repository is specifically dedicated to the compiler of the Juvix programming language.
For any Juvix-related inquiries, we strongly advise visiting the following resources.
Our documentation offers an in-depth understanding of the Juvix programming language. It encompasses a language reference, examples, blog posts, and numerous other resources to facilitate effective use of Juvix.