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Watch a 21-minute conference presentation from POPL 2018 exploring a groundbreaking partial evaluation technique that achieves Jones-optimality through specialization-safe normalization. Learn how researchers from UCLA developed the first type-checked, self-applicable partial evaluator that guarantees generation of type-correct code while removing entire layers of interpretation. Discover the novel affine-variable static analysis that enables decreased program runtime and see demonstrations of Jones-optimality across multiple evaluation settings including call-by-value, normal-order, and memoized normal-order reduction. Explore how this technique enables the Futamura projections and examine experimental results testing Jones-optimality with three different self-interpreters, all implemented in the Fωµi meta-programming language.
