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Description
Implicit Self-Adjusting Computation for Purely Functional ProgramsThis dissertation presents implicit self adjusting computation, a type directed technique for translating purely functional programs into self adjusting programs. In this implicit approach, the programmer annotates the (top level) input types of the programs to be translated. Type inference finds all other types, and a type directed translation rewrites the source program into an explicitly self adjusting target program. The type system is related to
This dissertation presents implicit self-adjusting computation, a type directed technique for translating purely functional programs into self-adjusting
programs. In this implicit approach, the programmer annotates the (top-level) input types of the programs to be translated. Type inference finds all other types, and a type-directed translation rewrites the source program
into an explicitly self-adjusting target program. The type system is related to information-flow type systems and enjoys decidable type inference via constraint solving. We prove that the translation outputs well-typed self-adjusting
programs and preserves the source programÕs input-output behavior, guaranteeing that translated programs respond correctly to all changes to their data. Using a cost semantics, we also prove that the translation preserves the
asymptotic complexity of the source program.
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