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Binding-time analysis for Standard ML
We present an efficient base algorithm for binding-time analysis based on constraint solving and the union-find algorithm. In practice it has been used to handle all of Standard ML except modules and
Hand-Writing Program Generator Generators
TLDR
This paper argues that hand-writing a program generator generator has a number of advantages compared to generating aprogram generator generator by self-application of a partial evaluator, and reports on some promising experiments made with a prototype implementation of a program generators generator for most of the Standard ML Core Language.
Very Efficient Conversions
Using program transformation techniques from the field of partial evaluation an automatic tool for generating very efficient conversions from equality-stating theorems has been implemented.
Partial Evaluation of Standard ML
TLDR
It is shown in this thesis that the cogen approach to the partial evaluation of the core of Standard ML is in many aspects superior to the traditional approach and that it eliminates the need for self-applying the specializer.