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Type-sensitive control-flow analysis

John Reppy

The 2006 ACM SIGPLAN Workshop on ML (ML 2006)
Portland, Oregon, 16th September 2006


Higher-order typed languages, such as ML, provide strong support for data and type abstraction. While such abstraction is often viewed as costing performance, there are situations where it may provide opportunities for more aggressive program optimization. Specifically, we can exploit the fact that type abstraction guarantees representation independence, which allows the compiler to specialize data representations. This paper describes a first step in supporting such optimizations; namely a control-flow analysis that uses the program's type information to compute more precise results. We present our algorithm as an extension of Serrano's version of 0-CFA and we show that it respects types. We also discuss applications of the analysis with examples of optimizations enabled by the analysis that would not be possible normal CFA.

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