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Type-directed flow analysis for typed intermediate languages

  • Functional Programming II
  • Conference paper
  • First Online:
Static Analysis (SAS 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1302))

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Abstract

Flow analysis is especially valuable for optimizing functional languages because control-flow information is not syntactically apparent in higher-order programs. Flow analyses typically operate on untyped languages. However, recent compilers for typed functional languages such as ML and Haskell use a typed intermediate language to expose data representations for optimization. This paper presents a polyvariant flow analysis framework for the predicative subset of system F, a common basis for typed intermediate languages. Analyses in this framework can take advantage of types to analyze programs more precisely. We study a specific analysis called S RT that uses types to control polyvariance. We prove that S RT respects types: whenever it assigns abstract value \(\hat \upsilon\)to a variable and the type system assigns type σ to the same variable, then \(\left[ {\hat \upsilon } \right] \subseteq \left[ \sigma \right]\), where [ · ] denotes a set of values. S RT does not terminate 1569 1655 V 3 for some programs. We present several variants of S RT that are better suited to practical use.

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Authors and Affiliations

  1. NEC Research Institute, 4 Independence Way, 08540, Princeton, NJ

    Suresh Jagannathan, Stephen Weeks & Andrew Wright

Authors
  1. Suresh Jagannathan
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  2. Stephen Weeks
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  3. Andrew Wright
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Pascal Van Hentenryck

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© 1997 Springer-Verlag Berlin Heidelberg

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Jagannathan, S., Weeks, S., Wright, A. (1997). Type-directed flow analysis for typed intermediate languages. In: Van Hentenryck, P. (eds) Static Analysis. SAS 1997. Lecture Notes in Computer Science, vol 1302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032745

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  • DOI: https://doi.org/10.1007/BFb0032745

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63468-3

  • Online ISBN: 978-3-540-69576-9

  • eBook Packages: Springer Book Archive

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