Type feedback vs. concrete type inference: a comparison of optimization techniques for object-oriented languages

  • Authors:
  • Ole Agesen;Urs Hölzle

  • Affiliations:
  • Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, University of California, Santa Barbara, CA

  • Venue:
  • Proceedings of the tenth annual conference on Object-oriented programming systems, languages, and applications
  • Year:
  • 1995

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Abstract

Two promising optimization techniques for object-oriented languages are type feedback (profile-based receiver class prediction) and concrete type inference (static analysis). We directly compare the two techniques, evaluating their effectiveness on a suite of 23 SELF programs while keeping other factors constant.Our results show that both systems inline over 95% of all sends and deliver similar overall performance with one exception: SELF's automatic coercion of machine integers to arbitrary-precision integers upon overflow confounds type inference and slows down arithmetic-intensive benchmarks.We discuss several other issues which, given the comparable run-time performance, may influence the choice between type feedback and type inference.