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

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.

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Index Terms

• General and reference

  • Cross-computing tools and techniques

    • Evaluation

    • Metrics

• Software and its engineering

  • Software notations and tools

    • Compilers

    • General programming languages

      • Language types

        • Object oriented languages