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A Set-Based Context Model for Program Analysis

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Programming Languages and Systems (APLAS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12470))

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Abstract

In program analysis, the design of context models is an understudied topic. This paper presents a study of context models for higher-order program analyses and develops new approaches. We develop a context model which equates control flows with the same set of call sites on the program stack, guaranteeing termination without the arbitrary cutoffs which cause imprecision in existing models. We then selectively polyinstantiate these contexts to avoid exponential growth.

We evaluate this model and existing models across multiple higher-order program analysis families. Existing demand-driven analyses cannot support the set model, so we construct a demand-driven analysis, Plume, which can. Our experiments demonstrate that the set-based model is tractable and expressive on representative functional programs for both forward- and demand-driven functional analyses.

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Author information

Authors and Affiliations

  1. Johns Hopkins University, Baltimore, USA

    Leandro Fachinetti, Scott F. Smith & Ke Wu

  2. Swarthmore College, Swarthmore, USA

    Zachary Palmer

  3. Cornell University, Ithaca, USA

    Ayaka Yorihiro

Authors
  1. Leandro Fachinetti
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  2. Zachary Palmer
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  3. Scott F. Smith
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  4. Ke Wu
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  5. Ayaka Yorihiro
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Corresponding author

Correspondence to Zachary Palmer .

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Editors and Affiliations

  1. University of Hong Kong, Hong Kong, Hong Kong

    Bruno C. d. S. Oliveira

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Fachinetti, L., Palmer, Z., Smith, S.F., Wu, K., Yorihiro, A. (2020). A Set-Based Context Model for Program Analysis. In: Oliveira, B.C.d.S. (eds) Programming Languages and Systems. APLAS 2020. Lecture Notes in Computer Science(), vol 12470. Springer, Cham. https://doi.org/10.1007/978-3-030-64437-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-64437-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64436-9

  • Online ISBN: 978-3-030-64437-6

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