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Dependent Array Type Inference from Tests

  • Conference paper
Verification, Model Checking, and Abstract Interpretation (VMCAI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8931))

Abstract

We present a type-based program analysis capable of inferring expressive invariants over array programs. Our system combines dependent types with two additional key elements. First, we associate dependent types with effects and precisely track effectful array updates, yielding a sound flow-sensitive dependent type system that can capture invariants associated with side-effecting array programs. Second, without imposing an annotation burden for quantified invariants on array indices, we automatically infer useful array invariants by initially guessing very coarse invariant templates, using test suites to exercise the functionality of the program to faithfully instantiate these templates with more precise (likely) invariants. These inferred invariants are subsequently encoded as dependent types for validation. Experimental results demonstrate the utility of our approach, with respect to both expressivity of the invariants inferred, and the time necessary to converge to a result.

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Author information

Authors and Affiliations

  1. Purdue University, USA

    He Zhu & Suresh Jagannathan

  2. Microsoft Research, USA

    Aditya V. Nori

Authors
  1. He Zhu
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  2. Aditya V. Nori
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  3. Suresh Jagannathan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India

    Deepak D’Souza

  2. Microsoft Research India, 560001, Bangalore, India

    Akash Lal

  3. Department of Computer Science, Aalborg University, Selma Lagerlöfs Vej 300, DK-9220, Aalborg East, Denmark

    Kim Guldstrand Larsen

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Zhu, H., Nori, A.V., Jagannathan, S. (2015). Dependent Array Type Inference from Tests. In: D’Souza, D., Lal, A., Larsen, K.G. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2015. Lecture Notes in Computer Science, vol 8931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46081-8_23

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  • DOI: https://doi.org/10.1007/978-3-662-46081-8_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46080-1

  • Online ISBN: 978-3-662-46081-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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