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Finding Reference-Counting Errors in Python/C Programs with Affine Analysis

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ECOOP 2014 – Object-Oriented Programming (ECOOP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8586))

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Abstract

Python is a popular programming language that uses reference counting to manage heap objects. Python also has a Foreign Function Interface (FFI) that allows Python extension modules to be written in native code such as C and C++. Native code, however, is outside Python’s system of memory management; therefore extension programmers are responsible for making sure these objects are reference counted correctly. This is an error prone process when code becomes complex. In this paper, we propose Pungi, a system that statically checks whether Python objects’ reference counts are adjusted correctly in Python/C interface code. Pungi transforms Python/C interface code into affine programs with respect to our proposed abstractions of reference counts. Our system performs static analysis on transformed affine programs and reports possible reference counting errors. Our prototype implementation found over 150 errors in a set of Python/C programs.

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Authors and Affiliations

  1. Lehigh University, Bethlehem, PA, 18015, USA

    Siliang Li & Gang Tan

Authors
  1. Siliang Li
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  2. Gang Tan
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Editors and Affiliations

  1. School of Computing, University of Kent, Canterbury, Kent, UK

    Richard Jones

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Li, S., Tan, G. (2014). Finding Reference-Counting Errors in Python/C Programs with Affine Analysis. In: Jones, R. (eds) ECOOP 2014 – Object-Oriented Programming. ECOOP 2014. Lecture Notes in Computer Science, vol 8586. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44202-9_4

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  • DOI: https://doi.org/10.1007/978-3-662-44202-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44201-2

  • Online ISBN: 978-3-662-44202-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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