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Automatic Annotating and Checking of Dynamic Ownership

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Programming Languages (SBLP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9889))

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Abstract

Object ownership is an important technique in dealing with object sharing and aliasing to support verification of OO programs. Dynamic Ownership proposes a very flexible encapsulation discipline and has been adopted in Spec#. However, to use this technique, programmers have to keep all the ownership information in mind to decide the validation for modifying one variable. This makes the approach difficult to master and use. In this paper, we apply data-flow analysis to generate most annotations of dynamic ownership automatically, thus can potentially reduce the workload of program verification. Moreover, our technique can reveal ownership topology errors and encapsulation errors. In addition, the entire analysis of our approach is static, thus is efficient.

The work is supported by NSFC under grant No. 61272160 and No. 61202069.

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Notes

  1. 1.

    Some ownership systems support ownership transfer. For simplicity, we ignore ownership transfer in this paper.

  2. 2.

    Leino and Müller [6] allows invariants to mention more objects than our work. Our work will still generate more proper annotations if we extend similar rules.

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Authors and Affiliations

  1. LMAM and Department of Informatics, School of Mathematical Sciences, Peking University, Beijing, China

    Tingting Hu, Haiyang Liu, Ke Zhang & Zongyan Qiu

Authors
  1. Tingting Hu
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  2. Haiyang Liu
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  3. Ke Zhang
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  4. Zongyan Qiu
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Correspondence to Tingting Hu .

Editor information

Editors and Affiliations

  1. Universidade Federal de Pernambuco, Recife, Brazil

    Fernando Castor

  2. State University of New York, Binghamton, New York, USA

    Yu David Liu

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Hu, T., Liu, H., Zhang, K., Qiu, Z. (2016). Automatic Annotating and Checking of Dynamic Ownership. In: Castor, F., Liu, Y. (eds) Programming Languages. SBLP 2016. Lecture Notes in Computer Science(), vol 9889. Springer, Cham. https://doi.org/10.1007/978-3-319-45279-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-45279-1_6

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  • Online ISBN: 978-3-319-45279-1

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