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LLOR: Automated Repair of OpenMP Programs

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Verification, Model Checking, and Abstract Interpretation (VMCAI 2025)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 15530))

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Abstract

In this paper, we present a technique for repairing data race errors in parallel programs written in C/C++ and Fortran using the OpenMP API. Our technique can also remove barriers that are deemed unnecessary for correctness. We implement these ideas in our tool called LLOR, which takes a language-independent approach to provide appropriate placements of synchronization constructs to avoid data races. To the best of our knowledge, LLOR is the only tool that can repair parallel programs that use the OpenMP API. We showcase the capabilities of LLOR by performing extensive experiments on 415 parallel programs.

Nicola Grandi : Univers-ITA project PRIN 2017 PI.

The author names are in alphabetical order.

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Acknowledgements

We thank the Ministry of Education, India, for their financial support.

Author information

Authors and Affiliations

  1. Indian Institute of Technology Hyderabad, Hyderabad, India

    Gautam Muduganti & Ramakrishna Upadrasta

  2. University of Cambridge, Cambridge, UK

    Utpal Bora

  3. Supra Research, Miami, USA

    Saurabh Joshi

Authors
  1. Utpal Bora
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  2. Saurabh Joshi
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  3. Gautam Muduganti
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  4. Ramakrishna Upadrasta
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Correspondence to Gautam Muduganti .

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Editors and Affiliations

  1. Indian Institute of Technology Bombay, Mumbai, Maharashtra, India

    Krishna Shankaranarayanan

  2. University of Colorado Boulder, Boulder, CO, USA

    Sriram Sankaranarayanan

  3. University of Colorado Boulder, Boulder, CO, USA

    Ashutosh Trivedi

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Bora, U., Joshi, S., Muduganti, G., Upadrasta, R. (2025). LLOR: Automated Repair of OpenMP Programs. In: Shankaranarayanan, K., Sankaranarayanan, S., Trivedi, A. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2025. Lecture Notes in Computer Science, vol 15530. Springer, Cham. https://doi.org/10.1007/978-3-031-82703-7_6

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