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Determinacy Race Detector for Promises (Artifact)

Authors Feiyang Jin, Lechen Yu

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DARTS.9.2.24.pdf
  • Filesize: 420 kB
  • 2 pages

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Subject Classification

ACM Subject Classification
  • Software and its engineering → Software creation and management
  • Software and its engineering → Software verification and validation
  • Software and its engineering → Software defect analysis
  • Software and its engineering → Software testing and debugging
  • Software and its engineering → Software notations and tools
  • Software and its engineering → General programming languages
  • Software and its engineering → Concurrent programming languages
Keywords
  • Race detection
  • Promise
  • Determinism
  • Determinacy-race

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Abstract

Much of the past work on dynamic data-race and determinacy-race detection algorithms for task parallelism has focused on structured parallelism with fork-join constructs and, more recently, with future constructs. This paper addresses the problem of dynamic detection of data-races and determinacy-races in task-parallel programs with promises, which are more general than fork-join constructs and futures.
We have introduced a dynamic data race detector, DRDP, to help examine task-parallelism programs with promises. DRDP is designed for the HCLIB parallel programming model and capable of pinpointing data races in a HCLIB program. In this artifact, we provide the race detector implementation and all benchmarks to help reproduce the reported results in the paper.

Cite As Get BibTex

Feiyang Jin and Lechen Yu. Determinacy Race Detector for Promises (Artifact). In Special Issue of the 37th European Conference on Object-Oriented Programming (ECOOP 2023). Dagstuhl Artifacts Series (DARTS), Volume 9, Issue 2, pp. 24:1-24:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/DARTS.9.2.24

Author Details

Feiyang Jin
  • College of Computing, Georgia Institute of Technology, Atlanta, USA
Lechen Yu
  • College of Computing, Georgia Institute of Technology, Atlanta, USA

Artifact

  MD5 Sum: a683aa51c2cd00b05cc1b941327713ae (Get MD5 Sum)

Artifact Evaluation Policy

The artifact has been evaluated as described in the ECOOP 2023 Call for Artifacts and the ACM Artifact Review and Badging Policy

Related Article

  • Feiyang Jin, Lechen Yu, Tiago Cogumbreiro, Jun Shirako, and Vivek Sarkar, "Dynamic Determinacy Race Detection for Task-Parallel Programs with Promises", in 37th European Conference on Object-Oriented Programming (ECOOP 2023), LIPIcs, Vol. 263, pp. 13:1-13:30, 2023. https://doi.org/10.4230/LIPIcs.ECOOP.2023.13
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