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Capturing High-level Nondeterminism in Concurrent Programs for Practical Concurrency Model Agnostic Record and Replay

Aumayr, Dominik, Marr, Stefan, Kaleba, Sophie, Gonzalez Boix, Elisa, Mössenböck, Hanspeter (2021) Capturing High-level Nondeterminism in Concurrent Programs for Practical Concurrency Model Agnostic Record and Replay. The Art, Science, and Engineering of Programming, 5 (3). Article Number 14. ISSN 2473-7321. (doi:10.22152/ (KAR id:86718)


With concurrency being integral to most software systems, developers combine high-level concurrency models in the same application to tackle each problem with appropriate abstractions. While languages and libraries offer a wide range of concurrency models, debugging support for applications that combine them has not yet gained much attention. Record & replay aids debugging by deterministically reproducing recorded bugs, but is typically designed for a single concurrency model only. This paper proposes a practical concurrency-model-agnostic record & replay approach for multi-paradigm concurrent programs, i.e. applications that combine concurrency models. Our approach traces high-level non- deterministic events by using a uniform model-agnostic trace format and infrastructure. This enables ordering- based record & replay support for a wide range of concurrency models, and thereby enables debugging of applications that combine them. In addition, it allows language implementors to add new concurrency mod- els and reuse the model-agnostic record & replay support. We argue that a concurrency-model-agnostic record & replay is practical and enables advanced debugging support for a wide range of concurrency models. The evaluation shows that our approach is expressive and flexible enough to support record & replay of applications using threads & locks, communicating event loops, communicating sequential processes, software transactional memory and combinations of those concurrency models. For the actor model, we reach recording performance competitive with an optimized special-purpose record & replay solution. The average recording overhead on the Savina actor benchmark suite is 10% (min. 0%, max. 23%). The performance for other concurrency models and combinations thereof is at a similar level. We believe our concurrency-model-agnostic approach helps developers of applications that mix and match concurrency models. We hope that this substrate inspires new tools and languages making building and maintaining of multi-paradigm concurrent applications simpler and safer.

Item Type: Article
DOI/Identification number: 10.22152/
Uncontrolled keywords: Multi-Threading SOMns Concurrency Multi-Paradigm Actors STM Record&Replay CSP Nondeterministic
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Stefan Marr
Date Deposited: 22 Feb 2021 14:53 UTC
Last Modified: 18 Sep 2023 22:18 UTC
Resource URI: (The current URI for this page, for reference purposes)

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