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

TL;DR

This paper introduces a practical, model-agnostic record & replay system for multi-paradigm concurrent programs, enabling effective debugging across diverse concurrency models with minimal overhead.

Contribution

It proposes a uniform trace format and infrastructure that support concurrency-model-agnostic record & replay, facilitating debugging of applications combining multiple concurrency paradigms.

Findings

Supports a wide range of concurrency models including threads, actors, and transactional memory.

Achieves competitive recording performance, with an average overhead of 10% on actor benchmarks.

Enables debugging of multi-model concurrent applications with minimal performance impact.

Abstract

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 nondeterministic events by using a uniform model-agnostic trace format and infrastructure. This enables orderingbased 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 models 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.