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Runtime Instrumentation for Reactive Components

Authors Luca Aceto , Duncan Paul Attard , Adrian Francalanza , Anna Ingólfsdóttir

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Author Details

Luca Aceto
  • Reykjavik University, Iceland
  • Gran Sasso Science Institute, L'Aquila, Italy
Duncan Paul Attard
  • University of Glasgow, UK
Adrian Francalanza
  • University of Malta, Msida, Malta
Anna Ingólfsdóttir
  • Reykjavik University, Iceland

Funding

This work is supported by the Reykjavik University Research Fund, the Doctoral Student Grant (No: 207055) and the MoVeMnt project (No: 217987) under the IRF, and the STARDUST project (No: EP/T014628/1) under the EPSRC.

Acknowledgements

We thank our reviewers and the Artefact Evaluation Committee for their feedback. Thanks also to Keith Bugeja, Simon Fowler, Simon Gay, and Phil Trinder for their input.

Cite AsGet BibTex

Luca Aceto, Duncan Paul Attard, Adrian Francalanza, and Anna Ingólfsdóttir. Runtime Instrumentation for Reactive Components. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 2:1-2:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.ECOOP.2024.2

Abstract

Reactive software calls for instrumentation methods that uphold the reactive attributes of systems. Runtime verification imposes another demand on the instrumentation, namely that the trace event sequences it reports to monitors are sound - that is, they reflect actual executions of the system under scrutiny. This paper presents RIARC, a novel decentralised instrumentation algorithm for outline monitors meeting these two demands. Asynchrony in reactive software complicates the instrumentation due to potential trace event loss or reordering. RIARC overcomes these challenges using a next-hop IP routing approach to rearrange and report events soundly to monitors. RIARC is validated in two ways. We subject its corresponding implementation to rigorous systematic testing to confirm its correctness. In addition, we assess this implementation via extensive empirical experiments, subjecting it to large realistic workloads to ascertain its reactiveness. Our results show that RIARC optimises its memory and scheduler usage to maintain latency feasible for soft real-time applications. We also compare RIARC to inline and centralised monitoring, revealing that it induces comparable latency to inline monitoring in moderate concurrency settings where software performs long-running, computationally-intensive tasks, such as in Big Data stream processing.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Software verification and validation
Keywords
  • Runtime instrumentation
  • decentralised monitoring
  • reactive systems

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