Exploratory, Omniscient, and Multiverse Diagnostics in Debuggers for Non-Deterministic Languages

Open Access
Authors
Publication date 2025
Book title SLE'25
Book subtitle Proceedings of SLE 2025 : 18th ACM IGPLAN International Confertence on Software Language Engineering : June 12-13, 2025, Koblenz, Germany
ISBN (electronic)
  • 9798400718847
Event 18th ACM SIGPLAN International Conference on Software Language Engineering, SLE 2025, Co-located with: STAF 2025
Pages (from-to) 134-147
Number of pages 14
Publisher New York, New York: Association for Computing Machinery
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract

Debugging non-deterministic programs is inherently difficult as the compound effects of non-deterministic execution steps is hard to predict and gives rise to a (potentially) vast space of reachable program states such that manual exploration of all reachable states is infeasible. 

Multiverse debugging addresses these problems by realising a fine-grained, exhaustive and interactive process for state space exploration. At SLE2023, Pasquier et al. presented a generic framework that makes exploration practical through user-defined reductions on program states and by proposing expressive logics for defining and searching for states and traces of interest, generalising the concept of breakpoint. The framework has been validated through the case study language AnimUML designed to make non-deterministic UML specifications executable. 

In this paper, we perform additional case studies to evaluate the applicability of the framework. We analyse three non-deterministic, domain-specific languages representing three different domains: grammar engineering, formal operational semantics, and norm engineering. The framework is evaluated against requirements extracted from these domains, resulting in the identification of several limitations of the framework. We then propose a modified and extended framework and apply it to develop multiverse debuggers for the case study languages. The result demonstrates a multiverse debugging framework with more general applicability.

Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3732771.3742719
Other links https://www.scopus.com/pages/publications/105010310985
Downloads
3732771.3742719 (Final published version)
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