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

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.

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Published
2025-06-12
DOI
https://doi.org/10.1145/3732771.3742719
Primary Topic
Machine Learning and Algorithms
Type
article
Field-Weighted Citation Impact
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article

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

Damian Frölich, L. Thomas van Binsbergen, Tommaso Pacciani
Machine Learning and Algorithms
article

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

Damian Frölich, L. Thomas van Binsbergen, Tommaso Pacciani
article en

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.

University of Amsterdam (NL)
Openalex Percentile: Top 93%
Machine Learning and Algorithms
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Exploratory, Omniscient, and Multiverse Diagnostics in Debuggers for Non-Deterministic Languages — Damian Frölich, L. Thomas van Binsbergen, et al. · (2025) | TGRS Research Map | TGRS