Tomás Dacík

dblp:372/7276 · DBLP profile ↗
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4ranked-venue papers
3as first author
4since 2021 · last 2026
0000-0003-4083-8943ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 4 · 3 first-author · 4 since 2021
YearPublicationVenuePosition
2026 Seal: Symbolic Execution with Separation Logic - (Competition Contribution)
Tomás Brablec, Tomás Dacík, Tomás Vojnar
TACAS (2)2
2025 RacerF: Lightweight Static Data Race Detection for C Code (Experience Paper)
Tomás Dacík, Tomás Vojnar
ECOOP1
2025 RacerF: Data Race Detection with Frama-C (Competition Contribution)
abstract
Abstract RacerF is a static analyser for detection of data races in multithreaded C programs implemented as a plugin of the Frama-C platform. The approach behind RacerF is mostly heuristic and relies on analysis of the sequential behaviour of particular threads whose results are generalised using a combination of under- and over-approximating techniques to allow analysis of the multithreading behaviour. In particular, in SV-COMP’25, RacerF relies on the Frama-C’s abstract interpreter EVA to perform the analysis of the sequential behaviour. Although RacerF does not provide any formal guarantees, it ranked second in the NoDataRace-Main sub-category, providing the largest number of correct results (when excluding metaverifiers) and just 4 false positives.
Tomás Dacík, Tomás Vojnar
TACAS (3)1
2024 Deciding Boolean Separation Logic via Small Models
abstract
Abstract We present a novel decision procedure for a fragment of separation logic (SL) with arbitrary nesting of separating conjunctions with boolean conjunctions, disjunctions, and guarded negations together with a support for the most common variants of linked lists. Our method is based on a model-based translation to SMT for which we introduce several optimisations—the most important of them is based on bounding the size of predicate instantiations within models of larger formulae, which leads to a much more efficient translation of SL formulae to SMT. Through a series of experiments, we show that, on the frequently used symbolic heap fragment, our decision procedure is competitive with other existing approaches, and it can outperform them outside the symbolic heap fragment. Moreover, our decision procedure can also handle some formulae for which no decision procedure has been implemented so far.
Tomás Dacík, Adam Rogalewicz, Tomás Vojnar, Florian Zuleger
TACAS (1)1