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Raoul Van Doren

dblp:426/3766 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

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

Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Automated reasoning and model checking · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Automated reasoning and model checking › satisfiability
MaxSAT solving
0.912025
Efficient and Verifiable Proof Logging for MaxSAT Solving · ASE 2025
Automated reasoning and model checking › theorem proving
proof logging
0.912025
Efficient and Verifiable Proof Logging for MaxSAT Solving · ASE 2025
Automated reasoning and model checking
satisfiability
0.912025
Efficient and Verifiable Proof Logging for MaxSAT Solving · ASE 2025

Methods — techniques the papers use, named apart from their topics

pseudo-boolean reasoning · 0.9proof logging · 0.9
YearPublicationVenuePosition
2025 Efficient and Verifiable Proof Logging for MaxSAT Solving
abstract
MaxSAT solvers are increasingly used as back-ends in software engineering tools. Yet their results have lacked automatically checkable certificates of optimality. While SAT solvers emit DRAT proofs of (un)satisfiability, MaxSAT must additionally prove that no lower-cost solution exists. Existing approaches either cover only isolated solving paradigms or re-duce MaxSAT reasoning to heavyweight pseudo-Boolean proofs, yielding impractical verification overhead.We present the first MaxSAT-specific proof-logging framework for core-guided OLL solvers. We formalize native inference rules for cores, cliques, hardenings, totalizer updates, and bound adjustments, and implement both a human-readable logger and a compact binary DAG logger in EvalMaxSAT. Evaluation on the 2024 MaxSAT competition dataset confirm the practicality and scalability of our certification pipeline, paving the way for trustworthy, solver use.
Raoul Van Doren, Timos Antonopoulos, Ruzica Piskac
ASE1