Demo Data from EDBT 2026 / reviewers in the wild / expert
Raoul Van Doren
dblp:426/3766
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Automated reasoning and model checking › satisfiability
MaxSAT solving |
0.9 | 1 | 2025 | Efficient and Verifiable Proof Logging for MaxSAT Solving · ASE 2025 |
Automated reasoning and model checking › theorem proving
proof logging |
0.9 | 1 | 2025 | Efficient and Verifiable Proof Logging for MaxSAT Solving · ASE 2025 |
Automated reasoning and model checking
satisfiability |
0.9 | 1 | 2025 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Efficient and Verifiable Proof Logging for MaxSAT SolvingabstractMaxSAT 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 |
ASE | 1 |