EDBT 2026 Demo / reviewers in the wild / expert
Umut Yigit Dural
dblp:437/7227
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0002-8071-3600ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021Theory of computation · 1 · 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.
| Software engineering, system software, and programming languages
1 paper |
Program verification · 100% | |
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 77% Logic in computer science · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification
deductive verification |
1.0 | 1 | 2026 | Caesar: A Deductive Verifier for Probabilistic Programs · CAV (3) 2026 |
Program verification › probabilistic verification
probabilistic program verification |
1.0 | 1 | 2026 | Caesar: A Deductive Verifier for Probabilistic Programs · CAV (3) 2026 |
Automated reasoning and model checking › model checking
probabilistic model checking |
1.0 | 1 | 2026 | Caesar: A Deductive Verifier for Probabilistic Programs · CAV (3) 2026 |
Logic in computer science
program logic |
0.3 | 1 | 2026 | Caesar: A Deductive Verifier for Probabilistic Programs · CAV (3) 2026 |
Methods — techniques the papers use, named apart from their topics
verification condition generation · 2.0probabilistic model checking · 2.0SMT solving · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Caesar: A Deductive Verifier for Probabilistic ProgramsabstractAbstract is a deductive verifier for probabilistic programs. At its core lies , a quantitative intermediate verification language based on the real-valued logic . allows users to express a probabilistic program, its specifications, and proof rules in a programming-language style, so that new proof rules can be easily integrated into the verifier. translates programs into verification conditions, which are then checked using the Z3 SMT solver. It also includes a backend based on probabilistic model checking for a subset of . We report on the results of five years of development of , highlighting its main features and architecture. In particular, we describe recent improvements such as additional proof rules, a model-checking backend, and better diagnostics. Philipp Schröer, Kevin Batz, Umut Yigit Dural, Darion Haase, Benjamin Lucien Kaminski, Joost-Pieter Katoen, Christoph Matheja |
CAV (3) | 3 |