EDBT 2026 Demo / reviewers in the wild / expert
Julian Müllner
dblp:348/5288
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2024
0009-0006-2909-2297ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-author · 2 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 · 67% Program analysis · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification
invariant generation |
0.8 | 1 | 2024 | Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs · Proc. ACM Program. Lang. 2024 |
Program verification › invariant generation
polynomial invariants |
0.8 | 1 | 2024 | Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs · Proc. ACM Program. Lang. 2024 |
Program analysis › static analysis
probabilistic program analysis |
0.8 | 1 | 2024 | Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs · Proc. ACM Program. Lang. 2024 |
Methods — techniques the papers use, named apart from their topics
skolem problem reduction · 0.8invariant ideals · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) ProgramsabstractWe show that computing the strongest polynomial invariant for single-path loops with polynomial assignments is at least as hard as the Skolem problem, a famous problem whose decidability has been open for almost a century. While the strongest polynomial invariants are computable for affine loops , for polynomial loops the problem remained wide open. As an intermediate result of independent interest, we prove that reachability for discrete polynomial dynamical systems is Skolem -hard as well. Furthermore, we generalize the notion of invariant ideals and introduce moment invariant ideals for probabilistic programs. With this tool, we further show that the strongest polynomial moment invariant is (i) uncomputable, for probabilistic loops with branching statements, and (ii) Skolem -hard to compute for polynomial probabilistic loops without branching statements. Finally, we identify a class of probabilistic loops for which the strongest polynomial moment invariant is computable and provide an algorithm for it. Julian Müllner, Marcel Moosbrugger, Laura Kovács |
Proc. ACM Program. Lang. | 1 |
| 2023 | Automated Sensitivity Analysis for Probabilistic Loops
Marcel Moosbrugger, Julian Müllner, Laura Kovács |
iFM | 2 |