VLDB 2026 Research / 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
| 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 |