Julian Müllner

dblp:348/5288 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Program verification
invariant generation
0.812024
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
0.812024
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
0.812024
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
YearPublicationVenuePosition
2024 Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs
abstract
We 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
iFM2