activity
20162023
most citedThe Hierarchy of Hyperlogics

38 citations · 79 across the 20 of their papers we have counts for

collaborators

23 papers

cs.AI2023

Lightweight Online Learning for Sets of Related Problems in Automated Reasoning

Haoze Wu, Christopher Hahn, Florian Lonsing +3

We present Self-Driven Strategy Learning (), a lightweight online learning methodology for automated reasoning tasks that involve solving a set of related problems.…

cs.LO2023★ 6 cited

nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models

Matthias Cosler, Christopher Hahn, Daniel Mendoza +2

A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as wri…

cs.LG2023★ 1 cited

Iterative Circuit Repair Against Formal Specifications

Matthias Cosler, Frederik Schmitt, Christopher Hahn +1

We present a deep learning approach for repairing sequential circuits against formal specifications given in linear-time temporal logic (LTL). Given a defective circuit and its for…

cs.DC2023★ 1 cited

Fast Convergence of -Opinion Undecided State Dynamics in the Population Protocol Model

Talley Amir, James Aspnes, Petra Berenbrink +4

We analyze the convergence of the -opinion Undecided State Dynamics (USD) in the population protocol model. For =2 opinions it is well known that the USD reaches consensus wi…

cs.LO2022★ 1 cited

Explaining Hyperproperty Violations

Norine Coenen, Raimund Dachselt, Bernd Finkbeiner +5

Hyperproperties relate multiple computation traces to each other. Model checkers for hyperproperties thus return, in case a system model violates the specification, a set of traces…

cs.SE2022★ 13 cited

Formal Specifications from Natural Language

Christopher Hahn, Frederik Schmitt, Julia J. Tillman +3

We study the generalization abilities of language models when translating natural language into formal specifications with complex semantics. In particular, we fine-tune language m…