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Florian Lonsing

Researcher at Vienna University of Technology

Publications -  54
Citations -  1374

Florian Lonsing is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: True quantified Boolean formula & Solver. The author has an hindex of 21, co-authored 53 publications receiving 1250 citations. Previous affiliations of Florian Lonsing include Stanford University & Johannes Kepler University of Linz.

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Journal ArticleDOI

DepQBF: A Dependency-Aware QBF Solver

TL;DR: In this article, a new search-based solver for quantified boolean formulae (QBF) is presented, which integrates compact dependency graphs to overcome the restrictions imposed by linear quantifier prefixes of QBFs in prenex conjunctive normal form.
Book ChapterDOI

Blocked clause elimination for QBF

TL;DR: Novel preprocessing methods for QBF based on blocked clause elimination (BCE), a technique successfully applied in SAT, are presented and it is shown that preprocessing with QBCE reduces formulas substantially and allows to solve considerable more instances than the previous state-of-the-art.
Book ChapterDOI

Automated testing and debugging of SAT and QBF solvers

TL;DR: This work develops automated testing and debugging techniques designed and optimized for SAT and QBF solver development that are able to find critical solver defects that lead to crashes, invalid satisfying assignments and incorrect satisfiability results.
Journal ArticleDOI

Clause elimination for SAT and QSAT

TL;DR: It turns out that the importance of applying the clause elimination procedures developed in this work is empirically emphasized in the context of state-of-the-art QSAT solving.
Book ChapterDOI

Long-Distance Resolution: Proof Generation and Strategy Extraction in Search-Based QBF Solving

TL;DR: This work considers search-based QBF solvers which are able to learn tautological clauses based on resolution and the conflict-driven clause learning method and proves that the resolution proofs produced by these solvers correspond to proofs in the LDQ calculus and can therefore be used as input for strategy extraction algorithms.