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Dagstuhl Reports, Volume 14, Issue 10
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Dagstuhl Reports, Volume 14
Journal: Dagstuhl Reports (DagRep)
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Dagstuhl Seminars 24411, 24421, 24431, 24432, 24441Publication Details
- published at: 2025-04-23
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
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Complete Issue
Dagstuhl Reports, Volume 14, Issue 10, October 2024, Complete Issue
Abstract
Dagstuhl Reports, Volume 14, Issue 10, October 2024, Complete Issue
Cite as
Dagstuhl Reports, Volume 14, Issue 10, pp. 1-102, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{DagRep.14.10,
title = {{Dagstuhl Reports, Volume 14, Issue 10, October 2024, Complete Issue}},
pages = {1--102},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10},
URN = {urn:nbn:de:0030-drops-230266},
doi = {10.4230/DagRep.14.10},
annote = {Keywords: Dagstuhl Reports, Volume 14, Issue 10, October 2024, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 14, Issue 10, 2024
Abstract
Dagstuhl Reports, Table of Contents, Volume 14, Issue 10, 2024
Cite as
Dagstuhl Reports, Volume 14, Issue 10, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{DagRep.14.10.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 14, Issue 10, 2024}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.i},
URN = {urn:nbn:de:0030-drops-230208},
doi = {10.4230/DagRep.14.10.i},
annote = {Keywords: Table of Contents, Frontmatter}
}
Document
New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411)
Abstract
The Dagstuhl Seminar concentrated on the development of new tools arising from the parameterized complexity of cuts, paths, and decompositions in graphs. The last 2 years were very exciting for the area, with a number of breakthroughs.
In FOCS 2021, Korhonen introduced a new method for approximating tree decompositions in graphs. His method, which was deeply rooted in classical graph theory, appeared to be a very handy tool for decomposing graphs, and several STOC/FOCS papers developed this method in various settings. In parallel, a novel perspective on graph decompositions was proposed by Bonnet et al. in FOCS 2020. The new theory of twin-width had many exciting consequences, and we were still at the beginning of understanding the real impact of the new decompositions on graph algorithms.
In a series of papers (SODA 2021, STOC 2022, SODA 2023), Kim et al. developed beautiful algorithmic methods for handling separators in (undirected, weighted, or directed) graphs by the addition of arcs. The new algorithmic tool was used to resolve a number of long-standing open problems in the area, and it also seemed to pave the road to many more new discoveries.
Reis and Rothvoss (Arxiv 2023) announced a ((log n)^{O(n)}) time randomized algorithm to solve integer programs in n variables. This breakthrough had an impact on many problems in parameterized complexity, especially on problems concerning cuts in graphs. Finally, by employing algebraic methods (both new and old), significant progress was made on several problems related to paths, including the classical (k)-disjoint path problems.
This seminar brought together people from the parameterized complexity community, specialists in cuts, flows, and connectivity, and those who had been at the forefront of these new developments. In doing so, it consolidated the results achieved in recent years, discussed future research directions, and further explored the potential applications of the methods and techniques described above.
Cite as
Fedor V. Fomin, Dániel Marx, Saket Saurabh, Roohani Sharma, and Madhumita Kundu. New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411). In Dagstuhl Reports, Volume 14, Issue 10, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{fomin_et_al:DagRep.14.10.1,
author = {Fomin, Fedor V. and Marx, D\'{a}niel and Saurabh, Saket and Sharma, Roohani and Kundu, Madhumita},
title = {{New Tools in Parameterized Complexity: Paths, Cuts, and Decomposition (Dagstuhl Seminar 24411)}},
pages = {1--21},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
editor = {Fomin, Fedor V. and Marx, D\'{a}niel and Saurabh, Saket and Sharma, Roohani and Kundu, Madhumita},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.1},
URN = {urn:nbn:de:0030-drops-230258},
doi = {10.4230/DagRep.14.10.1},
annote = {Keywords: fixed-parameter tractability, intractability, parameterized complexity}
}
Document
SAT and Interactions (Dagstuhl Seminar 24421)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar "SAT and Interactions" (24421). The seminar brought together theoreticians and practitioners from the areas of proof complexity, SAT and QBF solving, and first-order theorem proving, who discussed recent developments in their fields and embarked on an interdisciplinary exchange of ideas and techniques between these neighbouring subfields of SAT.
Cite as
Olaf Beyersdorff, Laura Kovács, Meena Mahajan, Martina Seidl, and Kaspar Kasche. SAT and Interactions (Dagstuhl Seminar 24421). In Dagstuhl Reports, Volume 14, Issue 10, pp. 22-38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{beyersdorff_et_al:DagRep.14.10.22,
author = {Beyersdorff, Olaf and Kov\'{a}cs, Laura and Mahajan, Meena and Seidl, Martina and Kasche, Kaspar},
title = {{SAT and Interactions (Dagstuhl Seminar 24421)}},
pages = {22--38},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
editor = {Beyersdorff, Olaf and Kov\'{a}cs, Laura and Mahajan, Meena and Seidl, Martina and Kasche, Kaspar},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.22},
URN = {urn:nbn:de:0030-drops-230243},
doi = {10.4230/DagRep.14.10.22},
annote = {Keywords: SAT, QBF, proof complexity, solving, first-order logic, automated theorem proving}
}
Document
Automated Programming and Program Repair (Dagstuhl Seminar 24431)
Abstract
The Dagstuhl Seminar 24431 on "Automated Programming and Program Repair" brought together 33 researchers from academia and industry to explore the intersection of automated code generation and program repair. Over five days (October 21–25, 2024), participants discussed advances in large language models (LLMs) for code generation, the role of automated program repair in improving generated code, and challenges in deploying these technologies in real-world software development. The seminar featured over 20 talks and three panel discussions on topics such as benchmarks for LLM-generated code, trust in automated programming, and the broader applications of LLMs beyond coding assistance. Key outcomes included identifying critical challenges in benchmarking, evaluation criteria, and developer adoption of automated repair techniques, fostering future collaborations and actionable research directions in the field.
Cite as
Claire Le Goues, Michael Pradel, Abhik Roychoudhury, and Shin Hwei Tan. Automated Programming and Program Repair (Dagstuhl Seminar 24431). In Dagstuhl Reports, Volume 14, Issue 10, pp. 39-57, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{legoues_et_al:DagRep.14.10.39,
author = {Le Goues, Claire and Pradel, Michael and Roychoudhury, Abhik and Tan, Shin Hwei},
title = {{Automated Programming and Program Repair (Dagstuhl Seminar 24431)}},
pages = {39--57},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
editor = {Le Goues, Claire and Pradel, Michael and Roychoudhury, Abhik and Tan, Shin Hwei},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.39},
URN = {urn:nbn:de:0030-drops-230235},
doi = {10.4230/DagRep.14.10.39},
annote = {Keywords: Auto-coding, Large Language Models, Automated Program Repair, Program Synthesis, Trustworthy Software}
}
Document
Behavioural Metrics and Quantitative Logics (Dagstuhl Seminar 24432)
Abstract
This report documents the program and the outcome of Dagstuhl Seminar "Behavioural Metrics and Quantitative Logics" (24432).
Behavioural metrics and quantitative logics specify quantitative aspects of systems. A metric measures how far apart two systems are in their behaviour while a quantititative logic evaluates the degree to which a state satisfies a formula. They are often intimately connected via a Hennessy-Milner theorem stating that the distance induced by a quantitative logic coincides with behavioural distance. There are various applications in model-checking, differential privacy, hybrid systems and learning. Several challenges in this area have been identified: studying suitable metrics and their corresponding logics, generalizing to the setting of coalgebras by parameterizing the branching type of the system under consideration, developing methods of quantitative algebraic reasoning, finding efficient methods for computing behavioural methods. This Dagstuhl Seminar provided a forum to researchers working in this area, to discuss the state-of-the-art and further developments, and in particular address applications in various domains.
Cite as
Barbara König, Radu Mardare, Prakash Panangaden, Jurriaan Rot, and Florence Clerc. Behavioural Metrics and Quantitative Logics (Dagstuhl Seminar 24432). In Dagstuhl Reports, Volume 14, Issue 10, pp. 58-75, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{konig_et_al:DagRep.14.10.58,
author = {K\"{o}nig, Barbara and Mardare, Radu and Panangaden, Prakash and Rot, Jurriaan and Clerc, Florence},
title = {{Behavioural Metrics and Quantitative Logics (Dagstuhl Seminar 24432)}},
pages = {58--75},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
editor = {K\"{o}nig, Barbara and Mardare, Radu and Panangaden, Prakash and Rot, Jurriaan and Clerc, Florence},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.58},
URN = {urn:nbn:de:0030-drops-230222},
doi = {10.4230/DagRep.14.10.58},
annote = {Keywords: Behavioural metrics, quantitative equational reasoning, quantitative logics}
}
Document
Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441)
Abstract
Combinatorial optimization problems are pervasive across critical domains, including business analytics, engineering, supply chain management, transportation, and bioinformatics. Many of these problems are NP-hard, posing significant challenges for even moderately sized instances. Moreover, even when polynomial-time algorithms exist, their practical implementation can be computationally expensive for real-world applications.
This has driven decades of research across diverse fields, encompassing exact and approximation algorithms, parameterized algorithms, algorithm engineering, operations research, optimization solvers (such as mixed-integer linear programming and constraint programming solvers), and nature-inspired metaheuristics.
Recently, there has been a surge in research exploring the synergistic integration of machine learning techniques with algorithmic insights and optimization solvers to enhance the scalability of solving combinatorial optimization problems. However, research efforts in this area are currently fragmented across several distinct communities, including those focused on "Learning to scale optimization solvers," "Algorithm Engineering," "Algorithms with predictions," and "Decision-focused learning."
This seminar brought together researchers from these diverse communities, fostering a dialogue on effectively combining algorithm engineering techniques, optimization solvers, and machine learning to address these challenging problems. The seminar facilitated the development of a shared vocabulary, clarifying similarities and distinctions between concepts across different research areas. Furthermore, significant progress was made in identifying key research directions for the future advancement of this field. We anticipate that these outcomes will serve as a valuable roadmap for advancing this exciting research area.
Cite as
Deepak Ajwani, Bistra Dilkina, Tias Guns, and Ulrich Carsten Meyer. Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441). In Dagstuhl Reports, Volume 14, Issue 10, pp. 76-100, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Article{ajwani_et_al:DagRep.14.10.76,
author = {Ajwani, Deepak and Dilkina, Bistra and Guns, Tias and Meyer, Ulrich Carsten},
title = {{Machine Learning Augmented Algorithms for Combinatorial Optimization Problems (Dagstuhl Seminar 24441)}},
pages = {76--100},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {14},
number = {10},
editor = {Ajwani, Deepak and Dilkina, Bistra and Guns, Tias and Meyer, Ulrich Carsten},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.10.76},
URN = {urn:nbn:de:0030-drops-230216},
doi = {10.4230/DagRep.14.10.76},
annote = {Keywords: Algorithm Engineering, Combinatorial Optimization, Constraint Solvers, Machine Learning}
}