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A fundamental algorithmic problem at the heart of static analysis is Dyck reachability. The input is a graph where the edges are labeled with different types of opening and closing parentheses, and the reachability information is computed…

Programming Languages · Computer Science 2019-10-02 Krishnendu Chatterjee , Bhavya Choudhary , Andreas Pavlogiannis

We give an algorithm that takes as input an $n$-vertex graph $G$ and an integer $k$, runs in time $2^{O(k^2)} n^{O(1)}$, and outputs a tree decomposition of $G$ of width at most $k$, if such a decomposition exists. This resolves the…

Data Structures and Algorithms · Computer Science 2023-08-21 Tuukka Korhonen , Daniel Lokshtanov

Kernelization studies polynomial-time preprocessing algorithms. Over the last 20 years, the most celebrated positive results of the field have been linear kernels for classical NP-hard graph problems on sparse graph classes. In this paper,…

Data Structures and Algorithms · Computer Science 2025-11-06 Christian Bertram , Deborah Haun , Mads Vestergaard Jensen , Tuukka Korhonen

We present a deterministic distributed algorithm that computes a $(2\Delta-1)$-edge-coloring, or even list-edge-coloring, in any $n$-node graph with maximum degree $\Delta$, in $O(\log^7 \Delta \log n)$ rounds. This answers one of the…

Data Structures and Algorithms · Computer Science 2017-04-11 Manuela Fischer , Mohsen Ghaffari , Fabian Kuhn

In the Min $k$-Cut problem, input is an edge weighted graph $G$ and an integer $k$, and the task is to partition the vertex set into $k$ non-empty sets, such that the total weight of the edges with endpoints in different parts is minimized.…

Data Structures and Algorithms · Computer Science 2020-09-15 Daniel Lokshtanov , Saket Saurabh , Vaishali Surianarayanan

The Path Contraction and Cycle Contraction problems take as input an undirected graph $G$ with $n$ vertices, $m$ edges and an integer $k$ and determine whether one can obtain a path or a cycle, respectively, by performing at most $k$ edge…

Data Structures and Algorithms · Computer Science 2024-03-12 R. Krithika , V. K. Kutty Malu , Prafullkumar Tale

Low Diameter Decompositions (LDDs) are invaluable tools in the design of combinatorial graph algorithms. While historically they have been applied mainly to undirected graphs, in the recent breakthrough for the negative-length Single Source…

Data Structures and Algorithms · Computer Science 2025-02-11 Karl Bringmann , Nick Fischer , Bernhard Haeupler , Rustam Latypov

We give the first almost-linear time algorithm for computing the \emph{maximal $k$-edge-connected subgraphs} of an undirected unweighted graph for any constant $k$. More specifically, given an $n$-vertex $m$-edge graph $G=(V,E)$ and a…

Data Structures and Algorithms · Computer Science 2023-07-04 Thatchaphol Saranurak , Wuwei Yuan

We consider the following online optimization problem. We are given a graph $G$ and each vertex of the graph is assigned to one of $\ell$ servers, where servers have capacity $k$ and we assume that the graph has $\ell \cdot k$ vertices.…

Data Structures and Algorithms · Computer Science 2020-11-03 Monika Henzinger , Stefan Neumann , Harald Räcke , Stefan Schmid

Diameter -- the task of computing the length of a longest shortest path -- is a fundamental graph problem. Assuming the Strong Exponential Time Hypothesis, there is no $O(n^{1.99})$-time algorithm even in sparse graphs [Roditty and…

Data Structures and Algorithms · Computer Science 2020-12-22 Matthias Bentert , André Nichterlein

In the $k$-cut problem, we are given an edge-weighted graph $G$ and an integer $k$, and have to remove a set of edges with minimum total weight so that $G$ has at least $k$ connected components. The current best algorithms are an…

Data Structures and Algorithms · Computer Science 2019-03-22 Anupam Gupta , Euiwoong Lee , Jason Li

We study deterministic algorithms for computing graph cuts, with focus on two fundamental problems: balanced sparse cut and $k$-vertex connectivity for small $k$ ($k=O(\polylog n)$). Both problems can be solved in near-linear time with…

Data Structures and Algorithms · Computer Science 2019-10-21 Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

We propose a new (theoretical) computational model for the study of massive data processing with limited computational resources. Our model measures the complexity of reading the very large data sets in terms of the data size N and analyzes…

Data Structures and Algorithms · Computer Science 2020-03-09 Jianer Chen , Ying Guo , Qin Huang

We study the design of robust subexponential algorithms for classical connectivity problems on intersection graphs of similarly sized fat objects in $\mathbb{R}^d$. In this setting, each vertex corresponds to a geometric object, and two…

Data Structures and Algorithms · Computer Science 2025-12-04 Malory Marin , Jean-Florent Raymond , Rémi Watrigant

We revisit Approximate Graph Propagation (AGP), a unified framework which captures various graph propagation tasks, such as PageRank, feature propagation in Graph Neural Networks (GNNs), and graph-based Retrieval-Augmented Generation (RAG).…

Data Structures and Algorithms · Computer Science 2026-01-13 Zhuowei Zhao , Zhuo Zhang , Hanzhi Wang , Junhao Gan , Zhifeng Bao , Jianzhong Qi

In this paper we provide a $\tilde{O}(m\sqrt{n})$ time algorithm that computes a $3$-multiplicative approximation of the girth of a $n$-node $m$-edge directed graph with non-negative edge lengths. This is the first algorithm which…

Data Structures and Algorithms · Computer Science 2020-04-15 Shiri Chechik , Yang P. Liu , Omer Rotem , Aaron Sidford

Over the past decade, there has been increasing interest in distributed/parallel algorithms for processing large-scale graphs. By now, we have quite fast algorithms -- usually sublogarithmic-time and often $poly(\log\log n)$-time, or even…

Data Structures and Algorithms · Computer Science 2021-06-30 Amartya Shankha Biswas , Michal Dory , Mohsen Ghaffari , Slobodan Mitrović , Yasamin Nazari

The radius and diameter are fundamental graph parameters. They are defined as the minimum and maximum of the eccentricities in a graph, respectively, where the eccentricity of a vertex is the largest distance from the vertex to another…

Data Structures and Algorithms · Computer Science 2015-06-08 Amir Abboud , Virginia Vassilevska Williams , Joshua Wang

The study of parameterized streaming complexity on graph problems was initiated by Fafianie et al. (MFCS'14) and Chitnis et al. (SODA'15 and SODA'16). Simply put, the main goal is to design streaming algorithms for parameterized problems…

Computational Complexity · Computer Science 2019-10-03 Arijit Bishnu , Arijit Ghosh , Sudeshna Kolay , Gopinath Mishra , Saket Saurabh

The dynamic shortest paths problem on planar graphs asks us to preprocess a planar graph $G$ such that we may support insertions and deletions of edges in $G$ as well as distance queries between any two nodes $u,v$ subject to the constraint…

Data Structures and Algorithms · Computer Science 2016-05-13 Amir Abboud , Søren Dahlgaard
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