The visibility graph of a set S ⊆ ℝ² is the graph whose vertices are the points of S, with two points x,y connected by an edge if and only if they see each other in S, that is, if the segment xy is contained in S. The edge density of this graph is known as the Beer index of S. Previously, it has been shown that a simply connected set S ⊆ ℝ² of unit Lebesgue measure with Beer index β > 0 contains a convex subset of measure Ω(β); in particular, for visibility graphs of simply connected sets, a positive edge density β > 0 implies the existence of a clique containing an Ω(β)-fraction of all vertices. The simple-connectivity assumption cannot be omitted, as there are non-simply-connected sets with Beer index 1 and no convex subset of positive measure. Nevertheless, in this paper, we extend the above result to non-simply-connected sets, by showing that a visibility graph with large edge density contains a triangle with large convex hull. More precisely, we show that a set S ⊆ ℝ² of unit Lebesgue measure with Beer index β > 0 contains three pairwise visible points whose convex hull has measure Ω(β⁹). If in addition S is an open domain with K holes, then S contains three pairwise visible points with convex hull of measure Ω(β/K) as well as a convex subset of measure Ω(β/K²).

We introduce a new complexity measure for cocomparability graphs of posets or in other words, intersection graphs of piecewise linear functions, the bend number. We prove that cocomparability graphs of bounded bend number are not too plentiful and give two hierarchies of classes of cocomparability graphs, depending on whether the piecewise linear functions are restricted to slopes of ±1 (diagonal case) or not (general case). These hierarchies give a gradation between permutation graphs and cocomparability graphs.

We consider the following general model of a sorting procedure: we fix a hereditary permutation class C, which corresponds to the operations that the procedure is allowed to perform in a single step. The input of sorting is a permutation π of the set [n] = {1, 2,…,n}, i.e., a sequence where each element of [n] appears once. In every step, the sorting procedure picks a permutation σ of length n from C, and rearranges the current permutation of numbers by composing it with σ. The goal is to transform the input π into the sorted sequence 1, 2,…,n in as few steps as possible.

We study the counting problem known as #PPM, whose input is a pair of permutations $π$ and $τ$ (called pattern and text, respectively), and the task is to find the number of subsequences of $τ$ that have the same relative order as $π$. A simple brute-force approach solves #PPM for a pattern of length $k$ and a text of length $n$ in time $O(n^{k+1})$, while Berendsohn, Kozma and Marx have recently shown that under the exponential time hypothesis (ETH), it cannot be solved in time $f(k) n^{o(k/\log k)}$ for any function $f$. In this paper, we consider the restriction of #PPM, known as $\mathcal{C}$-Pattern #PPM, where the pattern $π$ must belong to a hereditary permutation class $\mathcal{C}$. Our goal is to identify the structural properties of $\mathcal{C}$ that determine the complexity of $\mathcal{C}$-Pattern #PPM. We focus on two such structural properties, known as the long path property (LPP) and the deep tree property (DTP). Assuming ETH, we obtain these results: 1. If $C$ has the LPP, then $\mathcal{C}$-Pattern #PPM cannot be solved in time $f(k)n^{o(\sqrt{k})}$ for any function $f$, and 2. if $C$ has the DTP, then $\mathcal{C}$-Pattern #PPM cannot be solved in time $f(k)n^{o(k/\log^2 k)}$ for any function $f$. Furthermore, when $\mathcal{C}$ is one of the so-called monotone grid classes, we show that if $\mathcal{C}$ has the LPP but not the DTP, then $\mathcal{C}$-Pattern #PPM can be solved in time $f(k)n^{O(\sqrt k)}$. In particular, the lower bounds above are tight up to the polylog terms in the exponents.

We study the complexity of the decision problem known as Permutation Pattern Matching, or PPM. The input of PPM consists of a pair of permutations τ (the "text") and π (the "pattern"), and the goal is to decide whether τ contains π as a subpermutation. On general inputs, PPM is known to be NP-complete by a result of Bose, Buss and Lubiw. In this paper, we focus on restricted instances of PPM where the text is assumed to avoid a fixed (small) pattern σ; this restriction is known as Av(σ)-PPM. It has been previously shown that Av(σ)-PPM is polynomial for any σ of size at most 3, while it is NP-hard for any σ containing a monotone subsequence of length four. In this paper, we present a new hardness reduction which allows us to show, in a uniform way, that Av(σ)-PPM is hard for every σ of size at least 6, for every σ of size 5 except the symmetry class of 41352, as well as for every σ symmetric to one of the three permutations 4321, 4312 and 4231. Moreover, assuming the exponential time hypothesis, none of these hard cases of Av(σ)-PPM can be solved in time 2^o(n/log n). Previously, such conditional lower bound was not known even for the unconstrained PPM problem. On the tractability side, we combine the CSP approach of Guillemot and Marx with the structural results of Huczynska and Vatter to show that for any monotone-griddable permutation class 𝒞, PPM is polynomial when the text is restricted to a permutation from 𝒞.

Abstract The 3-coloring of hereditary graph classes has been a deeply-researched problem in the last decade. A hereditary graph class is characterized by a (possibly infinite) list of minimal forbidden induced subgraphs $$H_1,H_2,\ldots $$ H 1 , H 2 , … ; the graphs in the class are called $$(H_1,H_2,\ldots )$$ ( H 1 , H 2 , … ) -free. The complexity of 3-coloring is far from being understood, even for classes defined by a few small forbidden induced subgraphs. For H-free graphs, the complexity is settled for any H on up to seven vertices. There are only two unsolved cases on eight vertices, namely $$2P_4$$ 2 P 4 and $$P_8$$ P 8 . For $$P_8$$ P 8 -free graphs, some partial results are known, but to the best of our knowledge, $$2P_4$$ 2 P 4 -free graphs have not been explored yet. In this paper, we show that the 3-coloring problem is polynomial-time solvable on $$(2P_4,C_5)$$ ( 2 P 4 , C 5 ) -free graphs.

Permutation Pattern Matching (PPM) is the problem of deciding for a given pair of permutations P and T whether the pattern P is contained in the text T. Bose, Buss and Lubiw showed that PPM is NP-complete. In view of this result, it is natural to ask how the situation changes when we restrict the pattern P to a fixed permutation class C; this is known as the C-Pattern PPM problem. Grid classes are special kind of permutation classes, consisting of permutations admitting a grid-like decomposition into simpler building blocks. Of particular interest are the so-called monotone grid classes, in which each building block is a monotone sequence. Recently, it has been discovered that grid classes, especially the monotone ones, play a fundamental role in the understanding of the structure of general permutation classes. This motivates us to study the hardness of C-Pattern PPM for a (monotone) grid class C. We provide a complexity dichotomy for C-Pattern PPM when C is taken to be a monotone grid class. Specifically, we show that the problem is polynomial-time solvable if a certain graph associated with C, called the cell graph, is a forest, and it is NP-complete otherwise. We further generalize our results to grid classes whose blocks belong to classes of bounded grid-width. We show that the C-Pattern PPM for such a grid class C is polynomial-time solvable if the cell graph of C avoids a cycle or a certain special type of path, and it is NP-complete otherwise.

A permutation pi is a merge of a permutation sigma and a permutation tau, if we can color the elements of pi red and blue so that the red elements have the same relative order as sigma and the blue ones as tau. We consider, for fixed hereditary permutation classes C and D, the complexity of determining whether a given permutation pi is a merge of an element of C with an element of D. We develop general algorithmic approaches for identifying polynomially tractable cases of merge recognition. Our tools include a version of nondeterministic logspace streaming recognizability of permutations, which we introduce, and a concept of bounded width decomposition, inspired by the work of Ahal and Rabinovich. As a consequence of the general results, we can provide nontrivial examples of tractable permutation merges involving commonly studied permutation classes, such as the class of layered permutations, the class of separable permutations, or the class of permutations avoiding a decreasing sequence of a given length. On the negative side, we obtain a general hardness result which implies, for example, that it is NP-complete to recognize the permutations that can be merged from two subpermutations avoiding the pattern 2413.

Permutation Pattern Matching (or PPM) is a decision problem whose input is a pair of permutations π and τ, represented as sequences of integers, and the task is to determine whether τ contains a subsequence order-isomorphic to π. Bose, Buss and Lubiw proved that PPM is NP-complete on general inputs. We show that PPM is NP-complete even when π has no decreasing subsequence of length 3 and τ has no decreasing subsequence of length 4. This provides the first known example of PPM being hard when one or both of π and σ are restricted to a proper hereditary class of permutations. This hardness result is tight in the sense that PPM is known to be polynomial when both π and τ avoid a decreasing subsequence of length 3, as well as when π avoids a decreasing subsequence of length 2. The result is also tight in another sense: we will show that for any hereditary proper subclass c of the class of permutations avoiding a decreasing sequence of length 3, there is a polynomial algorithm solving PPM instances where π is from c and τ is arbitrary. We also obtain analogous hardness and tractability results for the class of so-called skew-merged patterns. From these results, we deduce a complexity dichotomy for the PPM problem restricted to π belonging to Av(α), where Av(α) denotes the class of permutations avoiding a permutation α. Specifically, we show that the problem is polynomial when α is in the set {1,12, 21,132, 213, 231, 312}, and it is NP-complete for any other α.

Let S be a subset of $$\mathbb {R}^d$$ with finite positive Lebesgue measure. The Beer index of convexity $${\text {b}}(S)$$ of S is the probability that two points of S chosen uniformly independently at random see each other in S. The convexity ratio $${\text {c}}(S)$$ of S is the Lebesgue measure of the largest convex subset of S divided by the Lebesgue measure of S. We investigate the relationship between these two natural measures of convexity. We show that every set $$S\subseteq \mathbb {R}^2$$ with simply connected components satisfies $${\text {b}}(S)\leqslant \alpha {\text {c}}(S)$$ for an absolute constant $$\alpha $$ , provided $${\text {b}}(S)$$ is defined. This implies an affirmative answer to the conjecture of Cabello et al. that this estimate holds for simple polygons. We also consider higher-order generalizations of $${\text {b}}(S)$$ . For $$1\leqslant k\leqslant d$$ , the k-index of convexity $${\text {b}}_k(S)$$ of a set $$S\subseteq \mathbb {R}^d$$ is the probability that the convex hull of a $$(k+1)$$ -tuple of points chosen uniformly independently at random from S is contained in S. We show that for every $$d\geqslant 2$$ there is a constant $$\beta (d)>0$$ such that every set $$S\subseteq \mathbb {R}^d$$ satisfies $${\text {b}}_d(S)\leqslant \beta {\text {c}}(S)$$ , provided $${\text {b}}_d(S)$$ exists. We provide an almost matching lower bound by showing that there is a constant $$\gamma (d)>0$$ such that for every $$\varepsilon \in (0,1)$$ there is a set $$S\subseteq \mathbb {R}^d$$ of Lebesgue measure 1 satisfying $${\text {c}}(S)\leqslant \varepsilon $$ and $${\text {b}}_d(S)\geqslant \gamma \frac{\varepsilon }{\log _2{1/\varepsilon }}\geqslant \gamma \frac{{\text {c}}(S)}{\log _2{1/{\text {c}}(S)}}$$ .

Let S be a subset of R^d with finite positive Lebesgue measure. The Beer index of convexity b(S) of S is the probability that two points of S chosen uniformly independently at random see each other in S. The convexity ratio c(S) of S is the Lebesgue measure of the largest convex subset of S divided by the Lebesgue measure of S. We investigate a relationship between these two natural measures of convexity of S. We show that every subset S of the plane with simply connected components satisfies b(S) <= alpha c(S) for an absolute constant alpha, provided b(S) is defined. This implies an affirmative answer to the conjecture of Cabello et al. asserting that this estimate holds for simple polygons. We also consider higher-order generalizations of b(S). For 1 <= k <= d, the k-index of convexity b_k(S) of a subset S of R^d is the probability that the convex hull of a (k+1)-tuple of points chosen uniformly independently at random from S is contained in S. We show that for every d >= 2 there is a constant beta(d) > 0 such that every subset S of R^d satisfies b_d(S) <= beta c(S), provided b_d(S) exists. We provide an almost matching lower bound by showing that there is a constant gamma(d) > 0 such that for every epsilon from (0,1] there is a subset S of R^d of Lebesgue measure one satisfying c(S) <= epsilon and b_d(S) >= (gamma epsilon)/log_2(1/epsilon) >= (gamma c(S))/log_2(1/c(S)).

We study the following problem: given a planar graph G and a planar drawing (embedding) of a subgraph of G , can such a drawing be extended to a planar drawing of the entire graph G ? This problem fits the paradigm of extending a partial solution for a problem to a complete one, which has been studied before in many different settings. Unlike many cases, in which the presence of a partial solution in the input makes an otherwise easy problem hard, we show that the planarity question remains polynomial-time solvable. Our algorithm is based on several combinatorial lemmas, which show that the planarity of partially embedded graphs exhibits the ‘TONCAS’ behavior “the obvious necessary conditions for planarity are also sufficient.” These conditions are expressed in terms of the interplay between (1) the rotation system and containment relationships between cycles and (2) the decomposition of a graph into its connected, biconnected, and triconnected components. This implies that no dynamic programming is needed for a decision algorithm and that the elements of the decomposition can be processed independently. Further, by equipping the components of the decomposition with suitable data structures and by carefully splitting the problem into simpler subproblems, we make our algorithm run in linear time. Finally, we consider several generalizations of the problem, such as minimizing the number of edges of the partial embedding that need to be rerouted to extend it, and argue that they are NP-hard. We also apply our algorithm to the simultaneous graph drawing problem Simultaneous Embedding with Fixed Edges (Sefe) . There we obtain a linear-time algorithm for the case that one of the input graphs or the common graph has a fixed planar embedding.

A partially embedded graph (or PEG) is a triple (G,H,EH), where G is a graph, H is a subgraph of G, and EH is a planar embedding of H. We say that a PEG (G,H,EH) is planar if the graph G has a planar embedding that extends the embedding EH.

We study the following problem: Given a planar graph G and a planar drawing (embedding) of a subgraph of G, can such a drawing be extended to a planar drawing of the entire graph G? This problem fits the paradigm of extending a partial solution to a complete one, which has been studied before in many different settings. Unlike many cases, in which the presence of a partial solution in the input makes hard an otherwise easy problem, we show that the planarity question remains polynomial-time solvable. Our algorithm is based on several combinatorial lemmata which show that the planarity of partially embedded graphs meets the “on-cas” behaviour – obvious necessary conditions for planarity are also sufficient. These conditions are expressed in terms of the interplay between (a) rotation schemes and containment relationships between cycles and (b) the decomposition of a graph into its connected, biconnected, and triconnected components. This implies that no dynamic programming is needed for a decision algorithm and that the elements of the decomposition can be processed independently. Further, by equipping the components of the decomposition with suitable data structures and by carefully splitting the problem into simpler subproblems, we improve our algorithm to reach linear-time complexity. Finally, we consider several generalizations of the problem, e.g. minimizing the number of edges of the partial embedding that need to be rerouted to extend it, and argue that they are NP-hard. Also, we show how our algorithm can be applied to solve related Graph Drawing problems.

Motivated by $L(p,q)$-labelings of graphs, we introduce a notion of $\lambda$-graphs: a $\lambda$-graph G is a graph with two types of edges: 1-edges and x-edges. For a parameter $x\in[0,1]$, a proper labeling of G is a labeling of vertices of G by nonnegative reals such that the labels of the endvertices of a 1-edge differ by at least 1 and the labels of the endvertices of an x-edge differ by at least x; $\lambda_G(x)$ is the smallest real such that G has a proper labeling by labels from the interval $[0,\lambda_G(x)]$. We study properties of the function $\lambda_G(x)$ for finite and infinite $\lambda$-graphs and establish the following results: if the function $\lambda_G(x)$ is well defined, then it is a piecewise linear function of x with finitely many linear parts. Surprisingly, the set $\Lambda(\alpha,\beta)$ of all functions $\lambda_G$ with $\lambda_G(0)=\alpha$ and $\lambda_G(1)=\beta$ is finite for any $\alpha\le\beta$. We also prove a tight upper bound on the number of segments for finite $\lambda$-graphs G with convex functions $\lambda_G(x)$.