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The run-length compressed Burrows-Wheeler transform (RLBWT) used in conjunction with the backward search introduced in the FM index is the centerpiece of most compressed indexes working on highly-repetitive data sets like biological sequences. Compared to grammar indexes, the size of the RLBWT is often much bigger, but queries like counting the occurrences of long patterns can be done much faster than on any existing grammar index so far. In this paper, we combine the virtues of a grammar with the RLBWT by building the RLBWT on top of a special grammar based on induced suffix sorting. Our experiments reveal that our hybrid approach outperforms the classic RLBWT with respect to the index sizes, and with respect to query times on biological data sets for sufficiently long patterns.

This study considers the (soft) capacitated vertex cover problem in a dynamic setting. This problem generalizes the dynamic model of the vertex cover problem, which has been intensively studied in recent years. Given a dynamically changing vertex-weighted graph $G=(V,E)$, which allows edge insertions and edge deletions, the goal is to design a data structure that maintains an approximate minimum vertex cover while satisfying the capacity constraint of each vertex. That is, when picking a copy of a vertex $v$ in the cover, the number of $v$'s incident edges covered by the copy is up to a given capacity of $v$. We extend Bhattacharya et al.'s work [SODA'15 and ICALP'15] to obtain a deterministic primal-dual algorithm for maintaining a constant-factor approximate minimum capacitated vertex cover with $O(\log n / \epsilon)$ amortized update time, where $n$ is the number of vertices in the graph. The algorithm can be extended to (1) a more general model in which each edge is associated with a nonuniform and unsplittable demand, and (2) the more general capacitated set cover problem.

Let G=(V,E) be a connected graph. A set U subseteq V is convex if G[U] is connected and all vertices of V\U have at most one neighbor in U. Let sigma(W) denote the unique smallest convex set that contains W subseteq V. Two players play the following game. Consider a convex set U and call it the `playground.' Initially, U = emptyset. When U=V, the player to move loses the game. Otherwise, that player chooses a vertex x in V\U which is at distance at most two from U. The effect of the move is that the playground U changes into sigma(U cup {x}) and the opponent is presented with this new playground. A graph is chordal bipartite if it is bipartite and has no induced cycle of length more than four. In this paper we show that, when G is chordal bipartite, there is a polynomial-time algorithm that computes the Grundy number of the P_3-game played on G. This implies that there is an efficient algorithm to decide whether the first player has a winning strategy.

A set C of vertices of a graph is P_3-convex if every vertex outside C has at most one neighbor in C. The convex hull \sigma(A) of a set A is the smallest P_3-convex set that contains A. A set M is convexly independent if for every vertex x \in M, x \notin \sigma(M-x). We show that the maximal number of vertices that a convexly independent set in a permutation graph can have, can be computed in polynomial time.

Without further ado, we present the P_3-game. The P_3-game is decidable for elementary classes of graphs such as paths and cycles. From an algorithmic point of view, the connected P_3-game is fascinating. We show that the connected P_3-game is polynomially decidable for classes such as trees, chordal graphs, ladders, cacti, outerplanar graphs and circular arc graphs.

The Grundy number of a graph is the maximal number of colors attained by a first-fit coloring of the graph. The class of Cameron graphs is the Seidel switching class of cographs. In this paper we show that the Grundy number is computable in polynomial time for Cameron graphs.

In a multi-battle contest, each time a player competes by investing some of her budgets or resources in a component battle to collect a value if winning the battle. There are multiple battles to fight, and the budgets get consumed over time. The final winner in the overall contest is the one who first reaches some amount of total value. Examples include R & D races, sports competition, elections, and many more. A player needs to make adequate sequential actions to win the contest against dynamic competition over time from the others. We are interested in how much budgets the players would need and what actions they should take in order to perform well. We model and study such budget-constrained multi-battle contests where each component battle is a first-price or all-pay auction. We focus on analyzing the 2-player budget ratio that guarantees a player's winning (or falling behind in just a bounded amount of collected value) against the other omnipotent player. In the settings considered, we give efficient dynamic programs to find the optimal budget ratios and the corresponding bidding strategies. Our definition of game, budget constraints, and emphasis on budget analyses provide a new perspective and analysis in the related context.

We revisit the exact shortest unique substring (SUS) finding problem, and propose its approximate version where mismatches are allowed, due to its applications in subfields such as computational biology. We design a generic in-place framework that fits to solve both the exact and approximate $k$-mismatch SUS finding, using the minimum $2n$ memory words plus $n$ bytes space, where $n$ is the input string size. By using the in-place framework, we can find the exact and approximate $k$-mismatch SUS for every string position using a total of $O(n)$ and $O(n^2)$ time, respectively, regardless of the value of $k$. Our framework does not involve any compressed or succinct data structures and thus is practical and easy to implement., Comment: 15 pages. A preliminary version of this paper appears in Proceedings of the 26th International Symposium on Algorithms and Computation (ISAAC), Nagoya, Japan, 2015

Solitaire {\sc Flood-it}, or {\sc Honey-Bee}, is a game played on a colored graph. The player resides in a source vertex. Originally his territory is the maximal connected, monochromatic subgraph that contains the source. A move consists of calling a color. This conquers all the nodes of the graph that can be reached by a monochromatic path of that color from the current territory of the player. It is the aim of the player to add all vertices to his territory in a minimal number of moves. We show that the minimal number of moves can be computed in polynomial time when the game is played on AT-free graphs., Comment: 10 pages, 1 figure

We study convexity properties of graphs. In this paper we present a linear-time algorithm for the geodetic number in tree-cographs. Settling a 10-year-old conjecture, we prove that the Steiner number is at least the geodetic number in AT-free graphs. Computing a maximal and proper monophonic set in $\AT$-free graphs is NP-complete. We present polynomial algorithms for the monophonic number in permutation graphs and the geodetic number in $P_4$- sparse graphs., Comment: 20 pages

Let $k \in \mathbb{N}$ and let $G$ be a graph. A function $f: V(G) \rightarrow 2^{[k]}$ is a rainbow function if, for every vertex $x$ with $f(x)=\emptyset$, $f(N(x)) =[k]$. The rainbow domination number $\gamma_{kr}(G)$ is the minimum of $\sum_{x \in V(G)} |f(x)|$ over all rainbow functions. We investigate the rainbow domination problem for some classes of perfect graphs.

A function f: V \rightarrow \{-1,0,1\} is a minus-domination function of a graph G=(V,E) if the values over the vertices in each closed neighborhood sum to a positive number. The weight of f is the sum of f(x) over all vertices x \in V. The minus-domination number \gamma^{-}(G) is the minimum weight over all minus-domination functions. The size of a minus domination is the number of vertices that are assigned 1. In this paper we show that the minus-domination problem is fixed-parameter tractable for d-degenerate graphs when parameterized by the size of the minus-dominating set and by d. The minus-domination problem is polynomial for graphs of bounded rankwidth and for strongly chordal graphs. It is NP-complete for splitgraphs. Unless P=NP there is no fixed-parameter algorithm for minus-domination. 79,1 5%

We show that there are polynomial-time algorithms to compute maximum independent sets in the categorical products of two cographs and two splitgraphs. The ultimate categorical independence ratio of a graph G is defined as lim_{k --> infty} \alpha(G^k)/n^k. The ultimate categorical independence ratio is polynomial for cographs, permutation graphs, interval graphs, graphs of bounded treewidth and splitgraphs. When G is a planar graph of maximal degree three then alpha(G \times K_4) is NP-complete. We present a PTAS for the ultimate categorical independence ratio of planar graphs. We present an O^*(n^{n/3}) exact, exponential algorithm for general graphs. We prove that the ultimate categorical independent domination ratio for complete multipartite graphs is zero, except when the graph is complete bipartite with color classes of equal size (in which case it is 1/2)., Comment: arXiv admin note: substantial text overlap with arXiv:1305.4237

Let G be a graph. The independence-domination number is the maximum over all independent sets I in G of the minimal number of vertices needed to dominate I. In this paper we investigate the computational complexity of independence domination for graphs in several graph classes related to cographs. We present an exact exponential algorithm. We also present a PTAS for planar graphs.

We present several results about position heaps, a relatively new alternative to suffix trees and suffix arrays. First, we show that, if we limit the maximum length of patterns to be sought, then we can also limit the height of the heap and reduce the worst-case cost of insertions and deletions. Second, we show how to build a position heap in linear time independent of the size of the alphabet. Third, we show how to augment a position heap such that it supports access to the corresponding suffix array, and vice versa. Fourth, we introduce a variant of a position heap that can be simulated efficiently by a compressed suffix array with a linear number of extra bits.

Let $\D = $$ \{d_1,d_2,...d_D\}$ be a given set of $D$ string documents of total length $n$, our task is to index $\D$, such that the $k$ most relevant documents for an online query pattern $P$ of length $p$ can be retrieved efficiently. We propose an index of size $|CSA|+n\log D(2+o(1))$ bits and $O(t_{s}(p)+k\log\log n+poly\log\log n)$ query time for the basic relevance metric \emph{term-frequency}, where $|CSA|$ is the size (in bits) of a compressed full text index of $\D$, with $O(t_s(p))$ time for searching a pattern of length $p$ . We further reduce the space to $|CSA|+n\log D(1+o(1))$ bits, however the query time will be $O(t_s(p)+k(\log \sigma \log\log n)^{1+\epsilon}+poly\log\log n)$, where $\sigma$ is the alphabet size and $\epsilon >0$ is any constant., Comment: 12 pages

The number of the non-shared edges of two phylogenies is a basic measure of the dissimilarity between the phylogenies. The non-shared edges are also the building block for approximating a more sophisticated metric called the nearest neighbor interchange (NNI) distance. In this paper, we give the first subquadratic-time algorithm for finding the non-shared edges, which are then used to speed up the existing approximating algorithm for the NNI distance from $O(n^2)$ time to $O(n \log n)$ time. Another popular distance metric for phylogenies is the subtree transfer (STT) distance. Previous work on computing the STT distance considered degree-3 trees only. We give an approximation algorithm for the STT distance for degree-$d$ trees with arbitrary $d$ and with generalized STT operations.