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版本更新 · v2arXiv:2609.01365

The Greedy Superstring Conjecture Is False

Nikolai Chukhin, Rishikesh Gajjala, Juha Harviainen, Alexander S. Kulikov, Ivan Mihajlin, Hiroki Shibata, Alexander V. Smal

原文摘要

In the Shortest Common Superstring problem (SCS), one is given a finite set of strings and is asked to find a shortest string containing every input string as a substring. Since the problem is NP-hard, various approximation algorithms have been proposed for it. The currently best known approximation ratio is $2.466$ due to Englert, Matsakis, and Veselý; a better approximation ratio $2$ has been announced by OpenAI just recently. In 1988, Tarhio and Ukkonen introduced a simple greedy algorithm that iteratively takes two strings with the longest overlap and merges them together. They showed that the greedy algorithm may produce a superstring that is about two times longer than the optimal one and conjectured that this bound is tight. This has become known as the Greedy Superstring Conjecture and has remained open for almost four decades. The best known upper bound on the approximation ratio of the greedy algorithm is $3.396$ due to Englert, Matsakis, and Veselý. In this paper, we present a series of results tightening the bounds of the greedy algorithm, with the main contributions being as follows: 1. We refute the Greedy Conjecture by constructing a family of instances for which a lower bound on the approximation ratio tends to $2.4$. 2. We prove that the greedy algorithm is $3$-approximate. 3. For input strings of fixed length $k$, we prove that the approximation guarantee is exactly $9/5$ for $k=3$ and at least $2$ for all $k \ge 6$.

cs.DS

版本更新 · v2arXiv:2605.13074

Computing Ultrabubbles in Linear Time by Reduction to Weak Superbubbles in the Double Covering Graph

Sebastian Schmidt, Juha Harviainen, Corentin Moumard, Aleksandr Politov, Francisco Sena, Alexandru I. Tomescu

原文摘要

In recent years, in attempts to capture variation structures in genomic and pangenomic graphs, the zoo of bubbles has been filled with more and more different variants. The first more complex variant was the superbubble which was later (informally) generalised to bidirected graphs as the ultrabubble. Ultrabubbles are more applicable in bioinformatics research, because genome and pangenome graphs usually are bidirected. In this paper, we study the relationship between superbubbles and ultrabubbles, and show that ultrabubbles in a bidirected graph are equivalent to the weak superbubbles in the corresponding double covering graph. Using this, we introduce a new linear-time algorithm to enumerate all ultrabubbles that consists of a very simple reduction to employ an existing linear-time algorithm to enumerate all weak superbubbles. Treating the superbubble algorithm as a black box, our algorithm is vastly simpler than the SPQR-tree-based linear-time ultrabubble enumeration algorithm of Sena et al. [2026]. Further, since our algorithm works on all bidirected graphs, it is strictly more powerful than the simple graph-orientation-based algorithm by Harviainen et al. [2026], which only works on a restricted class of bidirected graphs. In order to prove our equivalence, we additionally introduce simplified definitions of both ultrabubbles and weak superbubbles, through which the equivalence becomes more intuitive. Finally, our reduction motivates that some algorithmic problems in bidirected graphs can be reduced to well-known algorithmic problems in directed graphs.

cs.DS