Core Concepts
We present the first dynamic compressed data structure that supports suffix array (SA) queries and updates in polylogarithmic time and δ-optimal space, where δ is a measure of string repetitiveness. The data structure also supports essential queries for realizing suffix trees, including inverse suffix array (ISA), random access (RA), and longest common extension (LCE) queries.
Abstract
The content discusses the development of an efficient dynamic compressed data structure that supports various string queries, with a focus on the suffix array (SA) query.
Key highlights:
The data structure supports SA queries, updates, ISA queries, RA queries, and LCE queries in polylogarithmic time using expected δ-optimal space, where δ is a measure of string repetitiveness.
The data structure is built using a randomized algorithm based on the restricted recompression technique, which constructs a derivation tree from the input string.
The authors introduce novel concepts such as interval attractors, restricted suffix count (RSC) queries, and restricted suffix search (RSS) queries to efficiently answer SA queries.
The update operation is achieved by modifying the directed acyclic graph (DAG) representation of the derivation tree and the weighted points representing non-periodic interval attractors.
The expected space complexity of the data structure is O((H + δ log n log σ/δ log n)B) bits, where H is the height of the derivation tree, n is the length of the input string, σ is the alphabet size, and B is the machine word size.
The time complexity for SA and ISA queries is O(H^3 log^2 n + H log^6 n) and O(H^3 log n + H log^4 n), respectively, where H = O(log n) with high probability.
The content provides a comprehensive and detailed summary of the proposed dynamic compressed data structure, its key components, and the theoretical guarantees on its performance and space efficiency.