The field of succinct data structures is moving towards developing more efficient and scalable solutions for storing and querying large datasets. Recent developments have focused on improving the performance of data structures such as hash tables, Burrows-Wheeler transforms, and fully indexable dictionaries. Notably, researchers have made significant progress in reducing the space and time complexity of these data structures, making them more suitable for real-world applications. Some notable papers in this area have achieved innovative results, including the development of new algorithms for constructing the Burrows-Wheeler transform of highly repetitive texts, and the design of optimal static fully indexable dictionaries. Noteworthy papers include:

• PHast, which introduces a new approach to perfect hashing with fast evaluation, achieving the currently fastest query time with competitive construction time and space consumption.
• Dynamic r-index, which presents an updatable self-index for highly repetitive strings that supports locate queries and string insertions and deletions.
• Engineering Minimal k-Perfect Hash Functions, which revives the area of k-perfect hashing and presents four new constructions that dominate older approaches in space consumption, construction time, and query time.