Rank and select queries are basic operations on sequences, with applications in compressed text indexes and other space-efficient data structures. One of the standard data structures supporting these queries is the wavelet tree. In this paper, we study wavelet forests, that is, wavelet-tree structures based on the fixed-block compression boosting technique. Such structures partition the input sequence into fixed-size blocks and build a separate wavelet tree for each block. Previous work showed that this approach yields strong practical performance for rank queries. We extend wavelet forests to support select queries. We show that select support can be added with little additional space overhead and that the resulting structures remain practically efficient. In experiments on a range of non-repetitive and repetitive inputs, wavelet forests are competitive with, and in most cases outperform, standalone wavelet-tree implementations. We also study the effect of internal parameters, including superblock size and navigational data, on select-query performance.

One of the central problems in the design of compressed data structures is the efficient support for rank and select queries on bitvectors. These two operations form the backbone of more complex data structures used for the compact representation of texts, trees, graphs, or grids. One effective solution is the so-called hybrid bitvector implementation, which partitions the input bitvector into blocks and adaptively selects an encoding method - such as run-length, plain, or minority encoding - based on local redundancy. Experiments have shown that hybrid bitvectors achieve excellent all-around performance on repetitive and non-repetitive inputs. Current hybrid bitvector implementations, however, support only rank queries (i.e., counting the number of ones up to a given position) and lack support for select queries (which ask for the position of a given occurrence of a given bit), which limits their applicability. In this paper, we propose a method to add support for select queries to hybrid bitvectors, and we evaluate the resulting implementation on repetitive and non-repetitive inputs. Our results show that hybrid bitvectors offer very strong all-around performance, combining high query speed with space efficiency and remaining consistently on or near the Pareto frontier.