The field of computational geometry and string algorithms is witnessing significant developments, with a focus on improving the efficiency and accuracy of various algorithms and data structures. Researchers are exploring new approaches to solve long-standing problems, such as the construction of convex hulls, range reporting, and string matching. Notably, the use of space-filling curves and entropy-bounded computational geometry is gaining attention.

One of the key trends in this area is the development of simpler and more practical algorithms that can outperform more complex and theoretically optimal methods in practice. For example, a simple heuristic for distance reporting using space-filling curves has been shown to be competitive with more advanced data structures.

Another area of interest is the study of string algorithms, including the construction of indexing structures for rectangular pattern matching and the analysis of minimal unique substrings.

Some noteworthy papers in this area include: The paper on Better Indexing for Rectangular Pattern Matching, which presents a simple and efficient structure for locating all occurrences of a rectangular pattern in a two-dimensional string. The paper on Practical Insertion-Only Convex Hull, which investigates a variety of methods for constructing convex hulls in the insertion-only setting and presents a vector-based solution with improved cache performance. The paper on Simpler is Faster: Practical Distance Reporting by Sorting Along a Space-Filling Curve, which demonstrates the effectiveness of a simple heuristic for distance reporting using space-filling curves.