Theoretical advances are constant (just check the literature), but two particular advances in the last decade are of practical importance: one for sort and one

Theoretical advances are constant (just check the literature), but two particular advances in the last decade are of practical importance: one for sort and one for hash table. As in: check the implementation you are using, if it doesn't incorporate these advances you are leaving substantial performance (2x is not out of the question) on the table. How Branch Mispredictions don't affect Quicksort (2016) https://arxiv.org/abs/1604.06697 https://arxiv.org/abs/1604.06697 Quicksort is still the algorithm of choice for general purpose internal unstable sort. In modern hardwares, quicksort spends a lot of time recovering from branch misprediction, because quicksort's comparison branches are inherently unpredictable. The problem is severe to the extent that with branchful quicksort, uneven split with more recursion is faster than even split, because it makes branches more predictable! Exact penalty is hardware microarchitecture specific, but one report is 20:80 split being optimal. So... you should use branchless quicksort! The technique was pioneered by an implementation called BlockQuicksort, but pdqsort (for pattern-defeating quicksort) https://arxiv.org/abs/2106.05123 https://arxiv.org/abs/2106.05123 is also popular. pdqsort incorporates branchless technique and also includes other enhancements. Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step (2017) https://abseil.io/blog/20180927-swisstables https://abseil.io/blog/20180927-swisstables Hash table is the workhorse of data structures, and while improvements are possible for specific usage patterns, open addressing with linear probing is still the fastest implementation for general purpose. So called "Swiss Table" combines cache-friendly metadata layout with SIMD-enhanced probing. These two optimizations work well with each other and combination of two is particularly effective.