Stefan wrote:
* Optimize Boost String Algorithm finders to use an efficient substring matching algorithm as opposed to the naive algorithm. Most likely because of the fact that boost has implemented the finders for strings as generic algorithms, they haven't used efficient algorithms such as KMP, Boyer-Moore, Rabin-Karp etc. \see boost/algorithm/string/detail/finder.hpp The idea is to implement efficient algorithms such as the ones mentioned above to replace the current naive implementation. Note: it may be difficult to find nth matching substring position using some of these algorithms. Difficulty: easy-medium
* Implement a string algorithm for generating the suffix array. The suffix array, after being precomputed on a certain string, allows for very efficient substring searches in the future. This is useful when the string doesn't change too often but there are plenty of substring to search against.
Why are those two points separate? It seems to be the same thing: provides alternative and potentially better string searching algorithms. That seems fairly easy to get right and get included into boost.
* Space partitioning data structures? kd-trees? quadtrees? octtrees? collision detectors? closest neighbors?
There were already some projects about that in the past years, but I don't think they were very successful. You might want to take a look at them. Integrating with Boost.Geometry would definitely be good. (it already provides collision detection and closest neighbour I believe)
* In-place radix sort? Radix sort is a very efficient algorithm which performs better than std::sort (my implementation) (also asymptotically better) for some particular types such as: uint8_t, uint16_t, uint32_t, unsigned char, unsigned char[2], unsigned char[4] etc. Radix sorting takes linear time, but unfortunately, linear memory. It is very useful for sorting very large amounts of numbers tho (or genetic codes and maybe some other stuff).
I think there is a sorting library in the review queue that provides that kind of thing.