Backtracking calculates and finds the best overall solution to a particular problem. However, as described in Chapter 8, Algorithm Evaluation, there are problems that have a really large computational complexity, which leads to a really long running time. Since this is unlikely to be solved by simply making computers faster, smarter approaches are required.
With several strategies and techniques available, the choice is yours to find an approach that best solves your problem. The position of Rust in this space can be critical, thanks to its great speed and memory efficiency, so keeping an eye on solutions for complex problems might pay off in the future (in the author's opinion).
First up is a surprising programming technique that is aimed at improving the complexities of backtracking algorithms: dynamic programming.
