Warning: Some methods are impractical

Be careful not to make the wrong assumptions when studying the algorithms of this chapter. A few of them are efficient and easy to implement, but many might be neither. Even if an algorithm has an amazing asymptotic running time, it might be close to impossible to implement. For example, one of the most famous algorithms from computational geometry can split a simple^6.2 polygon into triangles in $O(n)$ time for a polygon with $n$ edges [190]. This is so amazing that it was covered in the New York Times, but the algorithm is so complicated that it is doubtful that anyone will ever implement it. Sometimes it is preferable to use an algorithm that has worse theoretical running time but is much easier to understand and implement. In general, though, it is valuable to understand both kinds of methods and decide on the trade-offs for yourself. It is also an interesting intellectual pursuit to try to determine how efficiently a problem can be solved, even if the result is mainly of theoretical interest. This might motivate others to look for simpler algorithms that have the same or similar asymptotic running times.