But programs are often complicated at the microscopic level, and that is something I can address here. You can't tell where a program is going to spend its time. Bottlenecks occur in surprising places, so don't try to second guess and put in a speed hack until you've proven that's where the bottleneck is. Don't tune for speed until you've measured, and even then don't unless one part of the code overwhelms the rest. Fancy algorithms are slow when n is small, and n is usually small.
Fancy algorithms have big constants.
Until you know that n is frequently going to be big, don't get fancy. For example, binary trees are always faster than splay trees for workaday problems. Fancy algorithms are buggier than simple ones, and they're much harder to implement. Use simple algorithms as well as simple data structures. For instance, a symbol table might be implemented as a hash table containing linked lists of arrays of characters.