Backtracking is an algorithm for finding all (or some) of the solutions to a problem that incrementally builds candidates to the solution(s). As soon as it determines that a candidate cannot possibly lead to a valid solution, it abandons the candidate. Backtracking is all about choices and consequences.

In this article I’m trying to explain the difference/similarities between dynamic programing and divide and conquer approaches based on two examples: binary search and minimum edit distance (Levenshtein distance).

Here's a recap of how you should be spending your day at work:

9:00AM-3:30PM: Start by reading your checkpoint notes from the day before so you can get started immediately, then work normally.

3:30PM-4:45PM: Continue on existing task, if you’re finished then transition to small tasks and planning.

4:45PM-5:00PM: Checkpoint your work, then leave your office.

5:00PM-…: Whatever you want to do.