Backtracking solves a problem by finding all possible solutions to its sub-problems and neglecting those which can not give a valid solution. It can eliminate many solutions with a single test, making the solution much faster than a brute-force approach. Hence, it is one of the most common topics for interviews.
Can backtracking be implemented using recursion?
Backtracking is also a form of recursion. Recursion is mainly used in those problems where there are chances of multiple solutions. It is used in backtracking to find all possible solutions until we get the best solution for the problem.
How do I know if I have backtracking problems?
There are mainly three types of problems in backtracking:
Decision Problems: To search for a feasible solution.
Optimization Problems: To search for the best solution.
Enumeration Problems: To find all feasible solutions.
In general, we can use backtracking to solve any constraint satisfaction problem that has clear and well-defined constraints on any objective solution.
Which algorithm uses backtracking?
A depth-first search is a particular form of backtracking. It uses backtracking to make searches in tree structures. Starting from the root node, we explore as far as possible along each branch before backtracking. Hence, backtracking and depth-first search are similar concepts as in both, we first explore a deeper node and then backtrack.
Which data structure is used for backtracking?
Backtracking problems are solved by constructing a search tree called a state-space tree. State-space tree represents all the possible solutions to the problem, having root node as the initial state and the leaf node as the final state. In this state-space tree, each branch represents a variable, and each level represents a solution.