Backtracking Fundamentals

Backtracking is a systematic way to explore all possible solutions to a problem by making choices, exploring their consequences, and undoing them when they don't lead to valid solutions. Think of it as exploring a maze: try a path, and if it's a dead end, backtrack and try another path.

This unit introduces the core backtracking pattern and provides a universal template that solves most backtracking problems. The beauty of backtracking is that once you understand the choose-explore-unchoose pattern, you can apply it to generate permutations, combinations, subsets, and solve complex constraint satisfaction problems.

What You'll Learn

• Introduction to Backtracking: What backtracking is, when to use it, and how it differs from other approaches. You'll learn to recognize backtracking problems by keywords like "all possible," "generate all," and "find all solutions."

• The Backtracking Template: A universal pattern for backtracking problems with six key components: result container, current state, base case, choice iteration, pruning, and the choose-explore-unchoose cycle. You'll see variations for finding one solution, counting solutions, and finding the best solution.

Why It Matters

Backtracking problems appear regularly in coding interviews, especially for generating combinations, permutations, and solving constraint problems like N-Queens or Sudoku. The template approach means you're not solving each problem from scratch—you're filling in a proven framework. This unit gives you that framework.