Introduction
N-Queens means:
- placing N queens
- on an N × N chessboard
Conditions:
- no two queens
- should attack each other
Queens attack:
- rows
- columns
- diagonals
Example:
N = 4One Valid Solution:
. Q . . . . . Q
Q . . . . . Q .
Explanation:
No queens share:
- same row
- same column- same diagonal
This problem is one of the most important applications of:
Advanced Backtracking Constraints
1 <= N <= 10 Approach : Backtracking Solution
Explanations:
Explanation:
The idea is:
- place queens row by row
- validate safe positions
Steps:
- Start from first row.
- Try every column.
- Check safe position.
- Place queen.
- Recurse for next row.
- Backtrack if invalid.
This approach:
- explores valid states
- prunes invalid placements
Dry Run
N = 4Place Queen:
Row 0 → Column 1
Place Queen:
Row 1 → Column 3
Place Queen:
Row 2 → Column 0
Place Queen:
Row 3 → Column 2
Valid arrangement found.
Practice :
Complexity Analysis :
Time Complexity:- ExponentialExplanation : Many recursive board states are explored.
Space Complexity:- O(n) Explanation : Recursion stack and board storage are used.
Why This Problem is Important
This problem builds the foundation for:
- Advanced backtracking
- Constraint satisfaction
- Recursive pruning
- State-space search
- Optimization problems
Real-World Applications
N-Queens concepts are used in:
- AI search systems
- Scheduling systems
- Puzzle solving
- Pathfinding algorithms
- Constraint optimization
Common Beginner Mistakes
- Incorrect diagonal checking
- Forgetting backtracking step
- Wrong recursion flow
- Invalid board updates
- Missing pruning logic
Interview Tip
Interviewers often expect:
- backtracking understanding
- pruning explanation
- constraint validation
- recursion tree analysis
Always explain:
- safe position checking
- recursive exploration
- pruning invalid placements
Related Questions
- Sudoku Solver
- Rat in Maze
- Permutations
- Combination Sum
- Backtracking Basics
Final Takeaway
The N-Queens problem is one of the most important advanced backtracking interview problems.
It teaches:
- recursive exploration
- pruning
- constraint validation
- state-space traversal
Understanding this problem builds a strong foundation for:
- advanced recursion problems
- optimization algorithms
- interview-level problem solving.