Leetcode pattern difficulty

This document is based on the concepts outlined in the post Leetcode Patterns and provides a summarized interpretation prepared with the assistance of Claude.

LeetCode Patterns: Easy to Hard Progression

EASY (Start Here)

1. Two Pointers

• Why Easy: Simple concept, intuitive logic
• Key Use: Palindromes, removing duplicates, sorted arrays
• Time Improvement: O(N²) → O(N)

2. Binary Search

• Why Easy: Well-defined algorithm, clear conditions
• Key Use: Finding elements in sorted arrays
• Time Improvement: O(N) → O(log N)

3. Prefix Sum

• Why Easy: Straightforward array preprocessing
• Key Use: Range sum queries, subarray sums
• Time Improvement: O(N) per query → O(1) per query

EASY-MEDIUM

4. Sliding Window

• Why Easy-Medium: Builds on two pointers, but requires window management
• Key Use: Subarray/substring problems with conditions
• Time Improvement: O(N²) → O(N)

5. Slow and Fast Pointers

• Why Easy-Medium: Simple concept but requires understanding of pointer speeds
• Key Use: Cycle detection, finding middle of linked list
• Space Improvement: O(N) → O(1)

6. Binary Tree Traversal

• Why Easy-Medium: Fundamental tree operations, good introduction to recursion
• Key Use: Tree processing, serialization, level-order operations

MEDIUM

7. In Place Linked List Reversal

• Why Medium: Requires careful pointer manipulation
• Key Use: Reversing lists, reversing in groups
• Space: O(1) solution

8. Top K Elements

• Why Medium: Requires understanding heaps and priority queues
• Key Use: Finding largest/smallest K elements
• Time Improvement: O(N log N) → O(N log K)

9. Overlapping Intervals

• Why Medium: Requires sorting and merging logic
• Key Use: Meeting rooms, scheduling, range merging
• Key Skill: Interval manipulation

10. Bit Manipulation

• Why Medium: Requires understanding of binary operations
• Key Use: Missing numbers, addition without operators
• Note: Less common but powerful when needed

MEDIUM-HARD

11. Monotonic Stack

• Why Medium-Hard: Requires understanding of stack properties and when to use them
• Key Use: Next greater/smaller element problems
• Time Improvement: O(N²) → O(N)

12. Graph and Matrices

• Why Medium-Hard: Multiple algorithms (DFS, BFS, topological sort)
• Key Use: Path finding, connectivity, ordering
• Complexity: Requires understanding of graph theory

HARD

13. Dynamic Programming

• Why Hard: Requires identifying optimal substructure and overlapping subproblems
• Key Use: Optimization problems, counting problems
• Time Improvement: Exponential → Polynomial
• Note: Often the most challenging pattern to master

14. Backtracking

• Why Hard: Requires understanding recursion, pruning, and constraint satisfaction
• Key Use: Combinatorial problems, puzzles (Sudoku, N-Queens)
• Complexity: Can be exponential but with smart pruning

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Learning Progression Tips

Phase 1: Foundation (Easy)

Master Two Pointers, Binary Search, and Prefix Sum first. These give you confidence and fundamental problem-solving skills.

Phase 2: Expansion (Easy-Medium)

Add Sliding Window, Slow/Fast Pointers, and Tree Traversal. These build on your foundation.

Phase 3: Intermediate (Medium)

Learn Top K Elements, Overlapping Intervals, Linked List Reversal, and Bit Manipulation. These introduce new data structures and concepts.

Phase 4: Advanced (Medium-Hard)

Tackle Monotonic Stack and Graph problems. These require combining multiple concepts.

Phase 5: Expert (Hard)

Master Dynamic Programming and Backtracking last. These are the most conceptually challenging.

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Practice Strategy

1. Start with 2-3 easy problems per pattern before moving to the next
2. Don’t rush - ensure you understand the “why” behind each pattern
3. Practice recognizing when to use each pattern in new problems
4. Review and revisit patterns regularly to maintain proficiency