Summary of "LeetCode Was Hard Until I Learned THESE 8 Patterns (With Templates!)"

Main Ideas and Concepts

Patterns Overview
- Linear Patterns: For data structures like arrays, linked lists, and strings.
- Nonlinear Patterns: For data structures like trees and graphs.
Linear Patterns
- Two Pointers
  - Reduces time complexity by allowing traversal in linear time (O(n)).
  - Two methods:
    - Same Direction: Used for single-pass problems (e.g., detecting cycles in linked lists).
    - Opposite Directions: Used for finding pairs (e.g., two numbers that sum to a target).
- Sliding Window
  - An extension of the two-pointer technique that maintains a dynamic range of elements.
  - Useful for problems involving substrings or subarrays (e.g., finding the longest substring without repeating characters).
- Binary Search
  - Efficiently finds a target in a sorted array using a divide-and-conquer strategy (O(log n)).
  - Applicable to any monotonic function, not just sorted numbers.
- Heaps
  - Used for finding top K elements (K smallest or largest).
  - Min Heap for K largest values; Max Heap for K smallest values.
Nonlinear Patterns
- Breadth-First Search (BFS)
  - Explores nodes level by level in trees or graphs using a queue.
  - Ideal for problems requiring level order traversal (e.g., level order traversal of a binary tree).
- Depth-First Search (DFS)
  - Explores as far down a branch as possible before backtracking.
  - Suitable for problems that require exploring all paths (e.g., counting islands in a grid).
- Backtracking
  - An extension of DFS, exploring all possible solutions by making decisions and backtracking when necessary (e.g., generating letter combinations from phone numbers).
- Dynamic Programming (DP)
  - Involves optimizing solutions by breaking them down into overlapping subproblems.
  - Two approaches: Top-Down (recursion with memorization) and Bottom-Up (iterative table filling).

Methodologies and Instructions

Two Pointers:
- Use Two Pointers moving in the same direction for single-pass problems.
- Use Two Pointers moving in opposite directions for pair finding.
Sliding Window:
- Maintain a start and end pointer to dynamically adjust the window size based on conditions.
Binary Search:
- Start with left and right pointers, checking the middle element and adjusting based on comparisons.
BFS:
- Use a queue to process nodes level by level.
DFS:
- Use a stack (or recursion) to explore one path as deeply as possible before backtracking.
Backtracking:
- Explore potential solutions by making decisions and undoing them when hitting dead ends.
Dynamic Programming:
- Use memorization for top-down approaches; fill out tables for bottom-up approaches.

Featured Speakers/Sources

The video references "Algo Monster" for additional resources and templates related to the patterns discussed.

This summary encapsulates the key takeaways from the video, providing a structured overview of the patterns and methodologies useful for coding interviews.