📚 Blog Series: Cracking Amazon Interviews with Patterns

Amazon is famous for focusing not just on coding ability but on patterns — reusable problem-solving approaches. Mastering these patterns allows you to handle a wide range of problems with confidence. In this series, we’ll break down the most commonly asked patterns at Amazon with explanations, real interview-style problems, and Java code snippets.

Part 1 – Sliding Window Pattern

Why Amazon asks this: Efficient handling of subarrays/substrings with optimal space-time complexity.
Key problems:
- Longest Substring Without Repeating Characters
- Minimum Window Substring
- Maximum Sum Subarray of Size K
Core idea: Maintain a window over a sequence and adjust it using two pointers.
Java snippet: Efficient sliding window implementation.

Part 2 – Two Pointers Pattern

Why Amazon asks this: Optimizes O(n²) brute-force approaches into O(n).
Key problems:
- Container With Most Water
- 3Sum Closest
- Move Zeroes
Core idea: Sort or use opposite ends of an array to converge on an answer.

Part 3 – Fast & Slow Pointers (Floyd’s Cycle)

Why Amazon asks this: Linked list & cycle detection are classics.
Key problems:
- Detect Cycle in Linked List
- Find the Middle Node of a Linked List
- Happy Number Problem
Core idea: Two pointers moving at different speeds to detect patterns.

Part 4 – Merge Intervals Pattern

Why Amazon asks this: Scheduling & interval merging is common in large-scale systems.
Key problems:
- Merge Intervals
- Insert Interval
- Minimum Meeting Rooms
Core idea: Sort by start time, merge overlapping intervals.

Part 5 – Monotonic Stack & Queue Pattern

Why Amazon asks this: Efficient next greater/smaller element problems.
Key problems:
- Next Greater Element
- Daily Temperatures
- Trapping Rain Water
Core idea: Use a stack/queue to maintain monotonic order.

Part 6 – Binary Search on Answer

Why Amazon asks this: Many optimization problems reduce to binary search on solution space.
Key problems:
- Koko Eating Bananas
- Capacity to Ship Packages within D Days
- Split Array Largest Sum
Core idea: Search over range of possible answers instead of raw array.

Part 7 – Backtracking & DFS Patterns

Why Amazon asks this: Tests recursion, state-space search, and optimization.
Key problems:
- Word Search
- N-Queens
- Generate Parentheses
Core idea: Explore all possibilities using recursion + pruning.

Part 8 – Dynamic Programming Patterns

Why Amazon asks this: DP is the most frequent advanced topic at Amazon.
Key problems:
- Longest Common Subsequence
- Coin Change
- Maximum Subarray (Kadane’s Algorithm)
Core idea: Breaking problems into overlapping subproblems, memoization, tabulation.

Part 9 – Greedy & Heap Patterns

Why Amazon asks this: Optimizing real-world scenarios with minimal operations.
Key problems:
- Top K Frequent Elements
- Meeting Rooms II (min heap)
- Reorganize String
Core idea: Locally optimal decisions leading to globally optimal solutions.

Part 10 – Graph & BFS/DFS Patterns

Why Amazon asks this: Amazon loves graph-based thinking for logistics, routing, dependencies.
Key problems:
- Rotten Oranges (BFS)
- Course Schedule (Topological Sort)
- Word Ladder
Core idea: Traversal, shortest paths, cycle detection.