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Patterns, Frameworks & Master Study Guides

Stop grinding random problems in the dark. Use community-tested mental models: the 5-step DP breakdown, universal sliding window templates, machine coding blueprints, and real FAANG interview debriefs.

15 Canonical Coding Interview Patterns

Each pattern links to the exact tutorial to learn the mental model, plus matching questions on our catalogue.

Hacker Noon 14 PatternsSean Prashad Patterns
Sliding WindowLearn Pattern

Maintains a contiguous window over an array or string that expands and shrinks to find optimal sub-ranges in linear time.

When to use: Problem involves finding the longest, shortest, or target-sum contiguous subarray/substring.
Canonical Questions:
#3 Longest Substring Without Repeating Characters#76 Minimum Window Substring#209 Minimum Size Subarray Sum
Practice topic questionsHacker Noon ref
Two PointersLearn Pattern

Iterates with two references converging from ends or moving toward a target in a sorted collection.

When to use: Sorted arrays/lists, searching for pairs with a target sum, reversing in-place, or verifying palindromes.
Canonical Questions:
#167 Two Sum II - Input Array Is Sorted#15 3Sum#11 Container With Most Water
Practice topic questionsHacker Noon ref
Fast & Slow PointersLearn Pattern

Moves two pointers at different speeds (Floyd's algorithm) to inspect cyclical behaviors and linked structures with O(1) space.

When to use: Detecting cycles in linked lists, finding middle node, or finding the duplicate number without mutating array.
Canonical Questions:
#141 Linked List Cycle#876 Middle of the Linked List#287 Find the Duplicate Number
Practice topic questionsHacker Noon ref
Merge IntervalsLearn Pattern

Sorts overlapping intervals by start time and consolidates overlapping ranges into unified bounds.

When to use: Meeting rooms scheduling, calendar conflicts, timeline merges, and range overlaps.
Canonical Questions:
#56 Merge Intervals#57 Insert Interval#435 Non-overlapping Intervals
Practice topic questionsHacker Noon ref
Cyclic SortLearn Pattern

Places elements in range [1, n] directly at index (value - 1) in linear time using minimal in-place swaps.

When to use: Finding missing, duplicate, or corrupted numbers within a 1-to-N or 0-to-N bounded array.
Canonical Questions:
#268 Missing Number#448 Find All Numbers Disappeared in an Array#41 First Missing Positive
Practice topic questionsHacker Noon ref
In-place Reversal of LinkedListLearn Pattern

Reverses sub-segments of linked lists by manipulating pointer references without allocating additional memory nodes.

When to use: Reversing entire linked list, reversing in K-groups, or reversing between positions m and n.
Canonical Questions:
#206 Reverse Linked List#92 Reverse Linked List II#25 Reverse Nodes in k-Group
Practice topic questionsHacker Noon ref
Tree Breadth-First Search (BFS)Learn Pattern

Processes tree and graph structures level-by-level using a FIFO Queue to examine shortest distances and level statistics.

When to use: Level order traversal, level averages, right side view, or zig-zag level order.
Canonical Questions:
#102 Binary Tree Level Order Traversal#199 Binary Tree Right Side View#103 Binary Tree Zigzag Level Order Traversal
Practice topic questionsHacker Noon ref
Tree Depth-First Search (DFS)Learn Pattern

Traverses deeply down branches recursively (or with an explicit stack) to inspect root-to-leaf paths and subtree heights.

When to use: Calculating maximum tree depth, root-to-leaf path sums, diameter, and lowest common ancestor.
Canonical Questions:
#112 Path Sum#113 Path Sum II#236 Lowest Common Ancestor of a Binary Tree
Practice topic questionsHacker Noon ref
Two Heaps (Min/Max Heap)Learn Pattern

Maintains two balanced priority queues (Max-Heap for lower half, Min-Heap for upper half) to query dynamic medians.

When to use: Finding running median of a data stream or balancing sliding windows of continuous metrics.
Canonical Questions:
#295 Find Median from Data Stream#480 Sliding Window Median
Practice topic questionsHacker Noon ref
Subsets & BacktrackingLearn Pattern

Explores all possible choices systematically via recursion, choosing an element, recurring, and undoing the choice.

When to use: Power sets, permutations, combinations, sudoku, N-Queens, and word search.
Canonical Questions:
#78 Subsets#46 Permutations#39 Combination Sum
Practice topic questionsHacker Noon ref
Modified Binary SearchLearn Pattern

Discards half of the remaining search space per step on sorted arrays, rotated arrays, or monotonic answer functions in O(log N).

When to use: Searching in rotated sorted arrays, finding boundary conditions, or optimization problems with monotonic feasibility.
Canonical Questions:
#33 Search in Rotated Sorted Array#153 Find Minimum in Rotated Sorted Array#875 Koko Eating Bananas
Practice topic questionsHacker Noon ref
Top 'K' ElementsLearn Pattern

Keeps a bounded Min-Heap of size K while iterating over N elements to extract extreme values in O(N log K) time.

When to use: Finding K largest, K smallest, or K most frequent elements without doing a full O(N log N) sort.
Canonical Questions:
#215 Kth Largest Element in an Array#347 Top K Frequent Elements#973 K Closest Points to Origin
Practice topic questionsHacker Noon ref
K-way MergeLearn Pattern

Inserts the first element of K sorted lists into a Min-Heap and repeatedly extracts the smallest element to build a unified stream.

When to use: Merging multiple sorted linked lists, arrays, or sorted matrix searches.
Canonical Questions:
#23 Merge k Sorted Lists#373 Find K Pairs with Smallest Sums#378 Kth Smallest Element in a Sorted Matrix
Practice topic questionsHacker Noon ref
0/1 Knapsack & Dynamic ProgrammingLearn Pattern

Models optimal choice decisions where items can either be included or excluded, memoizing state to prevent recomputation.

When to use: Subset sum partitions, target sums, minimum coin changes, and discrete resource allocation.
Canonical Questions:
#416 Partition Equal Subset Sum#494 Target Sum#322 Coin Change
Practice topic questionsHacker Noon ref
Topological SortLearn Pattern

Finds a linear sequence of tasks respecting directed prerequisite dependencies in a Directed Acyclic Graph (DAG) using Kahn's algorithm.

When to use: Build dependency resolution, course prerequisites, alien dictionaries, and task scheduling.
Canonical Questions:
#207 Course Schedule#210 Course Schedule II#269 Alien Dictionary
Practice topic questionsHacker Noon ref