15 Must-Know Coding Patterns to Ace Your Tech Interview (with Resources)

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit --- Educative.io

Hello Devs, if you have prepared for coding interviews, then you know how daunting it can be. Apart from the regular work you do, you need to spend a considerable amount of time practicing data structure and algorithm problems just for the interview.

I have done that, but more often than not, it's either miss or hit.

If you have practiced the coding problem, then the interview can be a breeze. All you need to do is act as if you are solving that question for the first time. However, if you get an unknown question, then good luck to you.

I knew my interview prep approach wasn't foolproof and needed improvement.

After solving numerous problems, I noticed certain tricks or patterns that I could apply repeatedly — for example, how the Two-Pointer technique on a linked list can help find the middle element or detect a cycle.

I didn't know that these are essential coding patterns until I came across Grokking the Coding Interview: Patterns for Coding Questions course from DesignGurus.io. This course teaches you 24 coding patterns that can be used to solve thousands of LeetCode problems.

That's the first time I came across this terminology, and I also learned many other patterns I didn't even know.

Just knowing that helped me a lot in my coding interview prep, and also to many of my readers who thanked and appreciated me that I told them about these patterns and this course.

In this article, I am going to share 15 essential coding interview patterns you can use to solve 100+ coding problems on Leetcode. Many of them are also covered in Algomonster), in greater depth.

Now, you don't need to blindly solve many coding problems just to get your hands on it. Instead, learn these patterns and then start using them to solve problems.

To make your preparation structured and effective, I also recommend Grokking Advanced Coding Patterns for Interviews from Designgurus.io. This course covers more advanced coding patterns you need for interviews and integrates interactive practice.

Educative also just rolled out AI-powered Personalized Interview Preparation Plan.

Think of it as a custom prep roadmap, tailored to your strengths and gaps.

15 Coding Patterns to Crack Tech Interviews

Without any further ado, here are the 15 essential coding patterns you should master, along with 2- 3 Leetcode problems to practice for each. These patterns are also quite common on FAANG and Big Tech interviews, as analysed by Algomonster.com, one of the popular websites for coding interview prep from ex-Google engineers.

1. Two Pointers

Two Pointers is a versatile pattern that involves using two pointers to traverse an array or linked list efficiently.

This was the first coding pattern I learned, and it works remarkably well on solving linked list and array-based problems like finding the middle elements of the list or finding the kth element from the end of the list.

Key Concepts:

• Optimize problems involving pairs, such as sum or difference.
• Avoid nested loops to reduce time complexity.

LeetCode Problems:

1. Two Sum II --- Input Array Is Sorted (167)
2. Remove Duplicates from Sorted Array (26)
3. Move Zeroes (283)

---

2. Prefix Sum

Prefix Sum is a powerful technique for optimizing range queries in arrays. By preprocessing cumulative sums, you can solve range-based problems efficiently.

This coding pattern is also very important for solving array-based problems like Subarray Sum Equals K on Leetcode.

Key Concepts:

• Precompute cumulative sums for quick access.
• Use for range queries like subarray sums.

Leetcode Problems:

1. Range Sum Query --- Immutable (303)
2. Subarray Sum Equals K (560)
3. Minimum Value to Get Positive Step by Step Sum (1413)

---

3. Sliding Window

Sliding Window is a powerful pattern to optimize problems involving contiguous subarrays. This problem can be tough to understand at first, but once you solve a couple of problems, you will appreciate its simplicity.

Key Concepts:

• Maintain a window over part of the array.
• Expand or contract the window as needed.

Leetcode Problems:

1. Longest Substring Without Repeating Characters (3)
2. Maximum Sum of Subarray of Size K (643)
3. Minimum Window Substring (76)

You can further see Algomonster.com's article and explanation on the Sliding Window to understand this pattern better.

---

4. Fast & Slow Pointers

Fast & Slow Pointers (also called Floyd's Cycle Detection) are commonly used for cycle detection in Linked Lists. This pattern is also known as the tortoise and hare pattern.

Key Concepts:

• Use two pointers moving at different speeds.
• Detect cycles or meeting points in a sequence.

Leetcode Problems:

1. Linked List Cycle (141)
2. Find the Duplicate Number (287)
3. Happy Number (202)

---

5. LinkedList In-Place Reversal

This pattern focuses on reversing portions of a Linked List without extra space. In-place algorithms can be used when you have memory constraints.

Key Concepts:

• Reverse a Linked List iteratively or recursively.
• Solve problems requiring sublist reversal.

LeetCode Problems:

1. Reverse Linked List (206)
2. Reverse Linked List II (92)
3. Swap Nodes in Pairs (24)

---

6. Monotonic Stack

The Monotonic Stack is a structured stack that maintains elements in sorted order (increasing or decreasing).

Key Concepts:

• Solve problems involving the next greater or smaller element.

LeetCode Problems:

1. Daily Temperatures (739)
2. Next Greater Element I (496)
3. Largest Rectangle in Histogram (84)

Though, when it comes to mastering this pattern, I found this flow chart on Algomonster.com and it's really great. It makes when to use this pattern a cakewalk if you know the concepts. I have used this site, and it's really great for anyone preparing for coding interviews.

---

7. Top 'K' Elements

This pattern focuses on efficiently finding the top K largest, smallest, or most frequent elements. You can use this pattern to solve problems like how to find the Kth largest element in a given array.

You can also find many questions based on these patterns on Educative-99, where you will get a chance to solve 99 selected questions instead of 2800 Leetcode problems.

Key Concepts:

• Use heaps (priority queues) or sorting.

LeetCode Problems:

1. Top K Frequent Elements (347)
2. Kth Largest Element in an Array (215)
3. Find K Pairs with Smallest Sums (373)

---

8. Overlapping Intervals

This pattern deals with problems involving intervals (e.g., time ranges, numeric ranges) where you need to detect, merge, or manipulate overlapping segments. It often requires sorting intervals by start time.

Key Idea: Sort intervals, then iterate to check for overlaps, merge them, or count conflicts based on problem constraints.

When to Use: Scheduling problems, resource allocation, or any scenario with start/end pairs.

Common Problems:
- Merge Intervals: Combine overlapping intervals into a single range.
- Non-Overlapping Intervals: Remove the minimum intervals to make the rest non-overlapping.
- Meeting Rooms: Determine if meetings conflict or how many rooms are needed.

Key Concepts:

• Sort intervals and merge based on conditions.

LeetCode Problems:

1. Merge Intervals (56)
2. Insert Interval (57)
3. Meeting Rooms II (253)

---

9. Modified Binary Search

Modified Binary Search optimizes searching in sorted or rotated arrays.

Key Concepts:

• Apply binary search creatively for custom conditions.

LeetCode Problems:

1. Binary Search (704)
2. Search in Rotated Sorted Array (33)
3. Find Peak Element (162)

---

10. Binary Tree Traversal

This is not a pattern but an essential binary tree concept, which is presented as a pattern. Basically, you need to learn various traversal techniques, such as in-order, pre-order, and post-order, to solve tree problems.

Another key thing to remember is that with the inorder traversal, you can print the list in a sorted order. Not many developers know this,s but it's a very good thing to remember.

LeetCode Problems:

1. Binary Tree Inorder Traversal (94)
2. Maximum Depth of Binary Tree (104)

Here is a nice diagram which shows different ways to traverse a binary tree like preorder, indorder and postorder

---

11. Depth-First Search (DFS)

DFS explores tree or graph nodes as deeply as possible before backtracking. In other words, all the nodes in one branch are explored before starting another branch.

Leetcode Problems:

1. Path Sum (112)
2. Number of Islands (200)

---

12. Breadth-First Search (BFS)

BFS explores nodes level by level, often implemented with a queue. This pattern is used to solve binary tree-related patterns, and it is also known as level-order traversal because it traverses all nodes in one level before moving to the next level.

LeetCode Problems:

1. Binary Tree Level Order Traversal (102)

Also, here is a nice diagram which explains the difference between breadth first and depth first search clearly

---

13. Matrix Traversal

Matrix Traversal involves navigating a 2D array (matrix) to solve problems like searching, counting paths, or collecting elements. Common approaches include depth-first search (DFS), breadth-first search (BFS), or iterative traversal.

Key Idea: Systematically visit matrix cells (rows/columns) while handling boundaries and tracking visited cells.

When to Use: Problems involving grids, such as finding paths, connected components, or specific patterns in a matrix.

Common Problems:
- Number of Islands: Count distinct landmasses in a grid (1s = land, 0s = water).
- Spiral Matrix: Return elements in spiral order.
- Flood Fill: Change a region's color starting from a given cell.

LeetCode Problems:

1. Flood Fill (733)

---

14. Backtracking

Backtracking is a recursive algorithmic pattern for solving problems by exploring all possible solutions incrementally and abandoning paths that don't lead to a valid solution.

It's like navigating a maze: you try a path, backtrack if it's a dead end, and try another.

• Key Idea: Build a solution step-by-step, and if it violates constraints, undo steps (backtrack) and try a different path.
• When to Use: Problems requiring all possible combinations, permutations, or solutions, often with constraints (e.g., puzzles, graph traversals).
• Common Problems:
  • N-Queens: Place N queens on an NxN chessboard so none attack each other.
  • Subsets: Generate all subsets of a set.
  • Sudoku Solver: Fill a 9x9 grid following Sudoku rules.

LeetCode Problems:

1. Subset (78)

Backtracking is a go-to for combinatorial problems in interviews. It tests recursion, state management, and problem decomposition—key skills for Java developers.

---

15. Dynamic Programming Patterns

Dynamic Programming focuses on breaking problems into subproblems and solving them optimally, and you can develop patterns by solving problems like the knapsack problem.

LeetCode Problems:

1. Climbing Stairs (70)
2. Longest Increasing Subsequence (300)

I also suggest that you go through Grokking Dynamic Programming Patterns for Coding Interviews on Educative to better understand these Dynamic programming patterns.

---

Top 6 Resources to Crack Coding Interviews

While I have mentioned the resource along with the articles, here is the summary of the top 6 resources I have used for coding interview preparation apart from popular books like Cracking the Coding Interview by Gayle Mcdowell and Coding Interview Patterns by Alex Xu and Shaun Gunawardane

Here are the top resources for coding interview prep, capturing their essence and value for developers in 2025:

1. AlgoMonster

   • Focused, pattern-based, efficient, and structured preparation.

2. LeetCode

   • Comprehensive, practice-heavy, community-driven

3. Educative

   • Interactive, text-based, in-depth

4. DesignGurus

   • Structured, pattern-focused, expert-led

5. Udemy

   • Affordable, video-based, diverse

6. ZTM Academy

   • Practical, project-driven, career-focused

And, if you prefer to read books, then Coding interview pattern book by Alex Xu and Shaun Gunawardane is another great book to learn coding interview patterns.

You will also learn 24 patterns there, and then you can combine these patterns with consistent LeetCode practice, and you'll be well-prepared to land your dream job!

That's it about the 15 essential Coding Interview Patterns for interviews. You must master these 15 patterns if you want to crack the interview and get the offer you want.

Preparing for coding interviews can be daunting, but focusing on essential problem-solving and coding patterns can make it significantly easier.

Instead of learning solutions to individual problems, mastering these patterns will help you tackle various coding challenges effectively.

You can also start with the Educative-99**, for a structured preparation. Here you will get a chance to solve 99 selected questions instead of 2800 Leetcode problems. This will also help you to master the above coding patterns better.

By the way, I have shared best data structure interview books and software engineering books, best System design books and courses, if you haven't checked them yet then you can also see them for coding interview prep and also covering all the bases.