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The Essential Ninety DSA Patterns That Cover Nearly All Coding Interviews


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You’ve spent hours grinding LeetCode problems — yet still find yourself freezing during live interviews?

Most companies reuse recurring data structure and algorithm (DSA) templates to evaluate problem-solving skills.

These organizations rely on pattern-based questions to assess how fast you adapt familiar logic to new contexts.

Understanding these 90 DSA blueprints equips you to decode almost any interview challenge with ease.

What You’ll Learn


Inside this guide, we organize 90 DSA templates into 15 essential families used by elite programmers.

On Thita.ai, you can experience pattern-based learning with interactive guidance and feedback.

Why Random LeetCode Grinding Doesn’t Work


Random problem-solving builds quantity, not recognition — and interviews reward recognition.

Patterns act like reusable schematics that instantly reveal how to solve new problems.

Sample applications:
– Target sum in sorted list ? Two Pointer technique
– Substring without duplicates ? Sliding Window
– Cycle detection ? Slow & Fast Pointers.

Those who excel identify the pattern first and adapt instantly.



The 15 Core DSA Pattern Families


Let’s dive into the core families that represent nearly every type of DSA problem.

1. Two Pointer Patterns (7 Patterns)


Used for efficient array/string navigation and pair-based operations.

Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.

? Tip: Sorted inputs often signal a two-pointer approach.

2. Sliding Window Patterns (4 Patterns)


Best for problems requiring flexible range adjustments.

Focuses on dynamically resizing sequences to meet constraints.

? Tip: Efficiency lies in the ability to manage window size dynamically.

3. Tree Traversal Patterns (7 Patterns)


Encompasses standard and Mock interviews advanced traversal techniques like LCA and serialization.

4. Graph Traversal Patterns (8 Patterns)


Focuses on efficient exploration and connection validation in networks.

5. Dynamic Programming Patterns (11 Patterns)


Central to solving resource allocation and sequence-based problems efficiently.

6. Heap (Priority Queue) Patterns (4 Patterns)


Helps in scheduling and optimization tasks.

7. Backtracking Patterns (7 Patterns)


Relies on decision trees and pruning to find valid outcomes.

8. Greedy Patterns (6 Patterns)


Relies on sorted order or prioritization strategies.

9. Binary Search Patterns (5 Patterns)


Applied in finding thresholds, boundaries, or minimum feasible values.

10. Stack Patterns (6 Patterns)


Involves handling nested structures and validation problems.

11. Bit Manipulation Patterns (5 Patterns)


Use Case: XOR-based logic, bit counting, and power checks.

12. Linked List Patterns (5 Patterns)


Common in list-based storage and cache designs.

13. Array & Matrix Patterns (8 Patterns)


Applied in image processing, pathfinding, and transformation tasks.

14. String Manipulation Patterns (7 Patterns)


Includes palindrome checking, encoding/decoding, and pattern validation.

15. Design Patterns (Meta Category)


Includes LRU Cache, LFU Cache, Min Stack, Trie, and Design Twitter.

How to Practice Effectively on Thita.ai


Learning the 90 DSA patterns is only the beginning — mastering their application is the key.

Begin by opening the full Thita.ai DSA pattern catalog.

Choose one category (e.g., Sliding Window) to practice related LeetCode-style problems.

Engage Thita.ai’s AI tutor for instant suggestions and solution breakdowns.

Step 4: Track Progress ? Analyze performance and identify weak zones.

The Smart Way to Prepare


Success in coding interviews is built on pattern familiarity, not repetition.

Use Thita.ai’s roadmap to learn, practice, and refine through intelligent feedback.

Why Choose Thita.ai?


Thita.ai empowers learners to:

– Master 90 reusable DSA patterns
– Practice interactively with AI feedback
– Experience realistic mock interviews
– Prepare for FAANG and top-tier interviews
– Build a personalized, AI-guided learning path.

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