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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?

What interviewers test isn’t random problem memory, but your ability to identify recurring DSA logic patterns.

Tech giants like Google, Meta, Amazon, and Microsoft repeatedly test the same core ideas.

If you internalize these 90 key templates, recognizing the logic behind any problem becomes second nature.

What You’ll Learn


The guide maps all 90 DSA patterns into 15 logical families — the same framework elite engineers use to master FAANG interviews.

Learn how to train smarter through real-time AI-assisted exercises on Thita.ai.

Why Random LeetCode Grinding Doesn’t Work


Blindly solving hundreds of questions rarely helps you identify underlying algorithmic blueprints.

Think of patterns as templates you can reuse for any similar scenario.

For instance:
– Sorted array with a target ? Two Pointers (Converging)
– Find longest substring without repeats ? Sliding Window (Variable Size)
– Detect loop in linked list ? Fast & Slow 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)


Use Case: Fast array or string traversal through pointer logic.

Examples: Converging pointers, expanding from center, and two-pointer string comparison.

? Hint: Look for sorted input or pairwise relationships between indices.

2. Sliding Window Patterns (4 Patterns)


Used to handle range-based optimizations in arrays and strings.

Examples include fixed or variable windows, character tracking, and monotonic operations.

? Hint: Balance expansion and contraction logic to optimize results.

3. Tree Traversal Patterns (7 Patterns)


Used for recursive and iterative traversals across hierarchical structures.

4. Graph Traversal Patterns (8 Patterns)


Includes Dijkstra, Bellman-Ford, and disjoint set operations.

5. Dynamic Programming Patterns (11 Patterns)


Covers problems like Knapsack, LIS, Edit Distance, and Interval DP.

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


Ideal for top-K computations and real-time priority adjustments.

7. Backtracking Patterns (7 Patterns)


Includes subsets, permutations, N-Queens, Sudoku, and combination problems.

8. Greedy Patterns (6 Patterns)


Use Case: Achieving global optima through local choices.

9. Binary Search Patterns (5 Patterns)


Use Case: Efficient searching over sorted data or answer ranges.

10. Stack Patterns (6 Patterns)


Enables structured data management through stack logic.

11. Bit Manipulation Patterns (5 Patterns)


Crucial for low-level data operations.

12. Linked List Patterns (5 Patterns)


Focuses on optimizing node traversal and transformation.

13. Array & Matrix Patterns (8 Patterns)


Covers spiral traversals, rotations, and prefix/suffix computations.

14. String Manipulation Patterns (7 Patterns)


Use Case: Parsing, validation, and frequency analysis in strings.

15. Design Patterns (Meta Category)


Represents higher-order algorithmic design and data structure construction.

How to Practice Effectively on Thita.ai


The real edge lies in applying these patterns effectively through guided AI coaching.

Access the DSA 90 mock coding interview platform framework sheet to visualize all pattern families.

Next, select any pattern and explore associated real-world problems.

Step 3: Solve with AI Coaching ? Receive real-time hints, feedback, and explanations.

Track your improvement and focus on weak areas using detailed reports.

The Smart Way to Prepare


Traditional grinding wastes time — pattern-based learning delivers results.

Thita.ai provides the smartest route — combining AI guidance with proven DSA frameworks.

Why Choose Thita.ai?


On Thita.ai, you’ll:
– Learn efficiently using pattern recognition
– Get intelligent problem-solving assistance
– Access mock environments for FAANG-style practice
– Refine strategies through AI-curated guidance
– Build confidence and precision for real interviews.

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