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The Essential Ninety DSA Patterns That Cover Nearly All Coding Interviews
Even after solving hundreds of LeetCode questions, do you still struggle when faced with real coding interviews?
Here’s the secret: most coding interviews don’t test unique problems — they reuse established logical templates.
Major companies prefer problem templates that measure reasoning, not rote memory.
Understanding these 90 DSA blueprints equips you to decode almost any interview challenge with ease.
What You’ll Learn
This comprehensive guide breaks down 90 DSA patterns grouped into 15 core categories.
Learn how to train smarter through real-time AI-assisted exercises on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Without pattern-based learning, random LeetCode practice fails to build adaptability.
Once recognized, a pattern turns complex problems into familiar exercises.
Example mappings include:
– Sorted Array + Target Sum ? Two Pointers (Converging)
– Longest Substring Without Repeats ? Sliding Window (Variable Size)
– Cycle in Linked List ? Fast & Slow Pointers.
Elite developers rely on pattern familiarity, not brute-force memorization.
The 15 Core DSA Pattern Families
Every pattern family addresses specific classes of problems that recur across companies.
1. Two Pointer Patterns (7 Patterns)
Use Case: Fast array or string traversal through pointer logic.
Key Patterns: Converging pointers, Fast & Slow pointers, Fixed separation, In-place modification, Expand from center, String reversal, and Backspace comparison.
? Tip: Sorted inputs often signal a two-pointer approach.
2. Sliding Window Patterns (4 Patterns)
Applicable when analyzing contiguous sequences in data.
Key Patterns: Fixed-size learn Data science AI window, Variable-size window, Monotonic queue, Character frequency matching.
? Tip: Efficiency lies in the ability to manage window size dynamically.
3. Tree Traversal Patterns (7 Patterns)
Applicable in computing paths, depths, and relationships within trees.
4. Graph Traversal Patterns (8 Patterns)
Use Case: Connectivity, pathfinding, and topology analysis.
5. Dynamic Programming Patterns (11 Patterns)
Central to solving resource allocation and sequence-based problems efficiently.
6. Heap (Priority Queue) Patterns (4 Patterns)
Ideal for top-K computations and real-time priority adjustments.
7. Backtracking Patterns (7 Patterns)
Powerful for constraint satisfaction and combinatorial logic.
8. Greedy Patterns (6 Patterns)
Common in interval scheduling, stock profits, and gas station routes.
9. Binary Search Patterns (5 Patterns)
Use Case: Efficient searching over sorted data or answer ranges.
10. Stack Patterns (6 Patterns)
Great for parentheses matching, evaluation, and next greater element logic.
11. Bit Manipulation Patterns (5 Patterns)
Use Case: XOR-based logic, bit counting, and power checks.
12. Linked List Patterns (5 Patterns)
Includes reversal, merging, and cycle detection problems.
13. Array & Matrix Patterns (8 Patterns)
Focuses on efficient iteration over structured grids.
14. String Manipulation Patterns (7 Patterns)
Used for matching, substring searches, and string reconstruction.
15. Design Patterns (Meta Category)
Applied in designing scalable and efficient systems.
How to Practice Effectively on Thita.ai
The real edge lies in applying these patterns effectively through guided AI coaching.
Start) by reviewing the official 90 DSA pattern sheet on Thita.ai.
Next, select any pattern and explore associated real-world problems.
Solve questions while the AI gives contextual hints, code feedback, and performance tips.
Track your improvement and focus on weak areas using detailed reports.
The Smart Way to Prepare
Success in coding interviews is built on pattern familiarity, not repetition.
Thita.ai provides the smartest route — combining AI guidance with proven DSA frameworks.
Why Choose Thita.ai?
Thita.ai helps you achieve interview mastery by offering:
– Comprehensive 90 DSA pattern training
– Real-time AI insights
– Mock interview simulations
– Tailored progress analytics
– Structured growth tracking.