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The 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?
What interviewers test isn’t random problem memory, but your ability to identify recurring DSA logic patterns.
Big tech interviews at companies like Google, Amazon, and Microsoft revolve around consistent logic frameworks.
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.
You’ll be guided on how to practice these patterns dynamically through AI-driven hints and feedback on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Random problem-solving builds quantity, not recognition — and interviews reward recognition.
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.
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)
Used for efficient array/string navigation and pair-based operations.
Examples: Converging pointers, expanding from center, and two-pointer string comparison.
? Tip: Sorted inputs often signal a two-pointer approach.
2. Sliding Window Patterns (4 Patterns)
Applicable when analyzing contiguous sequences in data.
Examples include fixed or variable windows, character tracking, and monotonic operations.
? Pro Tip: DSA patterns sheet Learn when to expand or contract your window efficiently.
3. Tree Traversal Patterns (7 Patterns)
Applicable in computing paths, depths, and relationships within trees.
4. Graph Traversal Patterns (8 Patterns)
Applied in DFS, BFS, shortest paths, and union-find logic.
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)
Use Case: Achieving global optima through local choices.
9. Binary Search Patterns (5 Patterns)
Used in range partitioning and target detection.
10. Stack Patterns (6 Patterns)
Enables structured data management through stack logic.
11. Bit Manipulation Patterns (5 Patterns)
Use Case: XOR-based logic, bit counting, and power checks.
12. Linked List Patterns (5 Patterns)
Focuses on optimizing node traversal and transformation.
13. Array & Matrix Patterns (8 Patterns)
Focuses on efficient iteration over structured grids.
14. String Manipulation Patterns (7 Patterns)
Use Case: Parsing, validation, and frequency analysis in strings.
15. Design Patterns (Meta Category)
Includes LRU Cache, LFU Cache, Min Stack, Trie, and Design Twitter.
How to Practice Effectively on Thita.ai
Knowledge without practice falls short — Thita.ai helps bridge that gap with interactive learning.
Begin by opening the full Thita.ai DSA pattern catalog.
Step 2: Choose a Pattern ? Pick one like “Sliding Window – Variable Size.”
Engage Thita.ai’s AI tutor for instant suggestions and solution breakdowns.
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.
Pattern-based learning through Thita.ai ensures faster growth and higher recall.
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.