The Essential Ninety DSA Patterns That Cover Nearly All Coding Interviews
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.
By learning 90 carefully chosen DSA patterns, you’ll unlock solutions to 99% of interview problems instantly.
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.
You’ll also discover how to practice these patterns interactively with AI feedback using 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
These pattern families cover the foundational structures behind most coding interview challenges.
1. Two Pointer Patterns (7 Patterns)
Applied in problems where two indices move strategically across data structures.
Core templates: Converging, Slow/Fast, Expansion, and In-place transformations.
? Pro Tip: Check if the data is sorted or relationships exist between index pairs.
2. Sliding Window Patterns (4 Patterns)
Use Case: Optimize subarray or substring challenges dynamically.
Key Patterns: Fixed-size window, Variable-size window, Monotonic queue, Character frequency matching.
? Pro Tip: Learn when to expand or contract your window efficiently.
3. Tree Traversal Patterns (7 Patterns)
Use Case: Binary and N-ary tree exploration including BFS, DFS, LCA, and serialization.
4. Graph Traversal Patterns (8 Patterns)
Use Case: Connectivity, pathfinding, and topology analysis.
5. Dynamic Programming Patterns (11 Patterns)
Use Case: Optimization with overlapping subproblems and state transitions.
6. Heap (Priority Queue) Patterns (4 Patterns)
Use Case: Ranking, median finding, and scheduling challenges.
7. Backtracking Patterns (7 Patterns)
Powerful for constraint satisfaction and combinatorial logic.
8. Greedy Patterns (6 Patterns)
Great for problems solvable with stepwise optimization.
9. Binary Search Patterns (5 Patterns)
Core to logarithmic time optimizations.
10. Stack Patterns (6 Patterns)
Great for parentheses matching, evaluation, and next greater element logic.
11. Bit Manipulation Patterns (5 Patterns)
Applied in optimization and binary arithmetic problems.
12. Linked List Patterns (5 Patterns)
Includes reversal, merging, and cycle detection problems.
13. Array & Matrix Patterns (8 Patterns)
Use Case: Handling multidimensional data, rotations, and prefix operations.
14. String Manipulation Patterns (7 Patterns)
Essential for problems involving text or symbol processing.
15. Design Patterns (Meta Category)
Applied in designing scalable and efficient systems.
How to Practice Effectively on Thita.ai
Knowledge without practice falls short — Thita.ai helps bridge that gap with interactive learning.
Start) by reviewing the official 90 DSA pattern sheet on Thita.ai.
Step 2: Choose a Pattern ? Pick one like “Sliding Window – Variable Size.”
Let Thita.ai guide Product Management roadmap your problem-solving with intelligent assistance and complexity insights.
Track your improvement and focus on weak areas using detailed reports.
The Smart Way to Prepare
Most candidates waste effort on random problem-solving instead of structured pattern recognition.
Pattern-based learning through Thita.ai ensures faster growth and higher recall.
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.