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?
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.
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
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.
Top performers in FAANG interviews don’t memorize — they recognize recurring logic patterns.
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)
Applied in problems where two indices move strategically across data structures.
Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.
? Pro Tip: Check if the data is sorted or relationships exist between index pairs.
2. Sliding Window Patterns (4 Patterns)
Best for problems requiring flexible range adjustments.
Examples include fixed or variable windows, character tracking, and monotonic operations.
? Mock interviews Tip: Efficiency lies in the ability to manage window size dynamically.
3. Tree Traversal Patterns (7 Patterns)
Used for recursive and iterative traversals across hierarchical structures.
4. Graph Traversal Patterns (8 Patterns)
Focuses on efficient exploration and connection validation in networks.
5. Dynamic Programming Patterns (11 Patterns)
Covers problems like Knapsack, LIS, Edit Distance, and Interval DP.
6. Heap (Priority Queue) Patterns (4 Patterns)
Helps in scheduling and optimization tasks.
7. Backtracking Patterns (7 Patterns)
Use Case: Recursive search and exhaustive solution exploration.
8. Greedy Patterns (6 Patterns)
Relies on sorted order or prioritization strategies.
9. Binary Search Patterns (5 Patterns)
Core to logarithmic time optimizations.
10. Stack Patterns (6 Patterns)
Use Case: LIFO operations, expression parsing, and monotonic stacks.
11. Bit Manipulation Patterns (5 Patterns)
Applied in optimization and binary arithmetic problems.
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.
Select your pattern of choice and begin interactive exploration.
Step 3: Solve with AI Coaching ? Receive real-time hints, feedback, and explanations.
Step 4: Track Progress ? Analyze performance and identify weak zones.
The Smart Way to Prepare
Most candidates waste effort on random problem-solving instead of structured pattern recognition.
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.