The 90 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.
Major companies prefer problem templates that measure reasoning, not rote memory.
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.
Learn how to train smarter through real-time AI-assisted exercises on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Random problem-solving builds quantity, not recognition — and interviews reward recognition.
Patterns act like reusable schematics that instantly reveal how to solve new problems.
Sample applications:
– Target sum in sorted list ? Two Pointer technique
– Substring without duplicates ? Sliding Window
– Cycle detection ? Slow & Fast Pointers.
Top performers in FAANG interviews don’t memorize — they recognize recurring logic patterns.
The 15 Core DSA Pattern Families
Every pattern family addresses specific classes of problems that recur across companies.
1. Two Pointer Patterns (7 Patterns)
Ideal for array manipulation and pointer-based optimization problems.
Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.
? Quick Insight: Two-pointer works best when the array is sorted or positional relationships exist.
2. Sliding Window Patterns (4 Patterns)
Applicable when analyzing contiguous sequences in data.
Common templates: expanding/shrinking windows and character frequency control.
? Hint: Balance expansion and contraction logic to optimize results.
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)
Focuses on efficient exploration and connection validation in networks.
5. Dynamic Programming Patterns (11 Patterns)
Emphasizes recursive breakdown and memoization.
6. Heap (Priority Queue) Patterns (4 Patterns)
Ideal for top-K computations and real-time priority adjustments.
7. Backtracking Patterns (7 Patterns)
Use Case: Recursive search and exhaustive solution exploration.
8. Greedy Patterns (6 Patterns)
Great for problems solvable with stepwise optimization.
9. Binary Search Patterns (5 Patterns)
Applied in finding thresholds, boundaries, or minimum feasible values.
10. Stack Patterns (6 Patterns)
Enables structured data management through stack AI resume analyzer logic.
11. Bit Manipulation Patterns (5 Patterns)
Applied in optimization and binary arithmetic problems.
12. Linked List Patterns (5 Patterns)
Use Case: Efficient pointer-based data manipulation.
13. Array & Matrix Patterns (8 Patterns)
Applied in image processing, pathfinding, and transformation tasks.
14. String Manipulation Patterns (7 Patterns)
Use Case: Parsing, validation, and frequency analysis in strings.
15. Design Patterns (Meta Category)
Applied in designing scalable and efficient systems.
How to Practice Effectively on Thita.ai
Learning the 90 DSA patterns is only the beginning — mastering their application is the key.
Access the DSA 90 framework sheet to visualize all pattern families.
Select your pattern of choice and begin interactive exploration.
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
Most candidates waste effort on random problem-solving instead of structured pattern recognition.
Use Thita.ai’s roadmap to learn, practice, and refine through intelligent feedback.
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.