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The Comprehensive Set of 90 DSA Patterns That Cover Almost All Coding Interviews
Many candidates solve 200+ LeetCode challenges but still blank out during actual technical rounds.
Here’s the secret: most coding interviews don’t test unique problems — they reuse established logical templates.
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
You’ll explore 15 foundational categories containing 90 powerful coding patterns.
You’ll also discover how to practice these patterns interactively with AI feedback using 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.
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.
Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.
? Hint: Look for sorted input or pairwise relationships between indices.
2. Sliding Window Patterns (4 Patterns)
Used to handle range-based optimizations in arrays and strings.
Key Patterns: Fixed-size 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)
Applied in DFS, BFS, shortest paths, and union-find logic.
5. Dynamic Programming Patterns (11 Patterns)
Use Case: Optimization with overlapping subproblems and state transitions.
6. Heap (Priority Queue) Patterns (4 Patterns)
Used for stream processing and efficient order maintenance.
7. Backtracking Patterns (7 Patterns)
Includes subsets, permutations, N-Queens, Sudoku, and combination problems.
8. Greedy Patterns (6 Patterns)
Great for problems solvable with stepwise optimization.
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)
Crucial for low-level data operations.
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)
Essential for problems involving text or symbol processing.
15. Design Patterns (Meta Category)
Use Case: Data structure and system design logic.
How to Practice Effectively on Thita.ai
Understanding these 90 templates is Product Management roadmap the first step; applying them strategically ensures interview success.
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
Traditional grinding wastes time — pattern-based learning delivers results.
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.