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?
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
This comprehensive guide breaks down 90 DSA patterns grouped into 15 core categories.
Learn how to train smarter through real-time AI-assisted exercises on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Blindly solving hundreds of questions rarely helps you identify underlying algorithmic blueprints.
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.
Those who excel identify the pattern first and adapt instantly.
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)
Use Case: Fast array or string traversal through pointer logic.
Examples: Converging pointers, expanding from center, and two-pointer string comparison.
? Hint: Look for sorted input or pairwise relationships between indices.
2. Sliding Window Patterns (4 Patterns)
Applicable when analyzing contiguous sequences in data.
Common templates: expanding/shrinking windows and character frequency control.
? Insight: Timing your window adjustments correctly boosts performance.
3. Tree Traversal Patterns (7 Patterns)
Applicable in computing paths, depths, and relationships within trees.
4. Graph Traversal Patterns (8 Patterns)
Includes Dijkstra, Bellman-Ford, and disjoint set operations.
5. Dynamic Programming Patterns (11 Patterns)
Covers problems like Knapsack, LIS, Edit Distance, and Interval DP.
6. Heap (Priority Queue) Patterns (4 Patterns)
Ideal for top-K computations and real-time priority adjustments.
7. Backtracking Patterns (7 Patterns)
Includes subsets, permutations, N-Queens, Sudoku, and combination problems.
8. Greedy Patterns (6 Patterns)
Use Case: Achieving global optima through local choices.
9. Binary Search Patterns (5 Patterns)
Use Case: Efficient searching over sorted data or answer ranges.
10. Stack Patterns (6 Patterns)
Enables structured data management through stack logic.
11. Bit Manipulation Patterns (5 Patterns)
Crucial for low-level data operations.
12. Linked List Patterns (5 Patterns)
Focuses on optimizing node traversal DSA roadmap and transformation.
13. Array & Matrix Patterns (8 Patterns)
Covers spiral traversals, rotations, and prefix/suffix computations.
14. String Manipulation Patterns (7 Patterns)
Use Case: Parsing, validation, and frequency analysis in strings.
15. Design Patterns (Meta Category)
Represents higher-order algorithmic design and data structure construction.
How to Practice Effectively on Thita.ai
The real edge lies in applying these patterns effectively through guided AI coaching.
Access the DSA 90 framework sheet to visualize all pattern families.
Next, select any pattern and explore associated real-world problems.
Step 3: Solve with AI Coaching ? Receive real-time hints, feedback, and explanations.
Track your improvement and focus on weak areas using detailed reports.
The Smart Way to Prepare
Stop random practice; focus on mastering logic templates instead.
Use Thita.ai’s roadmap to learn, practice, and refine through intelligent feedback.
Why Choose Thita.ai?
Thita.ai empowers learners to:
– Master 90 reusable DSA patterns
– Practice interactively with AI feedback
– Experience realistic mock interviews
– Prepare for FAANG and top-tier interviews
– Build a personalized, AI-guided learning path.