The Comprehensive Set of 90 DSA Patterns That Cover Almost 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.
Understanding these 90 DSA blueprints equips you to decode almost any interview challenge with ease.
What You’ll Learn
This comprehensive guide breaks down 90 DSA patterns grouped into 15 core categories.
On Thita.ai, you can experience pattern-based learning with interactive guidance and feedback.
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
Each category groups related concepts that repeatedly surface in coding interviews.
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 mock coding interview platform 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)
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)
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)
Used for detecting duplicates, toggling bits, and subset enumeration.
12. Linked List Patterns (5 Patterns)
Focuses on optimizing node traversal 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
Traditional grinding wastes time — pattern-based learning delivers results.
Thita.ai provides the smartest route — combining AI guidance with proven DSA frameworks.
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.