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.
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.
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.
Success in interviews comes from recognizing underlying DSA themes, not recalling exact problems.
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.
Key Patterns: Converging pointers, Fast & Slow pointers, Fixed separation, In-place modification, Expand from center, String reversal, and Backspace comparison.
? 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.
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)
Focuses on efficient exploration and connection validation in networks.
5. Dynamic Programming Patterns (11 Patterns)
Central to solving resource allocation and sequence-based problems efficiently.
6. Heap (Priority Queue) Patterns (4 Patterns)
Used for stream processing and efficient order maintenance.
7. Backtracking Patterns (7 Patterns)
DSA 90 patterns sheetRelies on decision trees and pruning to find valid outcomes.
8. Greedy Patterns (6 Patterns)
Relies on sorted order or prioritization strategies.
9. Binary Search Patterns (5 Patterns)
Applied in finding thresholds, boundaries, or minimum feasible values.
10. Stack Patterns (6 Patterns)
Involves handling nested structures and validation problems.
11. Bit Manipulation Patterns (5 Patterns)
Use Case: XOR-based logic, bit counting, and power checks.
12. Linked List Patterns (5 Patterns)
Common in list-based storage and cache designs.
13. Array & Matrix Patterns (8 Patterns)
Focuses on efficient iteration over structured grids.
14. String Manipulation Patterns (7 Patterns)
Includes palindrome checking, encoding/decoding, and pattern validation.
15. Design Patterns (Meta Category)
Includes LRU Cache, LFU Cache, Min Stack, Trie, and Design Twitter.
How to Practice Effectively on Thita.ai
Learning the 90 DSA patterns is only the beginning — mastering their application is the key.
Begin by opening the full Thita.ai DSA pattern catalog.
Choose one category (e.g., Sliding Window) to practice related LeetCode-style problems.
Engage Thita.ai’s AI tutor for instant suggestions and solution breakdowns.
Step 4: Track Progress ? Analyze performance and identify weak zones.
The Smart Way to Prepare
Success in coding interviews is built on pattern familiarity, not repetition.
With Thita.ai, you’ll follow a structured, AI-enhanced learning journey.
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.