The Comprehensive Set of 90 DSA Patterns That Cover Virtually All Coding Interviews
You might have solved over 200 LeetCode questions, yet your confidence drops the moment the interview starts.
Most companies reuse recurring data structure and algorithm (DSA) templates to evaluate problem-solving skills.
Tech giants like Google, Meta, Amazon, and Microsoft repeatedly test the same core ideas.
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.
You’ll be guided on how to practice these patterns dynamically through AI-driven hints and feedback on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Solving problems at random doesn’t build intuition for recurring logic patterns.
Once recognized, a pattern turns complex problems into familiar exercises.
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.
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)
Used for efficient array/string navigation and pair-based operations.
Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.
? Tip: Sorted inputs often signal a two-pointer approach.
2. Sliding Window Patterns (4 Patterns)
Use Case: Optimize subarray or substring challenges dynamically.
Key Patterns: Fixed-size window, Variable-size window, Monotonic queue, Character frequency matching.
? Hint: Balance expansion and contraction logic to optimize results.
3. Tree Traversal Patterns (7 Patterns)
Used for recursive and iterative traversals across hierarchical structures.
4. Graph Traversal Patterns (8 Patterns)
Applied in DFS, BFS, shortest paths, and union-find logic.
5. Dynamic Programming Patterns (11 Patterns)
Emphasizes recursive breakdown and memoization.
6. Heap (Priority Queue) Patterns (4 Patterns)
Used for stream processing and efficient order maintenance.
7. Backtracking Patterns (7 Patterns)
Relies 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)
Applied in optimization and binary arithmetic problems.
12. Linked List Patterns (5 Patterns)
Includes reversal, merging, and cycle detection problems.
13. Array & Matrix Patterns (8 Patterns)
Use Case: Handling multidimensional data, rotations, and prefix operations.
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.
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?
AI resume analyzerThita.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.