The Ninety DSA Patterns That Cover Almost All Coding Interviews
You’ve spent hours grinding LeetCode problems — yet still find yourself freezing during live interviews?
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.
By learning 90 carefully chosen DSA patterns, you’ll unlock solutions to 99% of interview problems instantly.
What You’ll Learn
You’ll explore 15 foundational categories containing 90 powerful coding patterns.
On Thita.ai, you can experience pattern-based learning with interactive guidance and feedback.
Why Random LeetCode Grinding Doesn’t Work
Without pattern-based learning, random LeetCode practice fails to build adaptability.
Each DSA pattern functions as a reusable design you can apply to multiple situations.
Sample applications:
– Target sum in sorted list ? Two Pointer technique
– Substring without duplicates ? Sliding Window
– Cycle detection ? Slow & Fast Pointers.
Success in interviews comes from recognizing underlying DSA themes, not recalling exact problems.
The 15 Core DSA Pattern Families
These pattern families cover the foundational structures behind most coding interview challenges.
1. Two Pointer Patterns (7 Patterns)
Ideal for array manipulation and pointer-based optimization problems.
Examples: Converging pointers, expanding from center, and two-pointer string comparison.
? Pro Tip: Check if the data is sorted or relationships exist between index pairs.
2. Sliding Window Patterns (4 Patterns)
Use Case: Optimize subarray or substring challenges dynamically.
Focuses on dynamically resizing sequences to meet constraints.
? Insight: Timing your window adjustments correctly boosts performance.
3. Tree Traversal Patterns (7 Patterns)
Used for recursive and iterative traversals across hierarchical structures.
4. Graph Traversal Patterns (8 Patterns)
Use Case: Connectivity, pathfinding, and topology analysis.
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)
Use Case: Recursive search and learn Data science AI exhaustive solution exploration.
8. Greedy Patterns (6 Patterns)
Great for problems solvable with stepwise optimization.
9. Binary Search Patterns (5 Patterns)
Used in range partitioning and target detection.
10. Stack Patterns (6 Patterns)
Use Case: LIFO operations, expression parsing, and monotonic stacks.
11. Bit Manipulation Patterns (5 Patterns)
Crucial for low-level data operations.
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)
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
The real edge lies in applying these patterns effectively through guided AI coaching.
Access the DSA 90 framework sheet to visualize all pattern families.
Step 2: Choose a Pattern ? Pick one like “Sliding Window – Variable Size.”
Solve questions while the AI gives contextual hints, code feedback, and performance tips.
Step 4: Track Progress ? Analyze performance and identify weak zones.
The Smart Way to Prepare
Stop random practice; focus on mastering logic templates instead.
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.