The Ninety DSA Patterns That Cover 99% Coding Interviews
You’ve spent hours grinding LeetCode problems — yet still find yourself freezing during live interviews?
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.
By learning 90 carefully chosen DSA patterns, you’ll unlock solutions to 99% of interview problems instantly.
What You’ll Learn
The guide maps all 90 DSA patterns into 15 logical families — the same framework elite engineers use to master FAANG interviews.
Learn how to train smarter through real-time AI-assisted exercises on Thita.ai.
Why Random LeetCode Grinding Doesn’t Work
Without pattern-based learning, random LeetCode practice fails to build adaptability.
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.
Top performers in FAANG interviews don’t memorize — they recognize recurring logic patterns.
The 15 Core DSA Pattern Families
Each category groups related concepts that repeatedly surface in coding interviews.
1. Two Pointer Patterns (7 Patterns)
Applied in problems where two indices move strategically across data structures.
Includes logic for in-place edits, fixed gaps, and center-based expansion techniques.
? Hint: Look for sorted input or pairwise relationships between indices.
2. Sliding Window Patterns (4 Patterns)
Best for problems requiring flexible range adjustments. System design interviews
Common templates: expanding/shrinking windows and character frequency control.
? Hint: Balance expansion and contraction logic to optimize results.
3. Tree Traversal Patterns (7 Patterns)
Encompasses standard and advanced traversal techniques like LCA and serialization.
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)
Used for stream processing and efficient order maintenance.
7. Backtracking Patterns (7 Patterns)
Includes subsets, permutations, N-Queens, Sudoku, and combination problems.
8. Greedy Patterns (6 Patterns)
Relies on sorted order or prioritization strategies.
9. Binary Search Patterns (5 Patterns)
Use Case: Efficient searching over sorted data or answer ranges.
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)
Focuses on optimizing node traversal and transformation.
13. Array & Matrix Patterns (8 Patterns)
Applied in image processing, pathfinding, and transformation tasks.
14. String Manipulation Patterns (7 Patterns)
Used for matching, substring searches, and string reconstruction.
15. Design Patterns (Meta Category)
Use Case: Data structure and system design logic.
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.
Get personalized progress tracking and adaptive recommendations.
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?
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.