The Ninety DSA Patterns That Cover 99% 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.
These organizations rely on pattern-based questions to assess how fast you adapt familiar logic to new contexts.
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.
On Thita.ai, you can experience pattern-based learning with interactive guidance and feedback.
Why Random LeetCode Grinding Doesn’t Work
Random problem-solving builds quantity, not recognition — and interviews reward recognition.
Each DSA pattern functions as a reusable design you can apply to multiple situations.
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.
Elite developers rely on pattern familiarity, not brute-force memorization.
The 15 Core DSA Pattern Families
These pattern families cover the foundational structures behind most coding interview challenges.
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 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)
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)
Common in interval scheduling, stock profits, and gas station routes.
9. Binary Search Patterns (5 Patterns)
Applied in finding thresholds, boundaries, or minimum feasible values. learn Data science AI
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)
Common in list-based storage and cache designs.
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
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.
Use Thita.ai’s roadmap to learn, practice, and refine through intelligent feedback.
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.