Indicators on AI interviews You Should Know
The Comprehensive Set of 90 DSA Patterns That Cover Almost All Coding Interviews
Many candidates solve 200+ LeetCode challenges but still blank out during actual technical rounds.
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.
Understanding these 90 DSA blueprints equips you to decode almost any interview challenge with ease.
What You’ll Learn
Inside this guide, we organize 90 DSA templates into 15 essential families used by elite programmers.
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.
Patterns act like reusable schematics that instantly reveal how to solve new problems.
Sample applications:
– Target sum in sorted list ? Two Pointer technique
– Substring without duplicates ? Sliding Window
– Cycle detection ? Slow & Fast Pointers.
Those who excel identify the pattern first and adapt instantly.
The 15 Core DSA Pattern Families
Each category groups related concepts that repeatedly surface in coding interviews.
1. Two Pointer Patterns (7 Patterns)
Used for efficient array/string navigation and pair-based operations.
Examples: Converging pointers, expanding from center, and two-pointer string comparison.
? Quick Insight: Two-pointer works best when the array is sorted or positional relationships exist.
2. Sliding Window Patterns (4 Patterns)
Applicable when analyzing contiguous sequences in data.
Common templates: expanding/shrinking windows and character frequency control.
? Tip: Efficiency lies in the ability to manage window size dynamically.
3. Tree Traversal Patterns (7 Patterns)
Encompasses standard and advanced traversal techniques like LCA and serialization.
4. Graph Traversal Patterns (8 Patterns)
Focuses on efficient exploration and connection validation in networks.
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.
10. Stack Patterns (6 Patterns)
Use Case: LIFO operations, expression parsing, and monotonic stacks.
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)
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, Mock interviews and refine through intelligent feedback.
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.