The Essential Ninety 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.
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.
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.
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.
Those who excel identify the pattern first and adapt instantly.
The 15 Core DSA Pattern Families
Every pattern family addresses specific classes of problems that recur across companies.
1. Two Pointer Patterns (7 Patterns)
Ideal for array manipulation and pointer-based optimization problems.
Core templates: Converging, Slow/Fast, Expansion, and In-place transformations.
? Pro Tip: Check if the data is sorted or relationships exist between index pairs.
2. Sliding Window Patterns (4 Patterns)
Used to handle range-based optimizations in arrays and strings.
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)
Use Case: Optimization with overlapping subproblems and state transitions.
6. Heap (Priority Queue) Patterns (4 Patterns)
Use Case: Ranking, median finding, and scheduling challenges.
7. Backtracking Patterns (7 Patterns)
Use Case: Recursive search and exhaustive solution exploration.
8. Greedy Patterns (6 Patterns)
Use Case: Achieving global optima through local choices.
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)
Use Case: XOR-based logic, bit counting, and power checks.
12. Linked List Patterns (5 Patterns)
Use Case: Efficient pointer-based data manipulation.
13. Array & Matrix Patterns (8 Patterns)
Focuses on efficient iteration over structured grids.
14. String Manipulation Patterns (7 Patterns)
Essential for problems involving text or symbol processing.
15. Design Patterns (Meta Category)
Represents higher-order algorithmic design and data structure construction.
How to Practice Effectively on Thita.ai
Knowledge without practice falls short — Thita.ai helps bridge that gap with interactive learning.
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?
Thita.ai helps you achieve interview mastery by offering:
– Comprehensive 90 DSA pattern training
– Real-time AI insights
– Mock DSA roadmap interview simulations
– Tailored progress analytics
– Structured growth tracking.