Coding Interview Preparation
Master data structures, algorithms, and problem-solving patterns essential for technical interviews at top companies.
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Coming Soon
This section is under development. Content will be added soon.
Expected topics:
- DSA Patterns (Sliding Window, Two Pointers, BFS/DFS)
- Dynamic Programming Patterns
- Graph Algorithms
- Tree and Binary Search Tree Problems
- LeetCode Solutions with Explanations
- Concurrency and Multithreading
- Language-Specific Idioms (Java, Go, Python)
Planned Categories
DSA Patterns
📋PlannedCore algorithmic patterns: sliding window, two pointers, BFS/DFS, and more.
ArraysTreesGraphsDP
LeetCode Solutions
📋PlannedCurated problem sets with detailed explanations and complexity analysis.
EasyMediumHardCompany Tags
Concurrency
📋PlannedMultithreading, locks, async patterns, and concurrent data structures.
ThreadsLocksAsync/AwaitRace Conditions
Language Specific
📋PlannedJava, Go, Python idioms and best practices for coding interviews.
Java StreamsGo ConcurrencyPython Collections
Problem-Solving Framework
When approaching coding problems:
- Understand – Clarify inputs, outputs, constraints, edge cases
- Plan – Think of approach before coding, consider time/space
- Implement – Write clean, readable code
- Test – Walk through examples, verify edge cases
- Optimize – Can you improve time or space complexity?
Time Complexity Cheat Sheet
| Complexity | Example Operations |
|---|---|
| O(1) | Hash table lookup, array access |
| O(log n) | Binary search |
| O(n) | Linear search, single loop |
| O(n log n) | Efficient sorting (merge, quick) |
| O(n²) | Nested loops, bubble sort |
| O(2ⁿ) | Recursive subsets |
| O(n!) | Permutations |
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