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Follow this structured path to build comprehensive understanding of arrays, from low-level memory concepts to advanced problem-solving patterns.
Understand how arrays are stored in memory, cache locality, and performance implications of different access patterns.
Master insertion, deletion, traversal, and search operations with hands-on interactive examples.
Learn essential problem-solving patterns: two pointers, sliding window, prefix sum, and array rotation techniques.
Arrays store elements in contiguous memory, enabling O(1) random access and excellent cache performance.
Fast access vs. expensive insertions/deletions in the middle. Choose the right data structure for your use case.
Master two pointers, sliding window, and prefix sum patterns to solve 80% of array problems efficiently.
| Operation | Syntax | Time | Description |
|---|---|---|---|
| Access | arr[i] | O(1) | Direct index access |
| Insert (End) | arr.push(x) | O(1)* | Amortized constant time |
| Insert (Middle) | arr.insert(i, x) | O(n) | Shift elements right |
| Delete (End) | arr.pop() | O(1) | Remove last element |
| Delete (Middle) | arr.erase(i) | O(n) | Shift elements left |
| Search | find(arr, x) | O(n) | Linear search through array |
Start with memory fundamentals and work your way up to advanced algorithms. Interactive examples and real code implementations included.