Big O Complexity of Common Data Structures
Flashcards on Big O time and space complexity for core data structures — essential for coding interviews at top tech companies and university algorithms exams. Understanding why arrays offer O(1) access while linked lists require O(n) traversal helps you choose the right structure and predict performance under load.
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5 CardsBinary search tree complexities
Stack and queue time complexities
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Why does array access take O(1)?
Arrays store elements in contiguous memory. Given a base address and index, the CPU computes the exact memory address in one step (
base + index × element_size), regardless of array size.What is the difference between O(1) and O(log n)?
O(1) means constant time — performance doesn't change with input size (e.g., hash table lookup). O(log n) means time grows logarithmically — doubling input only adds one step (e.g., binary search). Both are highly efficient in practice.
Which data structure has the best all-around complexity?
Hash tables offer O(1) average for insert, delete, and search — making them the most efficient general-purpose structure. However, they don't maintain order. Balanced BSTs are preferred when sorted traversal or range queries are needed.