Big O Notation | Asymptotic Notation | GATECSE | DAA

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This video explores Big O notation, a fundamental tool for computer scientists and software engineers to analyze the cost of algorithms. It describes the upper bound of complexity, stating that f(n) is O(g(n)) iff for some constants c and N₀, f(n) less than or equal to cg(n) for all n is greater than or equal to n₀. Big O is used for asymptotic upper bounds, as it bounds the growth of the running time from above for large enough input sizes.
Big O notation measures how software program's running time or space requirements grow as the input size grows. It is a mathematical way to measure time complexity, considering only the fastest growing term and discarding other terms and constants. It is also used to measure space complexity. By understanding Big O notation and its applications, users can evaluate and discuss the performance of different solutions to the same problem.

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📚 Subject Wise Playlist 📚
▶️Data Structures: http://tinyurl.com/bwptf6f7
▶️Theory of Computation: http://tinyurl.com/5bhtzhtd
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