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Time Complexity

/taɪm kəmˈplɛksəti/noun
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Time complexity is a fundamental concept in computer science that measures how the running time of an algorithm increases with the size of its input, typically expressed using Big O notation to predict performance on large datasets. It helps developers choose efficient algorithms for real-world applications, such as optimizing search functions in social media platforms where even small inefficiencies can lead to noticeable delays with millions of users.

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The study of time complexity is central to the unsolved P vs NP problem, which questions whether every problem whose solution can be verified quickly can also be solved quickly; this enigma has a $1 million prize from the Clay Mathematics Institute and has influenced fields from cryptography to AI for over 50 years.

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WikipediaGeeksforGeeksIntroduction to Algorithms by Cormen et al.ACM Digital Library

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