Grokking Algorithm Complexity and Big-O
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Big-Omega Notation (Ω-notation)
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Big-Omega Notation (Ω-notation) is used to describe the lower bound of an algorithm's growth rate. It provides a way to express the best-case scenario for how an algorithm performs as the input size increases.

  • Purpose: It tells us the minimum amount of time or space required by an algorithm, even in the best-case scenario.
  • Usefulness: While Big-O notation gives an upper bound (worst-case), Ω-notation helps understand the least amount of resources an algorithm will always need.

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