Algo analysis

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CSC-391. Data Structure and Algorithm course material

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Algo analysis

  1. 1. CSC 391
  2. 2. Polynomials in running time Desirable scaling property. When the input size doubles, the algorithm should only slow down by some constant factor C. We say that an algorithm is efficient if has a polynomial running time.
  3. 3. Cost of basic operations Observation. Most primitive operations take constant time
  4. 4. Factors affecting running time
  5. 5. ** The difference between Big O notation and Big Omega notation is that Big O is used to describe the worst case running time for an algorithm. But, Big Omega notation, on the other hand, is used to describe the best case running time for a given algorithm.
  6. 6. Big-Theta notation

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