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Big O Notation Algorithms explained

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  • Course
  • Introduction to Programming 1
  • Institution
  • Goldsmiths, University Of London (GUL)
  • Book
  • Data Structures and Algorithms in Java

A written short study into Big O Notation. How the algorithm determines how long an algorithm takes to execute- As well as enabling software engineers to determine how efficient different approaches to solving computational problems are.

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Document information

  • November 5, 2021
  • 3
  • 2021/2022
  • Class notes
  • Matthew lee king
  • All classes

Subjects

  • algorithms
  • software engineering
  • data structures
  • programming
  • cryptography
  • software development
  • software engineer
  • computer science

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Algorithms 1 - BSc Computer Science (Semester 1) - Goldsmith, University of London




Big O Notations is a way to represent how long an algorithm will take to execute. It is used to
enable a Software Engineer to determine how efficient different approaches to solving
problems are. There are 4 main common types of time complexities in Big O Notation: -




● O(1) - Constant time complexity
● O (n) - Linear time complexity
● O(log n) - Logarithmic time complexity
● O(n ^ 2) - Quadratic time complexity

O(1) CONSTANT TIME COMPLEXITY:

Constant time algorithms will always take the same amount of time to be executed. The
execution time of these algorithms is independent of the size of the input. A effective
example of O(1) time is accessing a value with an array index.
E.g Push() or pop() operations on an array.

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