Learning Outcomes
At the end of this lecture, you’ll be able to:
- Understand and appreciate why we do asymptotic analysis using Big Oh notation.
- Use Big Oh notation to describe asymptotic running time of a program when you are given the program code or its precise running time as a function of input size.
- Use Big Oh notation to describe the asymptotic running time of the operations of the data structures we have implemented so far.
- Understand Big Oh (asymptotic) notation groups functions into a set of classes.
- Enumerate common running time functions when the runtime is described in asymptotic (Big Oh) notation.
- Determine the asymptotic growth rates of a given function using Big Oh notation.
- Rank asymptotic complexities from smallest to largest.
Lecture Plan
In this lecture, we'll cover the following lessons:
- Asymptotic Analysis: Recap
- Asymptotic Analysis: Big Oh Notation
- Big Oh Notation: The Gist!
- Big Oh Notation: Exercise⚡
- Asymptotic Runtime: Example I⚡
- Asymptotic Runtime: Example II⚡
- Asymptotic Runtime: Example III⚡
- Asymptotic Runtime: Example IV⚡
- Asymptotic Runtime: Example V⚡
- Asymptotic Runtime: Example VI⚡
- Asymptotic Runtime: Example VII⚡
- Asymptotic Runtime: Example IIX⚡
- Asymptotic Runtime: Example IX⚡
- Asymptotic Runtime: Classes of runtime functions
- Asymptotic Order of Growth: Example⚡
- Asymptotic Order of Growth: Common Running Times⚡
- Asymptotic Order of Growth: Exercise I⚡
- Asymptotic Order of Growth: Exercise II⚡
Lessons marked with ⚡ contain exercise/activity.