Previous Lecture | lect10 | Next Lecture |
Code written in class
https://github.com/ucsb-cs24-s19-mirza/cs24-s19-lectures/tree/master/lec-10
Topics
- Challenges in measuring time efficiency and the pros/cons of different methods - absolute time, counting steps
- Measuring the impact of algorithms on running time (independent of implementation details/hardware/compiler….etc) - Count steps by detailed computer model of times to fetch, store, assign …
- O notation - Big Oh - asymptotic analysis and orders of growth, but also briefly Little O, Big Omega, Big Theta
- Formal Big O - formula and graphical presentation
- Complexity classes - constant, logarithmic, exponential, linear, quadratic, cubic
- Best case, worst case, average case
- Example algorithms