Introduction
Description
This chapter introduces Big-O runtimes, a standard metric for analyzing the efficiency of algorithms that is independent of the hardware used to implement the algorithm. Big-O allows for a meaningful comparison between different implementations of a particular algorithm.
Learning Objectives
- Determine basic space/time requirements of algorithms (Big O) and evaluate trade-offs in algorithm selection for a variety of problems
- Understand basic algorithm analysis
By the end of this chapter, you should be able to answer the following questions:
– How is Big O used to compare algorithms?
– What does Big O measure?
– What are the six standard runtimes?
definition
An algorithm is an explicit sequence of instructions, performed on data, to accomplish a desired objective.
