For this discussion, Read the following paragraphs. then go to the two websites and read about complexity Analysis.

In computer science, the analysis of algorithms is the determination of the amount of resources (such as time and storage) necessary to execute them. Most algorithms are designed to work with inputs of arbitrary length. Usually, the efficiency or running time of an algorithm is stated as a function relating the input length to the number of steps (time complexity) or storage locations (space complexity).

Algorithm analysis is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem. These estimates provide an insight into reasonable directions of search for efficient algorithms.

In theoretical analysis of algorithms it is common to estimate their complexity in the asymptotic sense, i.e., to estimate the complexity function for arbitrarily large input. Big O notation, Big-omega notation and Big-theta notation are used to this end. For instance, binary search is said to run in a number of steps proportional to the logarithm of the length of the list being searched, or in O(log(n)), colloquially "in logarithmic time". Usually asymptotic estimates are used because different implementations of the same algorithm may differ in efficiency. However the efficiencies of any two "reasonable" implementations of a given algorithm are related by a constant multiplicative factor called a hidden constant.

http://www.cs.utexas.edu/users/djimenez/utsa/cs1723/lecture2.html ( Read through Selection sort)

http://discrete.gr/complexity/ Read to Counting Instructions)

Write a summary paragraph or two and explain what is meant by Complexity Analysis. Then discuss if you think this is a useful tool for writing code? Is it useful in the overall study of Computer Science. Should we study this more in this course or another course in the SDEV program? After you have made your post, reply to two other student's post.