CST 370 - Module 1

 Week 1,

This course is known as "Design and Analysis of Algorithms". As you can guess, this class will cover material about algorithms and how or when to implement them.

The first week serves as more of a refresher on what we may have learned over the course of starting our computer science journey. Some of the refreshers include the basic yet fundamental data structures such as arrays, linked lists, stacks, queues, etc. Others include important problem types that can be solved by algorithms. There can be sorting problems which require algorithms to organize items in a given list, which in turn can benefit searching problems which algorithms would be used to find specific items in a list. There are graph problems which can vary depending on the goal. For example, one graph problem would be the traveling salesman problem (TSP) which, in short, requires us to find the shortest possible route through different and interconnected nodes once. There are other problem types, such as geometric, combinatorial, and numerical problems, however I will keep this brief and stop there.

Aside from the review of important aspects to algorithms, we also get into an introduction to algorithm analysis. First and foremost, there are generally two efficiencies discussed in this introduction. One being time efficiency (time complexity), which indicates how fast an algorithm runs. The other, space efficiency (space complexity) refers to the amount of memory units are required by the algorithm and space needed for its input and output. For now, our focus is on time complexity. There are different categories of time complexity "orders of growth" which acts as the main analysis of algorithms. There is much more to go over, however, this is already turning into a long post so I will leave the rest for future students to figure out when taking this class.

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