A Practical Approach to Computer Algorithms Using Python® and C#
Rod Stephens started out as a mathematician, but while studying at MIT, he discovered how much fun algorithms are. He took every algorithms course MIT offered, and he has been writing complex algorithms ever since.
During his career, Rod has worked on an eclectic assortment of applica- tions in fields such as telephone switching, billing, repair dispatching, tax processing, wastewater treatment, concert ticket sales, cartography, and training for professional football players.
There are several reasons why you should study algorithms. First, they provide useful tools that you can use to solve particular problems such as sorting or finding shortest paths. Even if your programming language includes tools to perform tasks that are handled by an algorithm, it’s useful to learn how those tools work. For example, understanding how array and list sorting algorithms work may help you decide which of those data structures would work best in your programs.
Algorithms also teach you methods that you may be able to apply to other problems that have a similar structure. They give you a collection of techniques that you can apply to other problems. Techniques such as recursion, divide and conquer, Monte Carlo simulation, linked data structures, network traversal, and others apply to a wide variety of problems.
Perhaps most importantly, algorithms are like a workout for your brain. Just as weight training can help a football or baseball player build muscle, studying algorithms can build your problem-solving abilities. A professional athlete prob- ably won’t need to bench press weights during a game. Similarly, you probably won’t need to implement a simple sorting algorithm in your project. In both cases, however, practice can help improve your game, whether it’s baseball or programming.
Finally, algorithms can be interesting, satisfying, and sometimes surprising. It never ceases to amaze me when I dump a pile of data into a program and a realistic three-dimensional rendering pops out. Even after decades of study, I still feel the thrill of victory when a particularly complicated algorithm pro- duces the correct result. When all of the pieces fit together perfectly to solve an especially challenging problem, it feels like something at least is right in the world.