Despite the increasing availability of alternative options such as online learning sites and coding boot camps, many students who are interested in programming still pick the traditional approach: getting a Computer Science degree. If you plan to do academic research, a degree is really the only option. But for someone who wants to get a job as a programmer, there are both advantages and disadvantages to a traditional degree.
Archives for March 2015
When you start solving programming puzzles like those on uHunt Chapter 1, what are you learning about? The obvious answer is that you’re learning about competitive programming. After all, uHunt has a companion textbook called Competitive Programming, and many programming puzzle sites are associated with the competitive programming community, or even run their own contests. But I don’t think that’s the right way to look at it. First of all, there’s not much competition happening when you’re first getting started. You may be using a site where the only rating is the number of problems submitted. Or if you are participating in real-time contests, you may not be making it through many problems before time runs out.
If you want to get better at programming, you need to get better at algorithms. In some ways, that statement is tautological. To quote Computer Science pioneer Niklaus Wirth, Algorithms + Data Structures = Programs. But besides the algorithms that you write yourself, it’s also worth studying well-known algorithms such as those taught in introductory Computer Science classes. Some software developers object to that idea. They say their language or framework already provides all of the standard algorithms, or that they can easily find them on the Web. Why do they need to learn how they’re implemented? It’s certainly true that professional software engineers shouldn’t re-implement standard algorithms for the purpose of using them in a product. But that’s not the point of learning them. The reason they’re part of CS education is that they contain useful ideas. Here’s one example: In modern programming languages, you don’t have to worry about finding the end of a string. The language hides that aspect of string implementation. But by studying string manipulation algorithms in C, you find out about the idea of a sentinel value. This is helpful in understanding how leaf nodes are represented in a tree. And now you have a couple of examples of a concept you can use in other situations where you need to indicate the end of a section of data.
If you want to get a lot better at a skill, you need a process for practicing it. When you follow a process, it encourages you to practice in a consistent way, rather than using whatever practice technique you happen to feel like using on a given day. As you get experience using your process, you can look for ways to improve it. In fact, improving your process should be a step in your process, since improvements makes your practice more effective every time you use the process. In this way, you can set up a virtuous cycle where your practice helps you improve your process, which in turn improves your practice. Here on Red-Green-Code, I’m working on a process for getting better at programming.