Comment by WhitneyLand
3 days ago
Your comment about memorizing as part of understanding makes a lot of sense to me, especially as one possible technique to get get unstuck in grasping a concept.
If it doesn’t work for you on l33t code problems, what techniques are you finding more effective in that case?
I was part of an ACM programming team in college. We would review classes of problems based on the type of solution necessary, and learn those techniques for solving them. We were permitted a notebook, and ours was full of the general outline of each of these classes and techniques. Along with specific examples of the more common algorithms we might encounter.
As a concrete example, there is a class of problems that are well served by dynamic programming. So we would review specific examples like Dijkstra's algorithm for shortest path. Or Wagner–Fischer algorithm for Levenshtein-style string editing. But we would also learn, often via these concrete examples, of how to classify and structure a problem into a dynamic programming solution.
I have no idea if this is what is meant by "l33t code solutions", but I thought it would be a helpful response anyway. But the bottom line is that these are not common in industry, because hard computer science is not necessary for typical business problems. The same way you don't require material sciences advancements to build a typical house. Instead it flows the other way, where advancements in materials sciences will trickle down to changing what the typical house build looks like.
>If it doesn’t work for you on l33t code problems, what techniques are you finding more effective in that case?
Memorization of l33t code DOES work well as prep for l33t code tests. I just don't think l33t code has much to do with application programming. I've long felt that "computer science" is physics for computers, low on the abstraction ladder, and there are missing labels for the higher complexity subjects built on it. Imagine if all physical sciences were called "physics" and so in order to get a job as a biologist you should expect to be asked questions about the Schroedinger equation and the standard model. We desperately need "application engineering" to be a distinct subject taught at the university level.
You mean like to Software Engineering?
That's a real major that's been around for a couple of decades which focuses on software development (testing, version control, design patterns) with less focus on the more theoretical parts of computer science? There are even specialties within the Software Engineering major that focus specifically on databases or embedded systems.
What I understand from the GP is that memorizing l33t code won't help you learn anything useful. Not that understanding the solutions won't help you memorize them.