One Data Structure to Rule Computer Science
Graph-ically speaking
When I was in the undergraduate Computer Science (CS) program at Indiana University, I decided to stay on campus one summer, work part-time, and take a class. For some reason, I chose to take Data Structures then. Wow, that was a big mistake.
Not because data structures aren’t useful or worth studying. The exact opposite is true, and that was the issue. A college summer class lasts only about eight weeks. That is a lot of information to pack into a short time. I didn’t spend nearly enough time on the subject then as I should. Probably partied a bit too much also.
Data structures are some of the most useful knowledge you can gain from a CS program. It’s not often people write a compiler or implement a database, but any time application code is written, there is data to be dealt with in some shape or form. This requires software engineers to make decisions on what data structures best support the algorithms to be applied.
In a previous post, we deconstructed abstract data types and broke them down into their two fundamental types: contiguous (“array”) and non-contiguous (“graph”).
