On the quality and complexity of software within FRC

[gblake]

Originally Posted by GeeTwo

I hadn't either until a few months ago, and I minored in computer science (1984). Back then, we just called it "order of magnitude". It tells you how resources required by a process (usually time) scales as the amount of data being handled increases. For example, a bubble sort is of order n² where n is the number of items being sorted, so "n²" is the "big O" for the bubble sort, starting from an unsorted data set.

Yeah...

For those who haven't noticed or cared (and... it's legitimate to be proud of not needing to notice or care ), I have noticed that the buzzworthiness of knowing and discussing the big O characteristics of various data structures and algorithms for various operations (insert, sort, etc.) has been on the rise for a while because of the money to be made in big data (business analytics, online shopping, social networking, searching, databases in clouds, intelligence/spying, etc. etc.), and it's now quite trendy.

It's become so trendy that I worry that folks are losing sight of the differences between efficiently operating on small datasets and efficiently operating on large datasets. For small datasets, low-overhead brute force will often beat the pants off of manipulating some fancy data structure that is appropriate for larger datasets. There is more to writing efficient code than learning the big O characteristics of various data structures and algorithms.

FRC has opportunities to for programmers to experience both sides of this fence.