Mile
Zero

I spend a lot of time at work straddling four programming languages: PHP, SQL, JavaScript, and ActionScript. Many of our projects use at least three of these, if not all four. Yet while there's certainly some degree of domain-specific knowledge in each, there's more technique shared between them, floating off in the indefinite space of "software engineering."

Granted, I didn't study computer science in college. I had done some programming before and didn't really want anything to do with it professionally--I wanted to work for the Travel Channel! So when I fell into doing data journalism for CQ, a job that's halfway between storytelling and interactive coding, I knew there were skills where I was probably behind. And now that I feel like I'm relatively up to speed on the languages themselves, I want to catch back up on some of what I missed, starting with various low-level data structures.

The result is Typedefs, a simple blog where, in each entry, I pick an item from Wikipedia's list of data structures, implement it in JavaScript, and then explain how I did it and provide a quick demonstration. So far, I've done linked lists (the old classic), AA trees, and heaps. Next I want to try a chunk-based file, like PNG, and also a trie or bloom filter for text lookup.

I can already tell that working through these examples has been good for me--not because I expect to implement a lot of AA trees, because in my experience that's pretty rare, but because building these structures gives me a better understanding of how languages actually work, and a wider range of algorithms for solving other problems. The mechanics of a heap, for example, define a set of interesting ways to use arrays for storage and processing. AA trees really force you to examine the implications of pass-by-reference and pass-by-value. Linked lists are always a good experiment in miniature API design. As bite-sized, highly-technical exercises, they give me a chance to stretch my skills without having to build a full-sized JavaScript application.

These posts are also intended to leverage a truism: that the best way to learn is to teach someone else. By writing the blog as a teaching tool for other people, it forces me to organize my thoughts into a logical, coherent narrative: what are the foundations of this structure? What's it actually doing during this algorithm? Why is this useful? When the goal is to educate, I can't just get away with refactoring someone else's example. I need to know how and why it's built that way--and that knowledge is probably more useful than the example itself.