Wednesday, September 2, 2009

What *IS* software anyway?

White Bass

Goofy question? Not really. Have you ever thought about what software is? Is it just 1's and 0's? Is it just the field where you are paid to toil away in? Is it a product to bring your company wealth and fame? Is it tool there to help others do their jobs, whatever they may be? Understanding that can really have an impact on what we create, how we go about creating it and how usable it is after we deliver it.

One of the valuable resources I've found out on the vastness of the web is the Software Process and Measurement Cast. Despite the unfortunate acronym chosen (SPaMCast? Really? How many people are going to click on a link that says "SPaM"? How many email filters will even let it through?), it is my favorite software related podcasts. Thomas Cagley has really solid guests from across the spectrum, asks good questions and related blog essays on each topic. My favorite episode of all time is Episode 36, which is actually the 2nd part of an interview with Phil Armour. Phil's answer to the question, "Software is not a product. It is a medium, it is a place where we store knowledge."

He explains that there are five such knowledge storing media in the world. They are:
  1. DNA - where species store their knowledge
  2. Brains - a transient knowledge read/write store
  3. Hardware - he gives an example of a ruler storing the knowledge of length or a WW II bazooka that has the knowledge of how to aim it built into the sighting mechanism.
  4. Books - especially the movable typeset books
  5. Software - where the knowledge is not just stored, but it is executable. For example, software doesn't teach me to do the computations needed to compute the standard deviation of a set of numbers- it does it.
He has a lot more discussion about this but just the concept really made a lot of things click for me. When we think about software being a way to encode (and later execute) knowledge, it makes complete sense why long drawn out projects are doomed to fail. Even IF we could completely capture the requirements correctly at the beginning of a project, what we delivered at the end would still miss the mark. Why? In the intervening time the user would have learned some new things. New knowledge that we didn't encode.

And why do we have such a hard time getting the requirements correct? Because, most of the time, we aren't the ones with the knowledge we're trying encode. And the people with the knowledge don't know how to encode it. It is as if the only way a book could be published is if only publishers knew how to write. You know bass fishing and want to share that knowledge? Fine. Call a publisher, describe what you do and see what they come up with. Maybe, if you're lucky, the publisher will come out to actually see you in action and not just go off your description...or let you read an early draft. Oh, and when the book does come out, you now have to fish exactly the way the book describes it and only that way.

We also, all too often, misunderstand "the way we do it now" with absolute knowledge and encode it with no eye towards allowing it to change in the future once we, or the user learn something more. That doesn't mean coding so that everything is an option. But coding in a test driven style so that we have the confidence to go back and change something later and know we didn't break everything else? Try shifting from Scrum with fixed iteration length to Kanban where you have no time constraint but want buckets for the different areas the work item flows through- can your tracking software handle that?

It also tied in to some of the Real Options thinking. Why do options have value? They are giving you some freedom before you've encoded something, which is then costly to change. Time to get more of the knowledge.

Phil also has a good point about things really taking off when the medium is applied to itself. Like when steam was used to power manufacturing lines to make steam engines. How well do we encode (and execute) the knowledge of how to build good quality software into the building of software? Automated testing and continuous integration tools are a good start, but where else can we apply it?

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