By Brad Cross - 1 April 2009
This article is the second in a series on putting the technical balance sheet to work. If you haven't done so already, you will want to read the first in the series.
Taking Action to Increase Equity
So, we've bootstrapped our balance sheet. Now, how to we get some of these ideas into our decision making process? If we notice something that is harming our owner's equity, how do we actually put that knowledge into practice?
It is critical to have code metrics that are actionable. A lot of tools will show you fancy charts, tables and diagrams, but few of these visual representations are actionable from a technical perspective. You need to be able to identify prioritized lists of actions. For example, Simian or CPD will sort the list of code duplication by worst offenders. Clearly, your first action is to tackle the worst offenders. If you see that your highest bug counts and lowest test coverage is in one of your most valuable components, then working on the robustness of that component is a clear action item. Often you can find a few monolithic classes where many of the issues occur; refactoring these while bringing them under test can be a simple way to achieve a radical change in your equity for that component.
Once you have defined a list of actions prioritized by impact on equity in your most valuable components, you are ready to start increasing your equity. There are other important and practical technical considerations to consider, however. As we discussed in the article on cost of carry vs. cost of switching you should be mindful of the impact of encapsulation and the dependencies among components. Start at the least dependent, but most depended upon, parts of the system: the leaf nodes of the dependency graph.
There are a couple of ways to tackle your list of actions. One is through big-bang refactoring or "clean up" efforts, and the other is through a more incremental "as you touch it" approach.
I typically prefer the incremental approach. I continue working as normal, and make the assumption that when I do a new piece of work in a target area, I am going to invest more time because I will be implementing actions from my prioritized list for increasing equity.
This incremental approach works very nicely most of the time and avoids big-bang "let's stop and refactor the world" efforts, which tend to suspend new development and rarely seem to work out well. That said, there are circumstances when it is appropriate to invest in testing and other infrastructure, because these investments can make your incremental efforts more effective. You will often run into structural issues that cause trouble. For example, you may have some monolithic piece of code in the system that everything is tightly coupled to. If this is holding up incremental progress, breaking this code apart in order to restructure the dependencies can be a sound investment. At the moment, I don't have any way to quantify this - you just need to have some people around who have significant experience working on large systems and restructuring efforts and have a pragmatic view and a good instinct for when this sort of thing is required.
Refactor, Rewrite or Replace?
In the article on the cost of carry vs. cost of switching, we made a passing mention of migration strategy.
|Cost of switching is the cost associated with your mitigation strategy. When indebted code is an impediment to sustaining and evolving the functionality of your project, your mitigation strategy is how you go about transitioning away from indebted code in order to reduce or eliminate the impediments. This can entail completely replacing a component with another component, partially replacing a component, or simply small incremental refactorings that accumulate over time. Switching costs are impacted by the size and scope of the component you are replacing, the time you have to spend to find and evaluate commercial and open source alternatives, time spent on custom modifications to the replacement, and time spent on migrating infrastructure - for instance, migrating or mapping user data after switching to a different persistence technology.|
Let's look at migration strategy in more concrete detail.
When we talk about migration strategy, it is usually related to refactoring, rewriting, or replacing.
First, your system needs to be structured in such a way that you make trade-offs at the component level and not system-wide. I discussed this at the very beginning of this series. It doesn't make sense to look at metrics and valuations at the component level unless you can actually trade-off at that level.
Components with a low asset value (easy to substitute) and high liabilities are good candidates for replacing or rewriting. Often you can combine replacing and rewriting by finding a way to write thin custom layers around open source components that can replace these parts of the system. This typically requires a bit of refactoring as well, in order to allow other components to use the new component, so you often end up using a bit of each approach.
Components with a high asset value (hard to substitute) and high liabilities are candidates for refactoring. Sometimes you can pull parts of these components out into new components that can be replaced or rewritten, but often this wont get you far. Typically these high value components are the core domain logic. Often the logic is more sophisticated and if you introduce new bugs while refactoring, they may be difficult to track down as they can result in subtle incorrectness rather than blatant crashing, exceptions and such. Careful and incremental refactoring is usually the way to go.
Finally, sometimes there are good reasons to rewrite an entire application stack. This might be appropriate, for example, if you are switching to an entirely new runtime and technology stack. Sometimes this is called re-platforming. Don't rewrite in the same language and technology stack just because you have written a crappy code base and it is too fragile to change anymore. When you abandon ship in that case, you lose the value of all the lessons you will learn from refactoring it. Sometimes, the best approach is to refactor your way to a rewrite.
Bridging the Gap
In the next piece, we will bridge the gap between finance and engineering. A big part of bridging this gap is noticing how each side tends to gravitate toward the asset and liability side of the balance sheet, respectively. This is where the technical balance sheet shines: allowing you to reduce ongoing investment into the plumbing aspects of your system and increase investment into your "special sauce."
About Brad Cross: Brad is a programmer.