The Experiment Canvas is a simple means of planning, tracking, and responding to your experiments.
Simple Things
When I say simple, I don’t necessarily mean easy. And I certainly do not mean crude in form or incomplete. Simple indicates something that does not have superfluous parts or multiple responsibilities, is easy to understand, is as independent from the rest of the solution as possible, and meets a need as is.
Simple may not address all use cases, but it does address some use cases.
Over the past several years, as I’ve been helping teams and organizations improve their ability to deliver software products that are desirable, viable, and feasible, I have been experimenting with a Behavior Framework that has proven to be rather effective. And I’d like to share it with you in hopes that you find it useful and that you provide me feedback on your experiences with it.
My plan is to write a series of blog posts all related to the behaviors framework. Some of them will be about a specific behavior. Some of them will be about tools or techniques that help teams express one or more of the behaviors. Some of them will be my own experiences. And some will be damn near complete fiction.
I was recently asked to engage in a debate over whether or not there are deadlines in agile. There were a few folks involved in the debate and the predominant perspective seemed to be that true agile efforts have no external deadlines - all deadlines are self-imposed by the team in the form of an iteration commitment or a scope negotiation with the Product Owner.
This is bunk.
I was recently asked to answer the somewhat vague question, “How do you interact with a large undocumented code base?”
One small step at a time.
A large code base can be overwhelming. Rather than trying to get to know the whole thing, I tend to focus on the problem at hand.
Today’s offering is another post inspired by a question on Quora about when to refactor away duplicate code.
The specific question was, “What is the limit for duplicate code to start refactoring?”
I took this to mean, “How much duplication needs to exist before you should refactor it?”
And I’m not sure that’s really a great question. So I decided to start with clarifying what duplication needs to be cleaned up and then when might that happen.
For me, refactoring is when we change the implementation of a piece of code without changing the behavior. That’s the entire definition - Change the implementation, but not the behavior.
As a result, I will generally not refactor code unless it has a solid set of tests around it. If I see code that needs refactoring, but has insufficient tests, I will add character tests.
I no longer believe we can return to the original, healthy and helpful definition of Technical Debt. Nor do I think we’re going to shift away from it to a better metaphor.
But maybe we can talk about remediation of Technical Debt in a way that helps us make better decisions.
The way I see it, Technical Debt Remediation is nothing more than Maintenance. Maintenance is to keep in an existing state (as of repair, efficiency, or validity) or to preserve from failure or decline.
Technical Debt Remediation (Maintenance) comes in different categories – Preventative, Deferred, and Repair.
I am wrapping up my second in a series for Clean Coders on Technical Debt. In the first episode, I explain the Technical Debt metaphor, how it originated, how it changed over time, and how it now is commonly understood in a way that is the opposite of what it originally meant. I talk a bit about the limitations of metaphors and how debt in particular has not served us well as a metaphor over time. So when a link to an article on the "Limits of the Technical Debt Analogy" hit my inbox this morning, I was quick to follow the link and see what the author had to say.
Unfortunately, this article is not at all about the limitations of the metaphor. The article is about how people other than those who write the software are responsible for the quality of the software. This article is bunk.
I recently gave a talk on the role of a Quality Analyst as an organization transitions from waterfall to agile. The talk was entitled "Switching Horses in Midstream" and covered a number of topics. One item in particular struck me as worthy of blogging about. It's a technique I've been using for years, but have never written about it. So here we go:
Legacy code bases with a lack of test coverage are often trepidatious places to hang out. You never know when a simple abstract method is going to create a sink-hole of logic and reason, eventually leading to your exhausted resolve to revert and leave it dirty.
In a discussion on the Agile Alliance Linked In Group, Michael Moles asked how refactoring fit into the agile process.
The Question
Refactoring: How does it fit into your Agile process?
We are in the midst of writing a new product, at this point the developers are realizing that some of the code should be refactored to improve performance and or clarity for ease of use. How do you fit refactoring into you Agile process? We have created separate backlog items for refactoring specific pieces of code. These backlog items are treated exactly like any other backlog item (meaning they have effort assigned and are committed to sprints by the team). What do you do when refactoring is necessary?
A former coworker of mine, Jim Highsmith, has recently written an article on The Financial Implications of Technical Debt. Jim states that recent studies indicate the cost of technical debt is near $1 trillion in the U.S. I would like to see these studies. I do know that not too long ago, Gartner released a report indicating that the worldwide cost of IT Debt will be $1 trillion by 2015. Regardless, the point he makes is still valid - technical debt is egregious.
Jim states, "Unfortunately, by the time many organizations are paying attention, all the solutions are bad ones: 1) do nothing and it gets worse, 2) re-place/re-write the software (expensive, high risk, doesn’t address the root cause problem), or 3) systematically invest in incremental improvement."
Of these three (bad) options, I think the second is often a better choice than the third. The first represents failure to make a necessary decision.
During the speaker panel at SCNA this past weekend, Chad Fowler (@chadfowler) asked, "How many projects fail because of the code?". Given the context, I assumed he was making the point that projects fail due to business issues, not code. The room was silent. While one might have assumed this meant the entire group thought it rhetorical, I concluded everyone agreed with Chad. Projects fail not due to code, but due to business issues.
