Joel Tosi Joel Tosi

Technical Debt - Learning in (and With!) the Face of Debt

Technical Debt has a few definitions ranging from 'the previous person's bad code' to 'the shortcuts taken to hit a deadline' to my favorite - Technical Debt is 'the gap in the code between what we knew when we started building our product and what we know now'.

Room full of garbage - working with technical debt

Technical Debt has a few definitions ranging from 'the previous person's bad code' to 'the shortcuts taken to hit a deadline' to my favorite - Technical Debt is 'the gap in the code between what we knew when we started building our product and what we know now'.

It's easy to look at a codebase with no automated tests, high cyclomatic complexity, and a manual build process and say 'look - Technical Debt'. It is more challenging to work with a team implementing new features where previous technical choices are making it costly to improve the product. In other words, the code is not maneuverable (Nygard).

These situations happen frequently in the dojo. Let's look at a couple examples.

THE UNTESTED 20-YEAR OLD MONOLITH

Imagine a 20+ year old code base, modified every year by the lowest cost outsourcing firm the organization could find. Now imagine you inherited that codebase with such delights as 900 line constructors that directly connect to databases, establishing pools and locks.  An agile coach could (and had) come into that team and said “You need to get to 70% code coverage for your unit tests”. The team laughed because crying was too obvious.

When teams are in this kind of bind, entering the dojo isn't just about learning how to write unit tests. The team already knew how to write unit tests and was eager to do so. The challenge was finding a strategy to attack the beast. And when deadlines were hitting, it was easier to keep adding code and crossing your fingers.

We did a few things to address the problem. First was getting the team together to identify and discuss quick wins they all wanted to knock out. We did some light brainstorming and affinity mapping which led to a new set of lightweight design changes - all in about an hour or two - and the team had a nice shortlist of changes to start working on. The list would take a week to complete and would be worked on concurrently with new work. It was a small set of changes, but it gave the team a few wins to build upon.

Next, we came up with strategies for attacking the technical debt while working on new stories. One strategy we used quite a bit was using a test-driven approach, focusing on the design of the tests themselves. We’d have a quick discussion around the tests – “where should the responsibility of the tests lie”? With that in mind we’d ask – “what is the delta between where those responsibilities should be and where they'd be given our current design? Can we get there now?”

For some of the stories, we could implement our desired changes immediately. For others, we couldn't. In those cases, we kept a visual list of the spots we wanted to work on. We also created higher-level tests that we could implement immediately with the knowledge that we would remove those tests once we had implemented lower-level tests.

THE MULTI-TEAM MATRIXED DESIGN

Another team was similar in that they had a lack of testing in place, but their challenges were slightly different. This team was formed as an organization’s first attempt at creating 'product teams.' The codebase was gnarly and had contributions from multiple teams over multiple years without much knowledge sharing.

Enter the dojo. The team was doing a little product exploration around a new feature using impact mapping. They came up with a few ideas that would have more impact for the customer than the new feature as it was originally defined. Excellent, right? Not quite. While these ideas were great and the team agreed they were better approaches to the problem, the technology would not allow the better ideas to be built. The way the product was designed made it difficult for required data to be accessed when needed, resulting in unnecessary extra steps. Streamlining a separate process would break downstream services. And so on...

Teaching ideas like parallel change can help in this space. But the real value here came from the whole team learning the cost of technology decisions together, and working together to learn approaches to attack technical debt.

When items like this arise, first and foremost it is still a good thing. Now we can start quantifying design problems and communicating the opportunity cost of technical debt. In this example, we could calculate the cost of the options we could not deliver. The learning expanded beyond the team and became organizational learning.

And in the dojo – we don’t simply teach approaches for tackling technical debt and send the on their way – we help the teams work through it.

What have you done to help teams with technical debt?

 

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