I rent my apartment. I moved here in 2018, and over the last 5 years (because of many factors, but mostly inflation), my rent has gone up about 30%. Inflation over that time is about 22%, so it’s even gone up in constant dollars.

If you had a fixed-rate mortgage, your payments would have gone up 0%. When you have a mortgage, inflation makes housing costs relatively smaller in your total budget because everything else goes up. If your interest rate is lower than inflation, then you get to pay the debt back in lower-value dollars.

The same is true for tech debt where inflation is the increasing size of the codebase and the team. Writing more code shrinks the relative cost of the debt you have. Having more team members makes paying tech debt a smaller proportion of your work.

If you had a metric of tech-debt, new good code would tend to lower it. This is true as long as interest on the tech debt is not too high. For tech debt, interest payments are only due if you want to change the code.

If your roadmap requires you to mostly change tech-debt-laden code, then inflation is low (no new code) and so the interest payments are high. This is a good time to prioritize paying tech debt down.

Conversely, code that has debt, but basically works and is not going to be changed, is like having a 0% loan. You have the loan. It may one day come due, but at least you don’t have to service it if you don’t want to. If your team and codebase doubles in size, that debt will feel smaller.

Yesterday, I wrote about the Tech Debt Detectors that I use in Visual Studio Code.

Here’s what it looks like for one of my CRAP-y functions. The red bars in the left-gutter show that I don’t test this function at all, and the red square at the end of line 4 shows that it has a lot of branches.

I wrote this function to make it easier to call GQL Mutate functions with boiler-plate error handling. This function reduces the complexity of each calling function. I am ok with this being complex, so to reduce CRAP, I should be testing each branch. I was surprised that I didn’t already do this, because I test GQL calls with a mock server. I did a full text search for for the function name, and I see that … I NEVER USE IT?!

Ah yes, now I remember. I didn’t like that this code wasn’t type-safe, so I generated type-safe variants from my queries (see Why I am Using Code Generation Again, Part I and Extending GraphQL Code Generation (Part II).

I never removed this function after migrating all code to the new version, so I did it now. Deleting code is a great way to lower tech debt. No code—no debt.

When I wrote Use Your First Commit to Fix CRAP I said that “there are extensions for many IDEs to get you the [CRAP] metric directly”, but I hadn’t installed any. I thought that the two components of CRAP were easy enough to notice without them, but that’s only half-way true. Today, I use two extensions for Visual Studio Code to help make CRAP-y more evident to me.

Note: The CRAP metric indicates that a function is risky to change because it’s complex and undertested. To fix the function, you either need to break it into smaller functions or add tests—both actions are generally good, so it’s a metric that’s hard to game.

The first component of a CRAP-y function is its complexity, which you can estimate by counting its branches. So, count each if/else-if/else, case in a switch, loop/break/continue, and each or/and in your boolean expressions. You are trying to get an idea of how many paths there are. Since, you want to keep function complexity very low, you really don’t need to count every branch—you can stop at some low (single-digit) number. It isn’t hard to estimate a YES/NO answer to the question of complexity for any particular function, but the problem is remembering to ask.

To get complexity in Visual Studio Code, I am using CodeMetrics by Kiss Tamás. For each function, the extension shows a green, yellow, or red indicator and a short message above the function.

The second component of CRAP is test coverage. To show that in my editor, I use Coverage Gutters. This extension shows red and green markers to the left of the code to indicate if a line was run during tests. It needs you to generate standard code coverage files, which jest can do for me. It should support any language that has standard coverage support (i.e. in lcov format).

I’ll show some examples of what this looks like and how I fixed problem areas in upcoming posts.

I just shut down a project I started in October 2021. It was code for a startup, but it turned out the idea didn’t have traction, and my partner and I decided that it wasn’t worth pursuing. The tech debt in this project will never be paid. If I had been paying it all along, it would have been a waste of time.

This was not a full-time project for me, and I am the only developer on it, so there’s not a ton of code. But, even a three-month project could have a little debt, so even though it’s not that old, it had some debt.

Like most projects, it had dependencies. I just checked my yarn.lock files and I see that the last time I did an update was about a year ago. I consider all third-party dependencies to be tech debt, especially as they get out of date, so that’s one that’s always building on most projects. The only way to avoid dependency debt is to not have dependencies. Which, in a way, is true now.

The biggest codebase issue that I was wrangling with was authorization. The permission model was getting a little out of control, and the code wasn’t helping make sense of it. I had been planning something more attribute based in the code, but well, now I don’t have to worry about it.

If there’s a lesson to learn here, it’s this: Don’t rush to pay off debt in projects that have a good chance of dying. The goal should be to get customers. To the extent that it’s not externally perceivable to customers, code health is usually not much of a factor in early traction.

I’ve been working on a new web app since October. The backend is a GraphQL API on top of a database schema. Each entry point unpacks the request and then calls a function that queries or mutates the database. There are some complex mutations—ones where there might be updates, inserts, and deletions that all need to succeed or fail together.

I know that I’m supposed to do this with transactions, but I was also using an ORM that I’m not very familiar with, and wanted to make progress quickly. I decided to pay lip-service to transactions, wrap some functions in them to indicate to myself that I needed to think about them, but mostly just ignore them. I would never not do transactions in a production app, but for this, it made sense.

After MVP, a month or so ago, I’ve just been adding minor things while my partner onboards some trial users. Eventually, I tried to implement a feature where the API call could result in many inserts and deletions, and I could see in tests that I could cause this to fail in ways that corrupted the data.

So, I had to stop, learn how to do transactions in this ORM, and then implement them in my data code. It took a few hours, and now the debt is paid off.

I do this kind of short-term borrowing/paying of debt all of the time. I am borrowing to keep myself in flow. I try to keep the debt top-of-mind by making it very evident in the code. It’s like using a credit card where you pay it off inside the grace period.