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Tackling Technical Debt- Where to start?

Every software project accumulates technical debt. Like financial debt, it compounds over time if left unaddressed, making future changes increasingly difficult and expensive. But knowing where to begin tackling technical debt can be overwhelming.  As our time is limited, we have to choose wisely.

I got inspired after watching Adam Tornhill  talk called Prioritizing Technical Debt as If Time & Money Matters. So before you continue reading this post, check out his great talk:

Back? Ok, let’s first make sure that we agree on our definition of ‘technical debt’…

Understanding Technical Debt

Technical debt isn't just "bad code." It represents trade-offs made during development—shortcuts taken to meet deadlines, features implemented without complete understanding of requirements, or design decisions that made sense at the time but no longer fit current needs.

Technical debt manifests in several ways:

  • Code smells: Duplicated code, overly complex methods, and poor naming conventions
  • Architectural issues: Components that are tightly coupled, poorly defined boundaries, or misaligned with current business needs
  • Missing practices: Inadequate test coverage, outdated documentation, or manual deployment processes
  • Outdated dependencies: Frameworks, libraries, and tools that are no longer maintained or compatible with newer systems

Where to start?

OK, time to tackle the real topic of this post; where do we need to start when tackling technical debt? In a large and complex codebase there are typical a lot of places where technical debt can be found. The way that Adam explains in his talk is by looking for ‘hotspots’ in your code, code that changes a lot:

It doesn’t make much sense to tackle technical debt in code that is never touched or changed. However if you combine this change frequency with any of the available static code analysis tools available to identify technical debt, you can easily craft a list of places where to look first.

You can identify these hotspots in a (git) codebase directly using git:

git log --format=format: --name-only --since=12.month \
| egrep -v '^$' \
| sort \
| uniq -c \
| sort -nr \
| head -50

This will return the list of most frequently modified files in the last year based on the number of commits:

While writing this post, I found that there are multiple tools out there that can help you identify these hotspots. I tried Hotspot, a .NET Global tool that combines your git change history with some complexity metrics to identify possible hotspots.

I first installed the tool using:

> dotnet tool install -g hotspot
You can invoke the tool using the following command: hotspot
Tool 'hotspot' (version '0.0.4') was successfully installed.

Now I can invoke it using:

> hotspot recommend

I tried it on an (older) project and I got the following output:

 

Nice!

More information

Prioritizing Technical Debt as If Time & Money Matters • Adam Tornhill • GOTO 2022

Understanding Technical Debt

Lehman’s Laws of Software Evolution

Hotspots — CodeScene 1 Documentation

dburriss/hotspot: A dotnet command-line tool for analysing code risks like high complexity, size, and bus factor.

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