- When you are building a system and making trade-off decisions between what can be done now and what will need to be done “sometime in the future”.
- “Sometime in the future”, when have to deal with those decisions, when you need to pay off that debt.
What happens when “sometime in the future” is now? How much debt is too much to carry? When do you have to pay if off?
How much debt is too much?
Every system carries some debt. There is always code that isn’t as clean or clear as it should be. Methods and classes that are too big. Third party libraries that have fallen out of date. Changes that you started in order to solve problems that went away. Design and technology choices that you regret making and would do differently if you had the chance.
But how much is this really slowing the team? How much is this really costing you? You can try to measure if technical debt is increasing over time by looking at your code base. Code complexity is one factor. There is a simple relationship between complexity and how hard it is to maintain code, looking at the chance of introducing a regression:
|Complexity||% Chance of bad fix|
Complexity by itself isn’t enough. Some code is essentially complex, or accidentally complex but it doesn’t need to be changed, so it doesn’t add to the real cost of development. Tools like Sonar look at complexity as well as other variables to assess the technical risk of a code base:
Cost to fix duplications + cost to fix style violations + cost to comment public APIs + cost to fix uncovered complexity (complex code that has less than 80% automated code coverage) + cost to bring complexity below threshold (splitting methods and classes)
This gives you some idea of technical debt costs that you can track over time or compare between systems.But when do you have to fix technical debt? When do you cross the line?
Deciding on whether you need to pay off debt depends on two factors:
- Safety / risk. Is the code too difficult or too dangerous to change? Does it have too many bugs? Capers Jones says that every system, especially big systems, has a small number of routines where bugs concentrate (the 20% of code that has 80% of problems), and that cleaning up or rewriting this code is the most important thing that you can do to improve reliability as well as to reduce long the term costs of running a system.
- Cost – real evidence that it is getting more expensive to make changes over time, because you’ve taken on too much debt. Is it taking longer to make changes or to fix bugs because the code is too hard to understand, or because it is too hard to change, or too hard to test?
While apparently for some teams it’s obvious that if you are slowing down it must be because of technical debt, I don’t believe it is that simple.
There are lots of reasons for a team to slow down over time, as systems get bigger and older, reasons that don’t have anything to do with technical debt. As systems get bigger and are used by more customers in more ways, with more features and customization, the code will take longer to understand, changes will take longer to test, you will have more operational dependencies, more things to worry about and more things that could break, more constraints on what you can do and what risks you can take on. All of this has to slow you down.
How do you know that it is technical risk that is slowing you down?
A team will slow down when people have to spend too much time debugging and fixing things – especially fixing things in the same part of the system, or fixing the same things in different parts of the system. When you see the same bugs or the same kind of bugs happening over and over, you know that you have a debt problem. When you start to see more problems in production, especially problems caused by regressions or manual mistakes, you know that you are over your head in debt. When you see maintenance and support costs going up – when everyone is spending more time on upgrades and bug fixing and tuning than they are on adding new features, you’re running in circles.
The 80:20 rule for paying off Technical Debt
Debt builds up slowly and incrementally over time, until you reach a breaking point. Without careful attention, all code will get worse over time, but whatever problems you do have are going to be worse in some places than others. When it comes to paying back debt, what you care about most are the hot spots:
- Code that is complex and
- Code changes a lot and
- Code that is hard to test and
- Code that has a history of bugs and problems.
You can identify these problem areas by reviewing check-in history, mining your version control system (the work that Michael Feathers is doing on this is really cool) and your bug database, through static analysis checks, and by talking with developers and testers.
This is the code that you have to focus on. This is where you get your best return on investment from paying down technical debt. Everything else is good hygiene – it doesn’t hurt, but it won’t win the game either. If you’re going to pay down technical debt, pay it down smart.
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This 162 page guide will cover topics within the field of software architecture including: software architecture as a solution balancing the concerns of different stakeholders, quality assurance, methods to describe and evaluate architectures, the influence of architecture on reuse, and the life cycle of a system and its architecture. This guide concludes with a comparison between the professions of software architect and software engineer.