Suppose we have a large to-do task manager app with many features. Say we have an entity, which is the task, and it has certain fields like: title, description, deadline, sub-tasks, dependencies, etc. This entity is used in many parts of our codebase.
Suppose we decided to modify this entity, either by modifying, removing, or adding a field. We may have to change most if not all of the code that deals with this entity. How can we do this in a way that protects us from errors and makes maintenance easy?
Bear in mind, this is just an example. The entity may be something more low-key, such as a logged user event in analytics, or a backend API endpoint being used in the frontend, etc.
Potential Solutions
Searching
One way people do this already is by just searching the entity across the codebase. This is not scalable, and not always accurate. You may get a lot of false positives, and some parts of the code may use the entity without using it by name directly.
Importing
Defining the entity in one central place, and importing it everywhere it is used. This will create an error if a deleted field remains in use, but it will not help us when, say, adding a new field and making sure it is used properly everywhere the entity is being used
so what can be done to solve this? plus points if the approach is compatible with Functional Programming
Automated Tests and CICD
Tests can discover these types of issues with high accuracy and precision. The downside is… Well tests have to be written. This requires developers to be proactive, and writing and maintaining tests is non-trivial and needs expensive developer time. It is also quite easy and common to write bad tests that give false positives.
Test coverage alone is meaningless, you need to think about input-coversge as well, and that’s where you can spend almost an infinite amount of time. At some point you also have to ship stuff.
You get it!
Fully agreed things need to get shipped but that’s why I’m a fan of test driven development. You’ll always have your tests written with your feature.
Then again even if someone does it after as long as you write a test every time you write a feature you’ll eventually have the code base covered.
Input coverage is new to me, mind linking me some info so I can learn? (Yes google exists but if someone has the low down on a good source I’d prefer that)
By input coverage I just mean that you test with different inputs. It doesn’t matter if you have 100% code coverage, if you only tested with the number “1”, and the code crashes if you give it a negative number.
If you can prove that your code can’t crash (e.g. using types), it’s a lot more valuable then spending time thinking about potentially problematic inputs and writing individual tests for them (there ate tools thst help with this, but they are not perfect).
Ahhh gotcha gotcha. I was doing this by default in my python testing, glad I was doing things right