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.
If you update your tests to reflect proper usage of the new field then you can catch potential errors.
Automates tests definitely work, but the downside is it requires the developer to be proactive, and the effort put in writing tests is non-trivial (and its easy and common for developers to write bad tests that give false positives).
Hmm I think you’re looking for a technical solution to a non-technical problem.
Depends on what you consider technical. I don’t see this as much different than how type systems prevent type errors.
Take your example of adding a field to an entity. Just because you’ve made that code change doesn’t mean other code should be using it. Who should be using it and how is determined by the business rules.
Also your interest in ensuring it is “properly” used is impossible to enforce. What’s considered proper even for existing code can change over time.
Having unit and automated integration tests backed by both requirements and high code coverage. As a lead I can verify that not only you made the change to support the requirements though these unit tests but also a really quick verification that other functionality may not have changed based on your large scale change. Helps a lot for significant refactoring too