this post was submitted on 03 Mar 2024
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Programming

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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.

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[โ€“] RonSijm 1 points 8 months ago (1 children)

It depends on the language, since you mentioned you don't want to do manual testing -

Start with a mono-repo, as in, 1 repo where you add every other repo as a git submodule

Then, every time something changes you run that repo though the build server, and validate that it at least compiles.

If it compiles, you can go a step further, build something that detects changes, for example by parsing the syntax tree of everything changed, then check the syntax tree of the entire project which other methods / objects might be affected. In dotnet you'd do this with a Roslyn Analyzer

[โ€“] [email protected] 1 points 8 months ago

you mentioned you don't want to do manual testing

Just to clarify: I didn't mean that tests shouldn't be written. I just don't see testing as a sufficient solution to this problem.