Error Prone VS NullAway

error-prone is good for some extra static analysis.

A special kind of validation is enforcing that record fields are not null. (Un)fortunately, records do not have any special behavior regarding nullability. You can use tools like NullAway or Error Prone to prevent null in your code in general, or you can add checks to your records:

I am all in favour to more third side libraries adding functionalities, like Lombok, Manifold and error prone. As well as smaller projects like this shameless plug and what appears in this list

If only Google didn't suck when it came to Java9+ support... https://github.com/google/error-prone/issues/2649

I haven't used it. I use Google's ErrorProne + Lombok to prevent NPEs in java.

Take a look at NullAway, a plugin for Error Prone.

For some of this stuff, there are compiler extensions that allow extra type checking to be added e.g. Google Error-Prone: https://github.com/google/error-prone with stuff like: https://errorprone.info/bugpattern/ReturnMissingNullable.

Doesn't help you with third party libraries, but across an org applying that rule (and others!) typically ensures some consistency.

How to build a static analysis plugin. Google has a framework for Java with a good tutorial.

Some patterns arise from language design

* You can't express `T` where `null` is forbidden in the type system so you get NullPointerException everywhere and defensive null checks.

* You express a sum type as a product type because your language does not have sum types .

* Your language doesn't have first class multiple return values (or tuples) so you return extra parameters via out parameters or thread local variables such as `errno`.

* Your language doesn't have exceptions (or algebraic effects) and can't do IO so you have monad transformers.

* Your language doesn't have set-theoretic types so you need hacks like `thiserror` .

* Your language doesn't have stackful coroutines or can't infer async IO for you so you have `async/await` spam or callback hell or "mono's".

* Your language doesn't have exhaustive checks (or pattern matching) so you need a fallthrough case check on switch statements .

* Your language doesn't have algebraic effects, so you need to pass context everywhere.

I know someone will reply about Java's null annotation checking options, so here is one of them: https://github.com/uber/NullAway .

If you must use Java, use Uber's Nullaway which gives null safety via Errorprone.

Does anyone have experience using this at Meta who can compare to https://github.com/uber/NullAway ?

A special kind of validation is enforcing that record fields are not null. (Un)fortunately, records do not have any special behavior regarding nullability. You can use tools like NullAway or Error Prone to prevent null in your code in general, or you can add checks to your records:

What do you think of https://github.com/uber/NullAway

Take a look at NullAway, a plugin for Error Prone.

PMD, Spotbugs, Nullaway: Java linting/static analysis (https://pmd.github.io, https://spotbugs.github.io, https://github.com/uber/NullAway)

In personal projects, I've had good experiences using the error-prone compiler plugin with uber's nullaway.