PMD VS NullAway

While the security findings can be pretty elaborate and helpful, the code quality and performance focused findings are not that impressive and can often be detected by more basic or powerful tools like SonarQube (paying) or PMD (free). To see what I mean you can have a look at the list of Java code quality detectors, which is pretty short and contains a lot of simple findings like:

Also saw this convo has a couple years worth of ideas going on … https://github.com/pmd/pmd/issues/3413

PMD and Checkstyle are static analysis tools that check your code on each project build. Gradle allows to apply them easily.

The generated classes should be put into .gitignore. Otherwise, if you have Checkstyle, PMD, or SonarQube in your project, then generated classes can violate some rules. Besides, if you don't put them into .gitignore, then each pull request might become huge due to the fact that even a slightest fix can lead to lots of changes in the generated classes.

- PMD Static Code Analysis tool: https://pmd.github.io/

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

PMD, and checkstyle as well.

Open up the config/ruleset.xml file, and you’ll find an XML document that lists several rules. These rules map to the issues which PMD will report on. Believe it or not, there are hundreds of Apex rules, and you can find the full set at the PMD repo. You have complete control over which rules to enable. Typically, you’d determine which ones are important by agreeing with your teammates on the ones that matter most. After all, their code will be statically analyzed, too!

While at it you could also point them to static code analyzers such as error_prone, spotbugs and pmd (use all 3 at once - they complement each other in detecting different issues).

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.