PMD VS infer

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).

I think most development occurs on problems that can't be formally modeled anyway. Most developers work on things like, "can you add this feature to the e-commerce site? And can the pop-up be blue?" which isn't really model-able.

But that's not to say that formal methods are useless! We can still prove some interesting aspects of programs -- for example, that every lock that gets acquired later gets released. I think tools like Infer[0] could become common in the coming years.

[0]: https://fbinfer.com/

Using infer, someone else exploited null-dereference checks to introduce simple affine types in C++. Cppcheck also checks for null-dereferences. Unfortunately, that approach means that borrow-counting references have a larger sizeof than non-borrow counting references, so optimizing the count away potentially changes the semantics of a program which introduces a whole new way of writing subtly wrong code.

Meta/Facebook are long time OCaml users, their logo is on the OCaml website. Their static analysis tool and its predecessor are both written in OCaml.

Then this idea that the US government will tell tech companies how to write secure software. Let's get this straight, the private sector, especially big tech is miles ahead of US government in this regard. Microsoft literally invented threat modelling and modern exploit mitigations. Facebook has the best appsec processes pretty much in the whole world, including their own cutting edge code analyzer. AWS uses formal verification everywhere. Meanwhile the US government itself runs mission-critical systems that's almost literally held together by bubble gum and toothpicks. Maybe they could dial down the arrogance a tad, get their own shit together, learn how this cyber stuff is actually done and only then try lecturing everyone else.

Efforts: Dependabot, CodeQL, Coverity, facebook's Infer tool, etc

I notice there isn't fbinfer. It's pretty cool, and is used for this library.

"Move fast, break stuff" is a great approach when you aren't pushing the broken bits to production. Fuck, even Facebook, the big "move fast, break stuff" company, uses tools to detect errors in its continuous integration toolchain. https://fbinfer.com/

TBH, there's a non-zero amount of non-"ivory tower" tools you may have used that are written in functional languages. Say, Pandoc or Shellcheck are written in Haskell; Infer and Flow are written in OCaml. RabbitMQ and Whatsapp are implemented in Erlang (FB Messenger was too, originally; they switched to the C++ servers later). Twitter backend is (or was, at least) written in Scala.