infer VS Spotbugs

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.

SpotBugs is an open source static anlysis tool. "SpotBugs uses static analysis to inspect Java bytecode for occurrences of bug patterns." This means that SpotBugs runs against the compiled source source code, rather than raw Java files. Because it analyses bytecode, it can catch some types of bugs that source code analysis would not catch.

SpotBugs is a great tool for static code analysis. Recently I got two similar warnings in one of the codebases I work on and I had to fix it.

SpotBugs is pretty good.

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

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).

First, it's better to use SpotBugs 4.4.1 and above, that includes a fix to make SARIF report compatible with Github code scanning API requirements.

RUN wget https://github.com/spotbugs/spotbugs/releases/download/4.4.1/spotbugs-4.4.1.tgz