[jillesvangurp]

There were static code analyzers like findbugs able to do stuff like this 20 years ago. These days, your IDE should tell you off as well. And hopefully teams configure their builds to catch stuff like this using any of the available plugins for this.

LLMs seems overkill for this. But of course letting it do general code reviews is not a bad idea. And static code analyzers aren't perfect. Doing this at scale might be a bit tricky though; you'd have to go file by file. I assume Uber might have many millions of lines of code to screen. And maybe their developers aren't that concerned with addressing warnings.

But going file by file might be simple enough. And you can probably screen for important stuff with some decent system prompt and instruct it to check for potential resource leaks and similar issues and produce detailed bug reports with some priority if it finds them and a diff that addresses the issue. Could be a nice use case for agentic AIs to screen code like this.

[TYMorningCoffee]

These existing tools (spotbugs, findings, sonarqube, null away, checker framework, pmd, etc) provide detection but not resolution. Resolution thru LLM is what Uber proposes.

[nradov]

Resolution of the kind of resource leaks that SonarQube finds is usually the work of a few seconds. And it should be integrated into the developer workflow in such a way that those bugs are found and fixed before the code even gets checked in. In other words, if that code is even making it into a repo where GenAI can find and fix it then you have deeper engineering process problems. Fix the root cause rather than patching around them with more tools.

And once SonarQube flags a resource leak to a developer, a competent developer would learn from that and never make the same mistake again.