Recently I landed experimental support for require()-ing synchronous ES modules in Node.js, a feature that has been long overdue. In the pull request, I commented with my understanding about why it did not happen sooner before this pull request in 2024. This post expands on that comment a bit more.

In the previous blog post, I described the heap snapshot trick as an “abuse” of the heap snapshot API, because heap snapshots are not designed to interact with the finalizers run in the heap. But the concept of using heap snapshots to identify/disprove leak itself is not an abuse - that’s exactly what they are designed for. Well then, can we use heap snapshots, or a simpler version of it, to test gainst memory leaks?

In the previous blog post, I talked about how Node.js used memory usage measurement to test against memory leaks. Sometimes that’s good enough to provide valid tests. Sometimes we want the test to be more precises and focus on the status of specific objects. This can be quite tricky with what’s available to interact with V8’s garbage collector.

Like many other relatively big piece of software, Node.js is no stranger to memory leaks, and with them, fixes and regression tests. Testing against memory leak regressions, however, can be particularly tricky in a runtime with a garbage-collected heap, and quite a few of these tests became source of flakes in the Node.js CI. In the past few months, I’ve been doing some work to improve the reliability of these tests. I’ve also come across a few bug reports in the Node.js issue tracker memory leaks that turn out to be false alarms because the reproductions made incorrect assumptions. Here are my notes about the testing strategies Node.js uses against memory leak regression, my observations about them, and why I added a new testing strategy with a new V8 API. Hopefully this can help the readers write less unreliable memory regression tests/memory leak reproductions.

In the last post I wrote about how I finally managed to fix the memory problems in the vm APIs, and it turned out that there was another issue blocking users from upgrading away from the End-of-Life Node.js v16 - vm.Script compilation could be ~100x slower in v16 in some cases. In this post, let’s look at what was causing the performance regression, and the fix/workaround developed for it.

In the last post I wrote about how a new memory management model in Node.js vm APIs was designed to fix the long-standing leaks and use-after-free issues, and we finally put together a PR that the Node.js core CI and CITGM CI were happy with. The road to landing it and releasing it to LTS still turned out to be bumpy, however.

In the last post, I wrote about how I came to work on a memory leak in the vm compilation APIs in Node.js, attempted a fix, and reverted it because the fix turned out to be unsound and introduced a use-after-free. In this post I will write about how I got to another fix that ended up working.

This year I spent some time fixing a few long-standing issues in the Node.js vm APIs that had been blocking users from upgrading away from Node.js v16 (End-of-Life). It had been an interesting journey, so I decided to write a few blog posts about it. Hopefully they can be helpful for posterity.

Up until V8 10.0, the class field initializers had been broken in the V8 startup snapshot - a feature used by embedders like Node.js and Deno to speed up the bootstrapping of themselves or user applications. This post is going to cover how the startup snapshot support was implemented, as part of the work our team did on the class features in V8. To learn about the optimizations we did for instance initialization with the new class features, checkout another post published in the V8 blog.

I’ve recently got an M1 MacBook and played around with it a bit. It seems many open source projects still haven’t added MacOS with ARM64 into their support matrix, requiring a few extra steps to work properly, and V8 is no exception. Here are the steps I’ve taken to get V8 building on a M1 MacBook and hopefully it could help someone else on the Internet.