Just-in-time (JIT) compilation

Just-in-time (JIT) compilation is a technique used by interpreters to compile code on-the-fly, just before executing it, rather than compiling the entire program ahead of time like a traditional compiler. It's a way to get the best of both worlds - the flexibility of interpreted code with the performance of compiled code, kind of like having your cake and eating it too (if the cake was made of bytecode).

How to use it in a sentence

  • I was trying to optimize my code, but then I remembered that the JIT compiler will probably do a better job than me anyway, so I went back to browsing Hacker News.

  • The startup's new interpreter uses just-in-time compilation to make their trendy language almost as fast as C, which is great news for the dozens of developers using it.

If you actually want to learn more...

  • JIT Compilation Techniques - This article dives into the nitty-gritty details of how JIT compilers work their magic, for those times when you really want to procrastinate on that feature you're supposed to be building.

  • The Java HotSpot Performance Engine Architecture - A classic paper on the HotSpot JIT compiler used in Java, which is responsible for making Java's performance almost tolerable.

  • Intro to JIT Compilers - A gentler introduction to just-in-time compilation that won't make your eyes glaze over quite as quickly as the other links.

Note: the Developer Dictionary is in Beta. Please direct feedback to skye@statsig.com.

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

Why the best build with us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy