Understand and identify code health issues and automatically improve them, all in one place. Semantically validated to eliminate the introduction of new bugs or poor quality code, no prompts or queries required.
More precise
Using multiple LLMs, ACE then selects the best option that is semantically validated against your existing codebase
More impactful
By automating code refactoring, dev teams can vastly improve their overall code quality while still continuing to innovate
More valuable
Devs spend the majority of their time understanding and maintaining code. ACE expedites code familiarity
Calling all early adopters
Now accepting sign ups to the waitlist
Join the waitlist for CodeScene's new AI generated code refactoring tool.
You'll get first access to the only generative AI coding assistant with up to 98% accuracy.
Backed by research
With a benchmark study, CodeScene's Adam Tornhill, Markus Borg and Enys Mones explore a new frontier by investigating AI support for improving existing code.
The majority of a developer’s time isn't writing but understanding and maintaining existing code. But today’s AI is simply too error-prone, and far from a point where it is able to securely modify existing code.
In this whitepaper, they benchmark the performance of the most popular Large-Language Models (LLM) on refactoring tasks for improving real-world code, with shocking results. Read the study and learn how CodeScene uses a different approach to ensure accuracy.
I'm surprised with ACE's suggestions, as they are quite similar to what I would have come up with myself, saving me time and cognitive effort.
Wlad Gramacho
- Manager Software Engineering, Up Learn
Relevance, context and impact
How does it work?
Understand the health of your entire code base
We use our proprietary algorithm called Code Health to identify refactoring targets in your code base based on a number of contextual factors and how your code has evolved over time. It is the only code-level metric with proven business impact
Get refactoring suggestions tailored to code smell
Not only does CodeScene identify what code is low in quality or has less than perfect Code Health, we understand why, by identifying a number of the most common code smells
Use generative AI to refactor legacy code
Using this gold standard metric, the AI then produces a recommended replacement for the code snippet that should be improved, ensuring the AI written code does, in fact, fix the code smells
Accurate and robust training model
The model has been trained on a massive data lake of refactoring examples so that it recognizes what old "bad" code looks like, as well as the changes made to improve it
Fact check AI generated code
We then use a secondary CodeScene AI that fact checks the AI generated refactored code. In early tests, we see a 98% accuracy rate, a stark difference to the current industry benchmark of 40-50%
Same certified security
We never store your source code, nor do we use it to train our models. We also never send the full source code to the AI, only snippets. Everything is encrypted and protected in transit
Learn more about CodeScene's Code Health and refactoring targets
Our AI for automated refactoring is built on top of our already leading software for code analysis and technical debt reduction.
