Why is this needed? Can't you imply the necessary analyzers from my codebase?
There is no support for Javascript, Typescript, PHP, Java or C#. No HTML or CSS support. Is there a roadmap?
Also, the name implies use if Deep Networks and AI. Am I mistaken? If not, what kind of AI is used here? Seems like just an automatic runner of static analysis tools.
Why is this needed? Can’t you imply the necessary analyzers from my codebase?
Sure. We can probably infer the languages used in the repository. But we need metadata like test glob patterns, exclude patterns, runtime versions (Python 2, Python 3) to improve the accuracy of issues. For ex: Usage of assert statement in application logic is discouraged as it is removed when compiling to optimised byte code (python -o producing *.pyo files). Ideally, assert statement should be used only in tests. Also, we haven’t found a way to infer Python 2 vs Python 3 accurately. Can you think of a way? That would be helpful.
There is no support for Javascript, Typescript, PHP, Java or C#. No HTML or CSS support. Is there a roadmap?
We strongly believe in starting out with a few languages and add as many issues as we can (with the ability to autofix most of them) -- before we go broad. That said, we released Ruby in beta couple weeks back and are currently working on the stable release. We’ve also started working on JavaScript (with TypeScript support) a month back and we should release the beta version of JavaScript analyzer in approx a month from now.
Also, the name implies use if Deep Networks and AI. Am I mistaken? If not, what kind of AI is used here? Seems like just an automatic runner of static analysis tools.
It’s just the name :) We do not use Machine Learning or AI at the moment — the reason being we’re optimizing for high accuracy, and a rules engine that uses AST parsing helps us do that reliably. We do plan to use learning in the future to capture data around which issues are being fixed the most and which are not, and then show issues in the most relevant order to users depending on their context.
Comments
Why is this needed? Can't you imply the necessary analyzers from my codebase?
There is no support for Javascript, Typescript, PHP, Java or C#. No HTML or CSS support. Is there a roadmap?
Also, the name implies use if Deep Networks and AI. Am I mistaken? If not, what kind of AI is used here? Seems like just an automatic runner of static analysis tools.
Sure. We can probably infer the languages used in the repository. But we need metadata like test glob patterns, exclude patterns, runtime versions (Python 2, Python 3) to improve the accuracy of issues. For ex: Usage of assert statement in application logic is discouraged as it is removed when compiling to optimised byte code (python -o producing *.pyo files). Ideally, assert statement should be used only in tests. Also, we haven’t found a way to infer Python 2 vs Python 3 accurately. Can you think of a way? That would be helpful.
We strongly believe in starting out with a few languages and add as many issues as we can (with the ability to autofix most of them) -- before we go broad. That said, we released Ruby in beta couple weeks back and are currently working on the stable release. We’ve also started working on JavaScript (with TypeScript support) a month back and we should release the beta version of JavaScript analyzer in approx a month from now.
It’s just the name :) We do not use Machine Learning or AI at the moment — the reason being we’re optimizing for high accuracy, and a rules engine that uses AST parsing helps us do that reliably. We do plan to use learning in the future to capture data around which issues are being fixed the most and which are not, and then show issues in the most relevant order to users depending on their context.