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Mar 11, 2017 at 21:48
Detecting Android malware by extracting a static call graph and applying ML https://blog.acolyer.org/2017/03/09/mamadroid-detecting-android-malware-by-building-markov-chains-of-behavorial-models/ (impressive how high-level the CFG is)

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Jun 14, 2022 at 22:37
Many languages use docstrings rather than doc comments: it certainly makes extracting them easier. You just parse the code. Could you go further and require all comments to be string literals? I'm struggling to think of many downsides.
Mar 3, 2018 at 16:53
There's an eslint plugin for extracting JS from HTML, so you can catch issues even when using inline JS!
GitHub - BenoitZugmeyer/eslint-plugin-html: An ESLint plugin to extract and lint scripts from HTML files.
GitHub - BenoitZugmeyer/eslint-plugin-html: An ESLint plugin to extract and lint scripts from HTML files.
An ESLint plugin to extract and lint scripts from HTML files. - BenoitZugmeyer/eslint-plugin-html
Aug 31, 2017 at 18:11
Extracting machine-readable specs from natural language specs for ARM architectures, and finding ambiguities!
Are natural language specifications useful?
In my efforts to create a formal specification of the Arm architecture, I have focussed on the parts written in “pseudocode”. I have reverse engineered the ASL language hiding inside the pseudocode to create a formal, executable specification that I can execute and test. In the process, I have tended to ignore all the natural language prose that makes up the bulk of the 6,000 page Arm Architecture Reference Manual. In defiance of Betteridge’s Law, this article is going to explain how I finally found a use for all that prose.