Given coverage data, how would you build a tool to decide which untested parts of a codebase most need tests?
The best I can think of is using profile data to ensure hotspots are tested. Not sure if it's ideal though: top level code and well-exercised logic would be highlighted.
miniblog.
Related Posts
Twitter treats #foo and $bar as special syntax due to emergent behaviour of users.
I keep seeing similar emergent features in other domains, e.g. airport wifi using '_Foo Wifi' to ensure it's sorted first. Ideally there'd be a priority flag, so a printer is never shown first.
Python and JS can both execute code when loading libraries (`import foo` and `require('foo')` respectively).
Yet the Python CLI apps I've seen have to do much more work to ensure good startup performance (e.g. `myapp --help` not being slow). I'm not sure why.
If you pay users to store copies of your data, how do you ensure that they don't claim they have extra copies? An interesting problem! Public Incompressible Encoding for e.g. FileCoin: https://hackingdistributed.com/2018/08/06/PIEs/