Has anyone found a static analysis tool which understands C11 annex K (aka “safe C”) functions? I’ve found some tools like CLANG static analysis will raise errors for potentially incorrect calls to stdlib C functions, but doesn’t understand the replacements, which means some errors previously caught by analysis can only be caught at runtime.
The concept I use is that the next stage is all about how you implement the previous one: the spec is how you implement the requirements, the design is how you implement the spec, the code is how you implement the design.
As okl said, it’s arguably terminology, and maybe high and low level requirements would work for you? I prefer to separate out the terms though, so that “requirements” are the thing that the engineering team can’t unilaterally change without upsetting the stakeholders. If I can change a spec item mid-delivery and it doesn’t matter to the customer, then it wasn’t a requirement. If I can’t change it, then it’s a requirement.
Note that legal tender != can buy milk with. Legal tender is only about payment of debt. A shop selling you something doesn’t have to accept any specific form of payment, as they don’t let you build up a tab which needs repaying.
Windows allows you to use a PIN for regular device logon - so you have a longer, more secure password for general use of the account, but an eg 8 digit numeric PIN _only_ for that device.
How did you find/calculate the floor area from Rightmove? In my experience listings _might_ have the area in the floor plan image, so you’d be hoping for floor plans then running OCR to find the area? But I’d expect that to often go wrong or not find anything (missing or duplicate floor plans etc). Would love to know as it’s infuriating that the UK market is based on bedroom count rather than floor area.
On the underground you’re meant to stand on the right of escalators to leave room for those walking up on the left. However, TFL ran a trial a few years ago instructing people to stand on both sides during peak times. This actually increased overall throughout and per-person speed: throughput as you can more closely pack passengers standing rather than allowing a smaller number of walkers half the space (and those walkers are necessarily spaced out more than standers), and per-passenger speed because even though walking up the escalator would be faster, the increased throughout reduces the queue time at the escalator entrance, which has a greater effect.
To my knowledge, they didn’t move forwards with keeping the instruction permanent in peak times, presumably because it’s difficult to implement / ingrain in people.
This seems a poor article for not mentioning the St Patrick’s Cross - one of the flags “making up” the Union Flag / Union Jack, representing Ireland. It’s contentious, but arguably significantly less so than the Ulster Banner.
So am I right in understanding you aren’t saying photography isn’t “an art”; just that it isn’t “fine art”? In which case I think you’d see much less disagreement here.
Does your art class perhaps only cover “fine art”? Or does it also include the performing arts like music, theatre, even cinema? In my experience in the UK, “art” in school commonly only means fine art, and other forms of art are different enough that they’re broken out into other “subjects”.
I agree? In the above I'm assuming equal likelihood between each lab and each city, rather than equally likely to have come from any lab vs any city. The second is a poor starting point as it suggests having two, 100, or 1M labs would mean no increased chance of coming from a lab vs 1 lab. That's why I suggest the first.
To get the 1% figure you have to include an unstated assumption, which is that a novel virus is just as likely to emerge from this lab as from all top 100 cities put together.
If we try to make a rough calculation from an unknowledgeable starting position, it might be more reasonable to say "just as likely to come from each 1M+ city as to come from each lab [of which there is one]". Then, if we didn't know the geographic origin, the lab probability is ~1% ( = 1/(100 cities + 1 lab)), but knowing the geographic start point you'd get 50%
P(this lab given Wuhan) = P(Wuhan given this lab) * P(lab) / P(Wuhan)
P(this lab given Wuhan) = 1 [this lab is in Wuhan!] * (1/101) / (2/101)