Not that it got me anywhere in the long run.
22 karma · joined January 4, 2021
Not that it got me anywhere in the long run.
Most poeple out there building new rail are building them in situations similar to how other people have already built rail: apply known best practices given the intricacies of the current situation. Very few people are doing things like "building the worlds first rail line across a floating bridge" (Seattle I-405).
Even something like DeepSeek in China, wasn't necessarily so much about big AI breakthroughs as it was low level optimization of existing hardware. At the end of the day, even big achievements are built on piles and piles of what seems like drudgery, I guess it's just about feeling like that drudgery is contributing to something great.
In terms of ratio between effort expended to leads generated, those hiring threads are A+.
That's a new one.
It would appear you linked to the NatGeo API for some reason, here's a link to the actual article: https://www.nationalgeographic.com/science/2021/01/has-scien...
BUT.
Neither of those imply to me that people should be building their own computers. My life revolves around computers, either at work, or in my primary leisure time. I am well incentivized to learn more about them. My mom's life does not, it revolves around her garden. My best friend's life does not, it revolves around his wife and son. Could these people learn to build a computer and get a better one for cheaper by building? Yes. Would they rather pay someone or some company a small premium to build it for them so they can live their life? Yes.
This also pertains to the car example leading the article, as well as the existence of professional accountants, stock brokers, paralegals, lawyers, librarians, dietitians, electricians, plumbers, arborists, etc. I could do anything I want for cheaper by putting my own effort into it, but life is way too short to do everything, especially things I have no interest in.
So the basic accounting equation is Assets = Liabilities + Equity. Any increase in liabilities must be balanced with an increase in Assets (you use a credit card to buy a lamp) or a decrease in equity (taking out a predatory payday loan to cover utilities).
The flipside of this is if you increase your liability to gain an asset worth even more, your equity goes up (take out a loan to buy a house that appreciates in value beyond the interest rate). This is what the goal of technical debt should be, increasing the "equity" of the software.
As far as tools, any of the big git providers (GitHub, Atlassian, GitLab) generally cover most of your bases. That kind of stuff is referred to as DevOps.
The overall test coverage of the code I'm currently unit testing is 63%. This does not mean the remaining 37% will ever get tested, it means around 63% of the codebase is worth testing. What's more relevant is the individual namespaces. For example: Services is at 100% test coverage, because everything in Services actually does something worth testing. Models.DTO, that's more like 50%. I do not need to test every auto getter and auto setter.
I view test coverage like a log curve, more is better, but the returns can get very diminishing.
As far as the tool, working in C# I use JetBrains dotCover.