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Some people think that the notion of classes is intrinsic to object-oriented programming. Bertrand Meyer even wrote a textbook about OOP called A Touch of Class. But back in the 1980s, Alan Borning and others were trying to teach object-oriented programming using the Smalltalk system, ostensibly designed to make simulation in computer programmers accessible to children. What they found was that classes are hard.
You’re not allowed to think about how your thing works before you’ve gone a level of abstraction up and told the computer all about the essence of thing-ness, what it is that’s common to all things and sets them apart from other ideas. And while you’re at it, you could well need to think about the metaclass, the essence of essence-of-thing-ness.
So Borning asked the reasonable question: why not just get rid of classes?. Rather than say what all things are like, let me describe the thing I want to think about.
But what happens when I need a different thing? Two options present themselves: both represent the idea that this thing is like that thing, except for some specific properties. One option is that I just create a clone of the first object. I now have two identical things, I make the changes that distinguish the second from the first, and now I can use my two, distinct things.
The disadvantage of that is that there’s no link between those two objects, so I have nowhere to put any shared behaviour. Imagine that I’m writing the HR software for a Silicon Valley startup. Initially there’s just one employee, the founder, and rather than think about the concept of Employee-ness and create the class of all employees, I just represent the founder as an object and get on with writing the application. Now the company hires a second employee, and being a Silicon Valley startup they hire someone who’s almost identical to the founder with just a couple of differences. Rather than duplicating the founder and changing the relevant properties, I create a new object that just contains the specific attributes that make this employee different, and link it to the founder object by saying that the founder is the prototype of the other employee.
Any message received by employee #2, if not understood, is delegated to the original employee, the founder. Later, I add a new feature to the Silicon Valley HR application: an employee can issue a statement apologising if anybody got offended. By putting this feature on the first employee, the other employee(s) also get that behaviour.
The year is 2017 and people are still recommending processing out assertions from release builds.
many assertions are short tests (whether or not that’s a good thing): this variable now has a value, this number is now greater than zero), which won’t cost a lot in production. Or at least, let me phrase this another way: many assertions are too cheap to affect performance metrics in many apps. Or, let me phrase that another way: most production software probably doesn’t have good enough performance monitoring to see a result, or constrained enough performance goals to care about the result.
The program counter has absolutely no business executing the instruction that follows a failed assertion, because the programmer wrote the subsequent instructions with the assumption that this would never happen. Yes, your program will terminate, leading to a 500 error/unfortunate stop dialog/guru meditation screen/other thing, but the alternative is to run…something that apparently shouldn’t ever occur. Far better to stop at the point of problem detection, than to try to re-detect it based on a surprising and unsupportive problem report later.
assertions are things that programmers believe to always hold, and it’s sensible to take issue with the words always and believe. There’s an argument that goes:
- I have never seen this situation happen in development or staging.
- I got this job by reversing a linked list on a whiteboard.
- Therefore, this situation cannot happen in production.
but unfortunately, there’s a flaw between the axioms and the conclusion. For example, I have seen the argument “items are added to this list as they are received, therefore these items are in chronological order” multiple times, and have seen items in another order just as often. Assertions that never fire on programmer input give false assurance.
Seen on the twitters:
1) Bad reasons why tech startups have incredibly large mobile teams even though from an engineering perspective they don’t need it.
This is the No True Scotsman fallacy, as no true software department needs more than, say, 20 people.
I’m not going to get into the details of what you do with hundreds of mobile engineers. Suffice it to say that the larger-team apps I’ve worked on have been very feature rich, for better or worse. And that’s not just in terms of things you can do, but in terms of how well you can do them. When you in-source the small details that are important to your experience, they become as much work to solve as the overall picture.
Make a list of the companies that you think have “too big” a mobile software development team. Now review that list: all of those companies are pretty big and successful, aren’t they? Maybe big enough to hire a few hundred developers to work on how their customers access their products or services? No true software department needs to be that successful.
And that’s what I think of as the underlying problem with the “your team’s too big, you’re doing it wrong” fallacy: it’s part of the ongoing narrative to devalue all software. It says that your application can’t possibly be worth enough to spend all that developer time on. After all, mine isn’t, and I’m a true software developer.
I’ve said it before, build systems are a huge annoyance. If your build is anything other than seemingly instantaneous, it’s costing you severe money.
Your developers are probably off reading HN, or writing blog posts about how slow builds cost them, while the build is going. When they finish doing that, which may be some time after the build completes, they’ll have forgotten some of what they were doing and need to spend some time getting back up to speed.
Your developers are probably suspicious of any build failure, thinking that “the build is flaky” rather than “I made a mistake”. They’ll press the button again and go back to HN. When the same error occurs twice, they might look into it.
Your developers probably know that the build is slow, but not which bit of the build is slow. And they don’t have time to investigate that, where it takes so long to get any work done anyway. So everyone will agree that “there is a problem”, but nothing will get done. Or maybe cargo-cult things will get done, things that speed up “builds” but are not the problem with your build.
The Joel test asks whether you can make a build in one test. Insufficient. If you notice when you’re making a build, you’re slowing your developers down.
…which is not always the worst thing, of course. Sometimes a lengthy translation step from some source language to some optimised form of a machine language program yields better results for your customers, because they get to use a faster program and don’t need to care about the time taken to prepare that program. But let’s be clear: that’s part of the release, and your developers don’t always need to be working from the released product (in fact, they’re usually not). Releases should be asynchronous, and the latency between having something ready to be released and having released it can be fairly high, compared with the latency between having created some source and being able to investigate its utility.
Nonetheless, that should all go off in the background. So really, builds and releases should both be non-events to the developers.