Sure, but when applying "simple is robust" principle it is extremely important to understand also intrinsic complexity. Not handling edge-cases etc does not make for robust code, no matter how much simpler it is.
This is where the advice in the article is excellent.
If you start with code that's easy to delete, it's often possible to alter your data representation or otherwise transform the problem in a way that simply eliminates the edge cases. With the result being a design that is simpler by virtue of being more robust.
If you start with code that's hard to delete, usually by the time you discover your edge and corner cases it's already too late and you're stuck solving the problem by adding epicycles.
Yes, but I definitely also see the opposite quite a bit: Somebody several layers down thought that something was an edge case, resolved it in a strange way, and now you have a chain of stuff above it dealing with the edge case because the bottom layer took a wrong turn.
The most common examples are empty collections: either disallowing them even though it would be possible to handle them, or making a strange choice like using vacuous falsity, i.e.
all [] == False
(Just for illustration what I mean by "vacuous falsity", Python's all correctly returns True).
Now, every layer above has to special-case these as well, even if they would be a completely normal case otherwise.
There will always be edge cases, and yes they will make the code more complicated, but what really helps is automatic testing to make sure those edge cases don't break when making changes.
Everything in balance. While I agree with this philosophy, I've also seen lots of duplicate bugs because it wasn't realized there was two copies of the same bug.
Agreed! I'll usually go one step further for early projects and lean towards 3rd time copy, 4th time refactor.
Example: So much early code is boilerplate CRUD, that it's tempting to abstract it. 9 times out of 10, you'll create a quasi-ORM that starts inheriting business logic and quickly grows omni-functions.
Eventually you may actually need this layer, assuming you're system miraculously scales to needing multiple services, datastores, and regions.
However this doesn't just apply to the obvious, and you may find omni-logic that made a feature more simple once and is currently blocking N new features.
Code is cheap, especially today. Complexity necessarily constrains, for better or worse.
+1, but I'm not sure if the "simple is robust" saying is straightforward enough? It opens up to discussion about what "simple" means and how it applies to the system (which apparently is a complex enough question to warrant the attention of the brilliant Rich Hickey).
Maybe "dumb is robust" or "straightforward is robust" capture the sentiment better?
The usual metric is complexity, but that can be hard to measure in every instance.
Used within a team setting, what is simple is entirely subjective to that set of experiences.
Example: Redis is dead simple, but it's also an additional service. Depending on the team, the problem, and the scale, it might be best to use your existing RDBMS. A different set of circumstances may make Redis the best choice.
Note: I love "dumb is robust," as it ties simplicity and straightforwardness together, but I'm concerned it may carry an unnecessarily negative connotation to both the problems and the team.
Indeed, simple is not a good word to qualify something technical. I have a colleague and if he comes up with something new and simple it usually takes me down a rabbit hole of mind bending and head shaking. A matter of personal perspective?
Can’t upvote enough. Too much dogshit in software is caused by solving imaginary problems. Just write the damn code to do the thing. Stop making up imaginary scaling problems. Stop coming up with clever abstractions to show how smart you are. Write the code as a monolith. Put it on a VM. You are ready to go to production. Then when you have problems, you can start to solve them, hopefully once you are cash positive.
Why is your “AirBnb for dogs” startup with zero users worrying about C100K? Did AWS convince you to pay for serverless shit because they have your interests in mind, or to extract money from you?
I am not sure on that. But I am certain the article Amazon published on cutting AWS bill by 90% by simplifying juvenile microservices to a dead simple monolith was deleted on accident.
Yep, to recycle a brief analysis of my own youthful mistakes:
____
I've come to believe the opposite, promoting it as "Design for Deletion."
I used to think I could make a wonderful work of art which everyone will appreciate for the ages, crafted so that every contingency is planned for, every need met... But nobody predicts future needs that well. Someday whatever I make is going to be That Stupid Thing to somebody, and they're going to be justified demolishing the whole mess, no matter how proud I may feel about it now.
So instead, put effort into making it easy to remove. This often ends up reducing coupling, but--crucially--it's not the same as some enthusiastic young developer trying to decouple all the things through a meta-configurable framework. Sometimes a tight coupling is better when it's easier to reason about. [...]
> So instead, put effort into making it easy to remove.
You might, but there's also going to be other people that will happily go ahead and create abstractions and logic that will form the very core of a project and entrench themselves to such a degree that they're impossible to get rid of.
For example, you might stumble upon CommonExcelFileParser, CommonExcelFileParserUtilities, HasExcelParseStatus, ProductImportExcelParser, ProductImportExcelParserView, ProductImportExcelParserResultHandler and who knows what else, the kind of stuff that ends up being foundational for the code around it, much like how if you start a front end project in React or Angular, migrating to anything else would be a Sisyphean task.
In practice, that means that people end up building a whole platform and you basically have to stick with it, even though some of the choices made might cause bunches of problems in the future and, due to all of the coupling, refactoring is way harder than it would be in an under-abstracted codebase.
I'm not sure what to do then. People seem to like doing that more than applying KISS and YAGNI and making code easy to delete.
Not my originals, and I cannot recall who said this... But it's completely on point
* Software has a tendency to become maximally complex. You either have an actually complex domain, or the developers will find a way to increase the complexity (..because otherwise, they're bored)
* Good software is modular and easy to remove. Consequently, good software will keep getting replaced until it's bad and cannot be removed anymore
Dealing with precisely this right now. Written by a consultant who I, maybe uncharitably, suspect is trying to ensure his job security. At this point, it is harder to even understand what's going on behind layers of handlers, factories and handler factories, forget about removing things. It works though and so no one wants to stick their neck out and call it out for the fear of being labelled "not smart".
It still depends. Business line application yes and 10x yes. It will change it will move, don’t try to foresee business requirements. Just write something that will be easy to replace or throw away.
Frameworks and libraries not really, for those you still have to adjust to whatever happens in the world but at much saner pace.
Biggest issue is when devs want to write “framework” when they work on business line application where they have frameworks that they are already using like Rails/Asp.Net etc.
I would say the biggest issue are the frameworks themselves: they practically force you to fit your code to their architecture, and before you know it, your logic is split across innumerable classes. Laravel (with which I have the most experience) has models, controllers, views, service providers, data transfer objects etc. etc. - that makes it (arguably) easier to write and extend code, but very hard to refactor/delete.
> Business line application yes and 10x yes. It will change it will move, don’t try to foresee business requirements. Just write something that will be easy to replace or throw away.
This is correct, but from my experience of working in the same company for over a decade: You'll learn to foresee requirements. Especially the "we'll never need that" ones that become business critical after a few months/years...
Pretty wild that none of this talks about testing or observability. Tests are also something that you need to pay to maintain, but they give the ability of reducing the risk that you broke something when you removed it. Additionally when you've exposed your service to potential external callers you need to both have a robust way of marking some calls as deprecated, to be deleted as well as observing whether they are still being called and by what.
I recently did our first semi-automated removal of exposed graphql resolvers, metrics about how often a given resolver was already available so parsing that yielded the set of resolvers I *couldn't* delete. Graphql already has a deprecated annotation, but our service didn't handle that annotation in any special way. I added observability to flag if any deprecated functions have been called & then let that run for sufficiently long in prod, then you can safely delete externally exposed code.
This is going to be a bit of an oversimplification but when you build things that are easy to delete, then you’re not going to cause unintentional bugs when you delete them. It’s once you over complicate things that everything becomes an interconnected mess where developers don’t know what sort of impact changes will have. There are a lot of ways to fuck this up of course. Maybe you’re following some silly “best practice” principle, maybe you’re doing “micro-services” in a manner where you don’t actually know who/what consumes which service. But then you’ve not build things that are easy to delete.
I think external consumption as you frame it is a good example of this. It’s fair to give consumers a reasonable warning about the depreciation of a service, but if you can’t actually shut it off when you want to, then you’ve not designed your system to let things be easily deleted.
Which is fair. If that works for you, then so things that way. I suspect it may not work too well if you’re relying on tests and observations to tell you if things are breaking. Not that I have anything against tests, but it’s not exactly a great safe-guard if you have to let them tell you if you broke something in a long complicated chain. Not least because you’re extremely unlikely to have test-coverage which will actually protect you.
If you write so many lines of code then you can expect some other number of lines of tests. If you delete some of the code, you may be able to delete some of the tests. The point is that you can talk about just the code like TFA does and assume related impact on tests. TFA not saying anything about tests does not let us assume that TFA means that one should not write tests.
> To write code that’s easy to delete: repeat yourself to avoid creating dependencies, but don’t repeat yourself to manage them. Layer your code too: build simple-to-use APIs out of simpler-to-implement but clumsy-to-use parts. Split your code: isolate the hard-to-write and the likely-to-change parts from the rest of the code, and each other. Don’t hard code every choice, and maybe allow changing a few at runtime.
My experience is that the title doesn't hold. Code that is easy to delete is -- more often than not -- also easy to extend because it is layered, modular, and isolates different pieces through abstractions like interfaces or other type contracts.
Personally, I split code into two parts. The business logic and actually implementation. The business logic may be duplicated due to its nature, but it should not have too many duplicated technical details in it. While the business logic can be as shitty as you want as long as you do not handle business logic directly in it and keep it application independent. In that way. If you know things messed up and don't go too well. You have the option to wipe the implementation as a whole instead of forced to fix it and try to find out the actual spec from implementation.
> The problem with code re-use is that it gets in the way of changing your mind later on.
This is simply incorrect, especially in the generality in which it is stated. If you change your mind and the code was copy-pasted to ten places, then you have to change ten places. On the other hand, if the code is in a function, then you only need to change it once. And if you do find that one of the ten invocations should not be changed, then you can still copy-paste - or make the function more general.
Like crossing a street without looking, copy-pasting is almost always a bad idea.
In my experience, bad copy pasted code results in an annoying afternoon of tech debt repayment and fixes. Badly abstracted code results in months of tech debt repayment.
Of course, the answer is “don’t make bad abstractions”, but we all know how that one goes with a team and changing product reqs.
If only that were the case on a project at work. The badly copy pasted code has diverged over the years so you have 10 different versions of the same looking code that individually have differing edge cases, half of them by mistake because they forgot about the other 9.
I would trade that for one piece of mediocre abstracted code any day.
Oh yeah and everything in the codebase is copy and pasted.
Many times the code is reused in places where it is the correct code, so then you when you change it you have to slow down and split those places up. We have a git submodule of common UI widgets, changing one of those is impossible now, easier to copy the component into the project and change it locally. It's a problem! The "shared code" needs to be as minimal as possible because the sharing makes it harder to change.
> On the other hand, if the code is in a function, then you only need to change it once. And if you do find that one of the ten invocations should not be changed, then you can still copy-paste - or make the function more general.
Ah yes, but what happens if you have to change 3 of the function invocations in one way, 5 in another, and the other two need to be completely rewritten because those aren't even using the same abstraction any more?
If it's all in one function, most developers will try to change that function to make all 10 cases work, when it should never have been one function in the first place.
It is much much easier to fix ten copy-paste places than to untangle a knot that should never have been tied, once it's holding pieces of your system together.
In a many cases I'd still
rather have three or more versions of a function, many which may just be very thin shims to accommodate that scenario than 10 copy/pastes of variations. Or shim at the call site and keep one function if that suits.
This is such a strange argument. You want to copy and paste code 10 times rather than making a function, because if the requirements change and if the person assigned to fix it is a moron, then it might prevent the moron from choosing one specific way of making a mess?
You can't prevent future morons from doing moronic stuff in the future. They'll just find another moronic thing to do.
> If you change your mind and the code was copy-pasted to ten places
The author would probably argue that you should have moved that code to a module / function.
Superficially, they contradict themselves on the topic. When read slowly, they use copy-paste as a way to indicate what code should be abstracted, and what really is a pattern to follow.
Readit News
Similar in spirit to Lehman’s Law of Continuing Change[0], the idea is that the less complexity a system has, the easier it is to change.
Rather than plan for the future with extensible code, plan for the future with straightforward code.
E.g. only abstract when the situation requires it, encourage simple duplication, use monoliths up front, scale vertically before horizontally, etc.
I’ve built many 0-1 systems, and this is the common thread among all of them.
[0] https://en.m.wikipedia.org/wiki/Lehman%27s_laws_of_software_...
If you start with code that's easy to delete, it's often possible to alter your data representation or otherwise transform the problem in a way that simply eliminates the edge cases. With the result being a design that is simpler by virtue of being more robust.
If you start with code that's hard to delete, usually by the time you discover your edge and corner cases it's already too late and you're stuck solving the problem by adding epicycles.
The most common examples are empty collections: either disallowing them even though it would be possible to handle them, or making a strange choice like using vacuous falsity, i.e.
(Just for illustration what I mean by "vacuous falsity", Python's all correctly returns True).Now, every layer above has to special-case these as well, even if they would be a completely normal case otherwise.
A rule I like to follow:
- first time: write it
- second time: copy it
- third time: maybe refactor it
Is this "the same" thing? If so - extract and reference. Or is it "a different" thing which is superficially similar? Then don't.
Knowing when two things are one thing or one thing is two things is most of our job, right?
Example: So much early code is boilerplate CRUD, that it's tempting to abstract it. 9 times out of 10, you'll create a quasi-ORM that starts inheriting business logic and quickly grows omni-functions.
Eventually you may actually need this layer, assuming you're system miraculously scales to needing multiple services, datastores, and regions.
However this doesn't just apply to the obvious, and you may find omni-logic that made a feature more simple once and is currently blocking N new features.
Code is cheap, especially today. Complexity necessarily constrains, for better or worse.
Maybe "dumb is robust" or "straightforward is robust" capture the sentiment better?
As a biomedical engineer who primarily writes software, it’s fun to consider analogies with evolution.
Copy/pasting and tweaking boilerplate is like protein-coding DNA that was copied and mutated in our evolutionary history.
Dealing with messy edge cases at a higher level is like alternative splicing of mRNA.
Used within a team setting, what is simple is entirely subjective to that set of experiences.
Example: Redis is dead simple, but it's also an additional service. Depending on the team, the problem, and the scale, it might be best to use your existing RDBMS. A different set of circumstances may make Redis the best choice.
Note: I love "dumb is robust," as it ties simplicity and straightforwardness together, but I'm concerned it may carry an unnecessarily negative connotation to both the problems and the team.
Simple isn't necessarily dumb.
Why is your “AirBnb for dogs” startup with zero users worrying about C100K? Did AWS convince you to pay for serverless shit because they have your interests in mind, or to extract money from you?
Write code that is easy to delete, not easy to extend (2016) - https://news.ycombinator.com/item?id=24989351 - Nov 2020 (30 comments)
Write code that is easy to delete, not easy to extend (2016) - https://news.ycombinator.com/item?id=23914486 - July 2020 (109 comments)
Write code that is easy to delete, not easy to extend - https://news.ycombinator.com/item?id=18761739 - Dec 2018 (2 comments)
Write code that is easy to delete, not easy to extend - https://news.ycombinator.com/item?id=11093733 - Feb 2016 (133 comments)
____
I've come to believe the opposite, promoting it as "Design for Deletion."
I used to think I could make a wonderful work of art which everyone will appreciate for the ages, crafted so that every contingency is planned for, every need met... But nobody predicts future needs that well. Someday whatever I make is going to be That Stupid Thing to somebody, and they're going to be justified demolishing the whole mess, no matter how proud I may feel about it now.
So instead, put effort into making it easy to remove. This often ends up reducing coupling, but--crucially--it's not the same as some enthusiastic young developer trying to decouple all the things through a meta-configurable framework. Sometimes a tight coupling is better when it's easier to reason about. [...]
https://news.ycombinator.com/item?id=41219130
You might, but there's also going to be other people that will happily go ahead and create abstractions and logic that will form the very core of a project and entrench themselves to such a degree that they're impossible to get rid of.
For example, you might stumble upon CommonExcelFileParser, CommonExcelFileParserUtilities, HasExcelParseStatus, ProductImportExcelParser, ProductImportExcelParserView, ProductImportExcelParserResultHandler and who knows what else, the kind of stuff that ends up being foundational for the code around it, much like how if you start a front end project in React or Angular, migrating to anything else would be a Sisyphean task.
In practice, that means that people end up building a whole platform and you basically have to stick with it, even though some of the choices made might cause bunches of problems in the future and, due to all of the coupling, refactoring is way harder than it would be in an under-abstracted codebase.
I'm not sure what to do then. People seem to like doing that more than applying KISS and YAGNI and making code easy to delete.
* Software has a tendency to become maximally complex. You either have an actually complex domain, or the developers will find a way to increase the complexity (..because otherwise, they're bored)
* Good software is modular and easy to remove. Consequently, good software will keep getting replaced until it's bad and cannot be removed anymore
Frameworks and libraries not really, for those you still have to adjust to whatever happens in the world but at much saner pace.
Biggest issue is when devs want to write “framework” when they work on business line application where they have frameworks that they are already using like Rails/Asp.Net etc.
This is correct, but from my experience of working in the same company for over a decade: You'll learn to foresee requirements. Especially the "we'll never need that" ones that become business critical after a few months/years...
Unless you’re writing the Linux kernel you shouldn’t write it like the Linux kernel.
I recently did our first semi-automated removal of exposed graphql resolvers, metrics about how often a given resolver was already available so parsing that yielded the set of resolvers I *couldn't* delete. Graphql already has a deprecated annotation, but our service didn't handle that annotation in any special way. I added observability to flag if any deprecated functions have been called & then let that run for sufficiently long in prod, then you can safely delete externally exposed code.
I think external consumption as you frame it is a good example of this. It’s fair to give consumers a reasonable warning about the depreciation of a service, but if you can’t actually shut it off when you want to, then you’ve not designed your system to let things be easily deleted.
Which is fair. If that works for you, then so things that way. I suspect it may not work too well if you’re relying on tests and observations to tell you if things are breaking. Not that I have anything against tests, but it’s not exactly a great safe-guard if you have to let them tell you if you broke something in a long complicated chain. Not least because you’re extremely unlikely to have test-coverage which will actually protect you.
> The problem with code re-use is that it gets in the way of changing your mind later on.
This is simply incorrect, especially in the generality in which it is stated. If you change your mind and the code was copy-pasted to ten places, then you have to change ten places. On the other hand, if the code is in a function, then you only need to change it once. And if you do find that one of the ten invocations should not be changed, then you can still copy-paste - or make the function more general.
Like crossing a street without looking, copy-pasting is almost always a bad idea.
Of course, the answer is “don’t make bad abstractions”, but we all know how that one goes with a team and changing product reqs.
I would trade that for one piece of mediocre abstracted code any day.
Oh yeah and everything in the codebase is copy and pasted.
Ah yes, but what happens if you have to change 3 of the function invocations in one way, 5 in another, and the other two need to be completely rewritten because those aren't even using the same abstraction any more?
If it's all in one function, most developers will try to change that function to make all 10 cases work, when it should never have been one function in the first place.
It is much much easier to fix ten copy-paste places than to untangle a knot that should never have been tied, once it's holding pieces of your system together.
In a many cases I'd still rather have three or more versions of a function, many which may just be very thin shims to accommodate that scenario than 10 copy/pastes of variations. Or shim at the call site and keep one function if that suits.
You can't prevent future morons from doing moronic stuff in the future. They'll just find another moronic thing to do.
The author would probably argue that you should have moved that code to a module / function.
Superficially, they contradict themselves on the topic. When read slowly, they use copy-paste as a way to indicate what code should be abstracted, and what really is a pattern to follow.