This article is very rambling and somehow manages to miss the most important driver of reduced software quality: shifting requirements.
You can have the most beautiful perfect design that leverages the greatest abstractions in the world, and then have it all entirely destroyed by a single requirement shift that totally kills your abstractions.
That's a refutation of agile, Vibe Coding and the last 25 years of the software industry.
One of my own quality metrics that almost everyone rejects is a "a good design is a design where a change that seems like a small change to management is... a small change"
It plays out like this. To get to product-market fit you are going to have to zig and zag 20 times. Everybody optimizes for the first step of this journey and then on the second step they optimize for that... and by step 5 or so the archiecture is exhausted and you have no hope of getting to step 20. The rare team that is looking ahead 20 steps is the one that survives.
>It plays out like this. To get to product-market fit you are going to have to zig and zag 20 times. Everybody optimizes for the first step of this journey and then on the second step they optimize for that... and by step 5 or so the archiecture is exhausted and you have no hope of getting to step 20.
It not being "exhausted" is just what distinguishes a good programmer from a bad one. If you're good you can keep a lid on tech debt in the face of rapidly changing requirements. If you suck at it, well... you can't.
>The rare team that is looking ahead 20 steps is the one that survives.
lol no good software engineering means assuming that you don't have a crystal ball and building accordingly.
This usually means YAGNI, minimizing up front design and refactoring aggressively.
The problem is that you don't know in advance what the 20 steps will be, and you may spend time solving the wrong problem.
Make step 1 as simple as possible, step 1 is small and changes are cheap, you can even rewrite everything with little effort, no need to prepare for anything at this point.
Step 2-4 will inevitably break something, no big deal, rewrite the parts that need to be rewritten, it is still cheap.
At step 5 rewrites are starting to get costly, but now you have a better idea of what is here to stay, so it is now time to invest in things like regression testing, style guides, etc...
At step 10, you have quite a history, rewrites become a really bad idea, no turning back after that. So now it is time to think about the future. The difference from doing that in step 1 is that you now have 10 steps of experience and only need to look ahead 10 steps.
Then I guess no design is good. Here's an easy example: take any software system you can think of. Let's add a single new requirement: it must produce an output in 1us. I'll bet your system has to change.
Well that's a pretty contrived example. There are fair amount of requirements that can be predicted as "possibly coming" in a given problem space, and a good design typically takes them into consideration and plans contingencies such that a design doesn't crumble.
It's extreme to demonstrate the point, but it's not contrived. Realtime deadlines are a completely normal requirement for the systems I work on. I have change reqs on my desk right now that specify a full reboot back to network responsiveness in <=300ms. That definitely changes how the system is designed.
Right, the point is that GP's definition should take the nuance you mention into account (namely, that some types of changes are more likely, and thus more important to handle nicely, than others).
I think you are interpreting his claim in the most extreme possible way. You are doing the equivalent of asking a civil engineer what if his bridge needs to support flying cars, or weight half as much while carrying ten times the load. Of course there are architecture breaking requirements, but his point still stands for reasonable and foreseeable changes. If it doesn't survive that, then it wasn't a good design begin with.
Completely untrue. Every design can be destroyed by a single poorly-thought out requirement. I can take down Facebook's design just by saying "any edit must immediately be visible to all users".
You would have liked the last place I worked before retirement. Full-on software test team and everything. Private offices, too. Don't get me wrong, there were warts (oh, were there warts), but overall it was a good time. It wasn't a 70% pay cut, but the cut was considerable in comparison to what I was accustomed to. I didn't care, I was nearing retirement, and my "I'd take a pay cut if..." was the aforementioned private office.
But the company got sold to a conglomerate before I left, so I can't guarantee that culture is still there.
Gene Kim wrote the DevOps Handbook and I think was at least involved in the related DORA and Phoenix Project and Unicorn Project office narrative books. Between those and the Google SRE book, I feel very well placed to have continuing value in the SDLC pipeline for wrangling the oncoming armies of Jr Developers-as-AI-agents-and-sometimes-humans into alignment. I also recommend System Design Interview 1 and 2 books by Xu for logical system design refurbishment, Designing Data Intensive Applications for most company programs, and Hexagonal Architecture Explained by Cockburn for finally getting something as small as a class or module to something as large as an entire Information System to have clear modular boundaries, without needing to do fuzzy pattern matching around half-remembered SOLID principles and GoF design patterns or trying to blindly apply 12 factor app design principles.
Quality used to take a back seat because there was so much legwork to do. AI has reduced the cost to be excellent, so let's be as excellent as our environments let us.
Great book recommendations (I have read parts of the Google SRE book and Designing Data Intensive Applications)! I will also add a couple gems that I don't see often-cited: Simple Object-Oriented Design by Mauricio Aniche and Secure by Design by Dan Bergh Johnsson, Daniel Deogun, and Daniel Sawano. Both have a lot to offer in terms of software design and maintaining complexity. I also liked Refactoring to Patterns by Joshua Kerievsky.
This article is very rambling and somehow manages to miss the most important driver of reduced software quality: shifting requirements.
You can have the most beautiful perfect design that leverages the greatest abstractions in the world, and then have it all entirely destroyed by a single requirement shift that totally kills your abstractions.
well you cannot design for the unpredictable, but well designed code will make refactoring easier anyways
If the design is so inflexible that a single requirement shift destroys it, then it wasn't a good design.
That's a refutation of agile, Vibe Coding and the last 25 years of the software industry.
One of my own quality metrics that almost everyone rejects is a "a good design is a design where a change that seems like a small change to management is... a small change"
It plays out like this. To get to product-market fit you are going to have to zig and zag 20 times. Everybody optimizes for the first step of this journey and then on the second step they optimize for that... and by step 5 or so the archiecture is exhausted and you have no hope of getting to step 20. The rare team that is looking ahead 20 steps is the one that survives.
>It plays out like this. To get to product-market fit you are going to have to zig and zag 20 times. Everybody optimizes for the first step of this journey and then on the second step they optimize for that... and by step 5 or so the archiecture is exhausted and you have no hope of getting to step 20.
It not being "exhausted" is just what distinguishes a good programmer from a bad one. If you're good you can keep a lid on tech debt in the face of rapidly changing requirements. If you suck at it, well... you can't.
>The rare team that is looking ahead 20 steps is the one that survives.
lol no good software engineering means assuming that you don't have a crystal ball and building accordingly.
This usually means YAGNI, minimizing up front design and refactoring aggressively.
The problem is that you don't know in advance what the 20 steps will be, and you may spend time solving the wrong problem.
Make step 1 as simple as possible, step 1 is small and changes are cheap, you can even rewrite everything with little effort, no need to prepare for anything at this point.
Step 2-4 will inevitably break something, no big deal, rewrite the parts that need to be rewritten, it is still cheap.
At step 5 rewrites are starting to get costly, but now you have a better idea of what is here to stay, so it is now time to invest in things like regression testing, style guides, etc...
At step 10, you have quite a history, rewrites become a really bad idea, no turning back after that. So now it is time to think about the future. The difference from doing that in step 1 is that you now have 10 steps of experience and only need to look ahead 10 steps.
Then I guess no design is good. Here's an easy example: take any software system you can think of. Let's add a single new requirement: it must produce an output in 1us. I'll bet your system has to change.
Well that's a pretty contrived example. There are fair amount of requirements that can be predicted as "possibly coming" in a given problem space, and a good design typically takes them into consideration and plans contingencies such that a design doesn't crumble.
It's extreme to demonstrate the point, but it's not contrived. Realtime deadlines are a completely normal requirement for the systems I work on. I have change reqs on my desk right now that specify a full reboot back to network responsiveness in <=300ms. That definitely changes how the system is designed.
It being extreme is what makes it contrived.
It's also a requirement programmers often overemphasise due to the McNamara fallacy.
Right, the point is that GP's definition should take the nuance you mention into account (namely, that some types of changes are more likely, and thus more important to handle nicely, than others).
I think you are interpreting his claim in the most extreme possible way. You are doing the equivalent of asking a civil engineer what if his bridge needs to support flying cars, or weight half as much while carrying ten times the load. Of course there are architecture breaking requirements, but his point still stands for reasonable and foreseeable changes. If it doesn't survive that, then it wasn't a good design begin with.
Completely untrue. Every design can be destroyed by a single poorly-thought out requirement. I can take down Facebook's design just by saying "any edit must immediately be visible to all users".
If there is a place that is hiring and cares about Software Quality, I'll take a 70% paycut to work there.
You would have liked the last place I worked before retirement. Full-on software test team and everything. Private offices, too. Don't get me wrong, there were warts (oh, were there warts), but overall it was a good time. It wasn't a 70% pay cut, but the cut was considerable in comparison to what I was accustomed to. I didn't care, I was nearing retirement, and my "I'd take a pay cut if..." was the aforementioned private office.
But the company got sold to a conglomerate before I left, so I can't guarantee that culture is still there.
Why are people so reticent to name companies, even when they're praising them?
It can be seen as dark advertising. Because it is.
I've just accepted the fact that every tech company is just a dumpster fire.
Gene Kim wrote the DevOps Handbook and I think was at least involved in the related DORA and Phoenix Project and Unicorn Project office narrative books. Between those and the Google SRE book, I feel very well placed to have continuing value in the SDLC pipeline for wrangling the oncoming armies of Jr Developers-as-AI-agents-and-sometimes-humans into alignment. I also recommend System Design Interview 1 and 2 books by Xu for logical system design refurbishment, Designing Data Intensive Applications for most company programs, and Hexagonal Architecture Explained by Cockburn for finally getting something as small as a class or module to something as large as an entire Information System to have clear modular boundaries, without needing to do fuzzy pattern matching around half-remembered SOLID principles and GoF design patterns or trying to blindly apply 12 factor app design principles.
Quality used to take a back seat because there was so much legwork to do. AI has reduced the cost to be excellent, so let's be as excellent as our environments let us.
Great book recommendations (I have read parts of the Google SRE book and Designing Data Intensive Applications)! I will also add a couple gems that I don't see often-cited: Simple Object-Oriented Design by Mauricio Aniche and Secure by Design by Dan Bergh Johnsson, Daniel Deogun, and Daniel Sawano. Both have a lot to offer in terms of software design and maintaining complexity. I also liked Refactoring to Patterns by Joshua Kerievsky.
Previously...
How to think about software quality (2022) - https://news.ycombinator.com/item?id=39490543 - Feb 2024 (66 comments)
Testing is not "Quality Assurance".
If I got nothing else out of TFA, at least I could raise my hands and shout an "amen!".
That’s great, but how do I fix my motorcycle?
Maybe we could take a page from the SWEBOK here, which contains a lot of previous thinking on this topic.
(2022)
(edited 2023) agreed mods should append a year given how fast things have been changing
Hey Siri, is my app doing what I wanted it to do?
Siri: Yes, but each action takes 10 minutes to resolve and your users are jumping out of their windows after dealing with your software.
Programmer: Great, my software works!
Hey Siri, my software isn't doing what I wanted it to do. Confirm PRD did not include 10 minute wait times and send my IQ test results again please.