This struck a chord with me: "Software Is about Developing Knowledge More than Writing Code"
I've experienced more issues caused by management passing around tasks between teams and never paying attention to knowledge and knowledge transfer.
What's amazing, is that in over 18 years as a software engineer, I've seen this so many times. Teams will function well, then the institution tries to change. Often they will try to open up the "innovation" by throwing money at R&D, basically trying to add bodies in order to grow. Then you have tons of teams, and communication becomes very challenging, so then they grow some kind of "task management" layer. Management that never understands who actually _knows_ something, just tracks how much "theoretical bandwidth" they have and a wishlist of features to create. And then the crapware really starts flowing. And then I get bored and move on to the next place.
> "Software Is about Developing Knowledge More than Writing Code"
The company I work for uses Scrum. They consider the User Stories + the code to be everything you need. I struggle with this, but my manager says they don't want to get tied up doing documentation "because it goes out of date". Beside, they are being Agile which "prefers working code over comprehensive documentation".
I am wondering what other companies do to capture this "distilled knowledge". The backend services I rely on are undocumented beside some paltry swagger that leaves much to be desired. The front end has no product-level "spec", if you want to rebuild the thing from scratch. There isn't even a data dictionary, so everyone calls the same thing by different terms (in code, and conversation).
There are just user stories (thousands) and code.
Does anyone have any suggestions on how to fix this?
+ 1 Yes, things really changed for me once I started to ask why we implement things. Tried to understand the manager/customer/stakeholder what is their domain? What kind of issue they want to solve? What is the business case we are working on?
I know as a software developer you don't want to do that. More fun refactoring code than dealing with management. More fun writing that piece of SQL than sitting in a meeting. Easier to whine about missing specifications than to understand the big picture.
Once I stepped back from coding and looked at the software from a birds eye view, I had actually a much easier time programming features than before. More knowledge, less writing code.
Haha yeah the number of times I've gotten "Hey someone estimated a task would take 40 hrs on a project you've never seen with libraries you've never touched. mind knocking that out this week?" is astounding.
The first place I worked as a software dev had an owner that would explain everything about the business and the problems to me in very good detail. He would just stop by my desk whenever he thought of something he thought might be good for me to know. Eventually understanding the business became just as interesting as the coding. These days, I hate getting a task without knowing the business side of things or not being able to discuss it directly with the person that does.
Some good tidbits from the government perspective on software development:
“Beware of bureaucratic goals masquerading as problem statements. “Drivers feel frustrated when dealing with parking coupons” is a problem. “We need to build an app for drivers as part of our Ministry Family Digitisation Plans” is not. “Users are annoyed at how hard it is to find information on government websites” is a problem. “As part of the Digital Government Blueprint, we need to rebuild our websites to conform to the new design service standards” is not. If our end goal is to make citizens’ lives better, we need to explicitly acknowledge the things that are making their lives worse.”
It's not that they have the knowledge but that the knowledge is now encoded in software and available to anyone else - software shares knowledge without the users having to learn it (for example having to learn which five systems need to have their names enters in order to pay their parking fine
> Reusing software lets you build good things quickly
It also introduces unknown amounts of debt and increases the likelihood that you'll end up with intractable performance/quality/velocity problems that can only be solved by re-writing large portions of your codebase.
This can be a dangerous cultural value when it's not presented with caution, which it isn't here. I think it's best to present it alongside Joel Spoelsky's classic advice: "If it’s a core business function — do it yourself, no matter what".
If it’s a core business function — do it yourself, no matter what.
Pick your core business competencies and goals, and do those in house. If you’re a software company, writing excellent code is how you’re going to succeed. Go ahead and outsource the company cafeteria and the CD-ROM duplication. If you’re a pharmaceutical company, write software for drug research, but don’t write your own accounting package. If you’re a web accounting service, write your own accounting package, but don’t try to create your own magazine ads. If you have customers, never outsource customer service.
```
This all rings true in my experience. You should write the software that's critical to your core business competency yourself, because the maintenance cost is worth paying if you can achieve better software. But if it's not a core competency and your business isn't directly going to benefit from having best in class vs good enough, then it may be worth outsourcing.
I agree completely. Dependencies solve problems but not for free - bugs, security issues, versioning headaches, performance problems, compatibility gotchas, churn, &c. I live by the following:
(1) If a problem can be exhaustively specified in a formally well-defined way (mathematical logic), it will be wise to adopt a mature implementation - if it exists.
(2) If a problem can't be so specified, all implementations will be incomplete and will contain trade-offs. I have to address these problems myself to ensure that limits and trade-offs suit as well as possible what the business needs. If I can.
So, (1) says I shouldn't parse my own JSON. (2) says I should avoid the vast majority of what shows up in other people's dependency trees.
I found this to be an incredibly accessible and easy to read guide for software development. It’s a very short read - just a few minutes - but it’s full of practical examples and written in a way that speaks to non-engineers (like bureaucrats). If you are a non-technical person handling software stuff, this article should definitely be high on the reading list.
The author seems like an unknown in the software development world, but they’re one of the managers for Singapore’s fairly successful digital government initiative. So it does feel safe to say they have some experience.
Li Hongyi is the son of Singapore PM Lee Hsien Loong, as well as a deputy director in GovTech Singapore (the Government Technology Agency). (He's also an MIT CS grad, and a past Googler.)
I suppose he wrote this for other people in the Singapore civil service.
Nice post! Agreed on keeping the initial stuff simple as possible.
In python, I typically follow a pattern of keeping stuff in __name__ == '__main__' block and running it directly, then splitting to functions with basics args/kwargs, and finally classes. I divide into functions based on testability btw. Which is another win, since functional tests are great to assert against and cover/fuzz with pytest.mark.parameterize [1]
If the content of this post interested you: Code Complete: A Practical Handbook of Software Construction by Steve McConnell would make good further reading.
I prefer putting the main code into a "main" function (called from the __name__ == '__main__' block) fairly early, since otherwise the functions you extract might accidentally keep relying on global variables.
> I have taught my children never to mention or flaunt their relationship to their grandfather, that they needed to make their own way in the world only on their own merits and industry.
Regarding "Seek Out Problems and Iterate", it's a bit of an understatement how important this is. I've invested a lot of time helping my coworkers understand the distinction between tasks and problems. The end goal being only tracking problems in the ticketing system. It's not easy to do this and it takes constant effort, but it pays off very quickly. I've yet to see a real "problem" ticket stay unresolved for a long time, whereas "task" tickets tend to stay around until they're either irrelevant or they get closed after getting kicked between a few people.
A good example of this is:
- Add worker thread for X to offload Y
When the actual problem is more along the lines of:
- Latency spikes on Tuesdays at 3pm in main thread
Which may be caused by a cronjob kicking off and hogging disk IO for a few minutes.
A good rule of thumb I've found is that task tickets tend to have exactly one way of solving them, whereas problem tickets can be solved in many ways.
Can you explain the 3pm on Tuesdays issue? My sister works for LLS and she said their servers get very slow at a precise time every Tuesday. Not saying it's the same bug, but what was the solution in your specific case?
Building good software requires mainly achieving two things:
1. Making sure what you build is what was really requested (correct), and
2. Making sure what you've built doesn't have a higher running "cost" than the thing it replaced (either manual process or old automated solutions).
Everything else, IME, is ancillary. Performance, choice of platform, frameworks, methodology to build, maintainability etc are sub-objectives and should never be prioritized over the first two objectives. I have worked on many projects where the team focussed mostly on the "how to build" parts and have inevitably dropped the ball on the "what" to build of the projects. Result: failure.
Sauce: personal experience with several years of different projects (n = 1; episodes = 20+ projects that have gone live and have remained live versus 100+ projects lying by the wayside).
I agree with you but what I've noticed is for all the large projects I've worked on it was impossible to get an official answer as to whether or not the whole endeavor had a positive ROI. In fact, with a little back of the napkin math and some knowledge of the project's resource allocation it was obvious in most cases there would not ever be a positive ROI.
This is where most companies fail. Yes, they do want the best developers, but for the budget of an average junior/medior dev.
For some reason most companies/managers I worked for do not understand the financial impact of a not so good developer. Or the other way around; they fail to value the best developers and are unable recognize them.
I've worked for plenty companies where they let mediocre dev's build a big app from scratch (including the architecture), in an Agile self managed team.. These are the codebases that always need to be rewritten entirely because they have become an unmanageble buggy mess of bad ideas and wrong solutions.
I've worked for companies where supposed senior devs write a massive amount of code without even the slightest indepth thought because they think they know everything.
Then the project turns out to be months late, even though I called the timeline of the project virtually unfeasible, and we have to go back and make several changes that could've been caught early on with a better strategy.
The problem with hiring the "best" engineers is as follows:
1. Nobody can ever tell you what the best means. People just throw 10x around without any explanation.
2. Most people in the world are average. You simply don't have enough of the best people to handle the work load, even if they're 10x average. So much existing software and new problems exist that it's nigh impossible to have the best everywhere.
3. Many of the best people are able to write really good code, but they consider it so easy that they often write code that they think is correct and it gets put in production. Since they're loners, they often don't do the necessary leg work either because of their own arrogance, or because the company hasn't clearly defined its processes and the developer can't even reach this goal despite numerous efforts. So management just believes the code is correct without any verification.
4. Many average developers support the best ones by taking needed work away from them through comparative advantage. Just because X employee is awesome at Y task, doesn't mean he meets the highest utility by doing Y task all the time. Especially when there are conflicting priorities.
5. The best engineers aren't going to be working at a small company in most cases. They also aren't likely to be paid well outside a large company either. The article sites Google, Facebook, and all the large tech companies and their supposed stringent interview process as a reason. But these companies have written terrible software (Google+, AMP pages) and become ethically compromised easily. Plus their interview process is often so outside the daily work flow because it involves answering algorithm questions, that it often makes no sense. Even worse, it teaches people to do katas instead of build actual projects. Project based interviews make much more sense.
6. Rewriting code bases is one of the worst things you can do and is what caused Netscapes downfall. Companies with supposedly the best engineers (ie. Netscape), can't even do it well.
So while hiring the best engineers is an awesome goal. It isn't feasible in a lot of cases.
I admit I have some bias as I consider myself pretty average. But I do a lot of crap on the side that "10x devs" don't even hear about because they're working on something more urgent. Does that mean I'm worthless?
One of the principles the article highlights is that additional features make a software complex and therefore more likely to fail. This is true, but I'd argue it's not for the reason the article claims.
The claim is:
> Stakeholders who want to increase the priority for a feature have to also consider what features they are willing to deprioritise. Teams can start on the most critical objectives, working their way down the list as time and resources allow.
In other words, the argument is "competing priorities in a large-scale project make it more likely to fail, because stakeholders can't figure out which ones to do first." Actually, in this very paragraph, the author glosses over the real issue: "Teams can start on the most critical objectives, working their way down the list" - treating development as an assembly line input-to-output process.
I argue that it's not time constraints that complex programs bad, but instead the mere act of thinking that throwing more developers at the work will make it any better. Treating the application as a "todo list" rather than a clockwork of engineering makes a huge difference in the quality of the work. When developers are given a list of customer-facing features to achieve, more often than not the code winds up a giant ball of if-statements and special cases.
So yes, I do agree that complex software is worse and more prone to failure than simple software - but not for the reason that there's "too much to do" or that prioritizing is hard. Complex software sucks because it's requirement-driven, instead of crafted by loving hands. No one takes the time to understand the rest of the team's architecture or frameworks when just throwing in another special case takes a tenth of the time.
I’ve also seen the failures in requirement driven software. When engineers receive unfiltered customer requests as requirements or tasks they tend to focus simply on getting that functionality into the software. Most times not understanding the job the customer is trying to get done.
There are different personalities of engineers, those who thrive on explicit requirements and can accomplish difficult engineering tasks when they are given clear requirements. But those engineers should only be given those requirements once the job that the customer is trying to get done is clearly understood. Some engineers have the ability to find creative solutions, that customers or product managers can’t see, when they are provided with problems and jobs rather than requirements and tasks.
Managers would be wise to distinguish between the type of engineers they are managing and play to their strengths. Whatever type you have, understanding the job the end user is trying to get done must occur, preferably by an engineer that’s capable of articulating that, if needed, to team members as technical requirements.
I argue that it's not time constraints that complex programs bad,
but instead the mere act of thinking that throwing more developers
at the work will make it any better.
The bit about throwing more developers is true, but really does not follow from anything else you or the author is talking about.
Treating the application as a "todo list" rather than a clockwork
of engineering makes a huge difference in the quality of the work.
When developers are given a list of customer-facing features to achieve,
more often than not the code winds up a giant ball of if-statements
and special cases.
Admittedly, this is often the case when doing feature-driven development.
But it absolutely does not need to be the case.
If you treat engineers as interchangeable cogs who only need to know about one story at a time, and never tell them about the medium- and long-term goals of the business and the application? Then yes. Then you get an awful code base with tons of if-then crap.
However, it doesn't need to be this way. If you give engineers visibility into (and some level of empowerment with regard to) those longer-term goals, they can build something more robust that will allow them to deliver features and avoid building a rickety craphouse of special cases.
> In other words, the argument is "competing priorities in a large-scale project make it more likely to fail, because stakeholders can't figure out which ones to do first."
This is a misinterpretation of the article's claim. The article very explicitly begins by saying that the best recipee to increase a project's chances to success is to:
> 1. Start as simple as possible;
> 2. Seek out problems and iterate;
The priority part reads to me as a way to determine which features are critical (and hence part of the as simple as possible set) and which ones are not (and hence you should not build "yet"). The underlying vibe being that these other features should probably never get implemented because once the critical ones get built and the software is put to use you will actually find other critical fearures that solve actual problems found through usage.
That is, only when you find that one of the initially non-critical features has become a hindrance for users actually using your software you should seek to implement it.
I really think this would be a better way to build software, just as much as I think that you will have a very very hard time getting any management on board with it...
I've personally been thinking about this for some time and wondering if in the real world this looks like building as much as possible at the database level and treating your DB as a state machine for your app, aiming to disallow whole classes of errors and communicating the design of the business logic at the SQL functions/triggers/data layer, separate from the API, Services, Programming Language, and Frontend layer(s).
This means that instead of lots of issues with business logic being separate from the data the business logic and data sit together and prevent your system from getting into bad states.
Thinking about this, maybe I just stole this thought from Derek Sivers: https://sivers.org/pg
Yes, the data model is probably the most important aspect of your application, it defines the relations and constraints. With a good data model, you don't need to write a lot of code to deal with it. Having lots of code that deals with weird situations in the database means your data model needs some serious consideration.
A database in my opinion is not a good place to write business logic with functions and triggers, since there is lack of tooling that would make development and debugging easy. Let the database do what it does well, which is storing and querying data.
All very good points. Don't write code, solve the problem. For that, first understand the problem. Take time to reduce complexity, else you won't be able to evolve. Gather knowledge along th he way.
This all takes a bird-eye view and a long perspective, very unlike quarter-results-driven development.
This is great. So many quotable quotes. If only we could make it required reading for our clients!
This one struck me, because as soon as I read it I knew it was true yet had never considered it:
> Most people only give feedback once. If you start by launching to a large audience, everyone will give you the same obvious feedback and you’ll have nowhere to go from there.
I've been on both sides of that fence and it rings true.
>>> The hard limit to system complexity is not the quantity of engineering effort, but its quality.
This article is full of good ideas, an antidote to creeping corporate take over of software projects - make this required reading for software projects.
The initial proposition of the article, that software is bad because it follows the lifecycle "gather requirements - write software - deliver it" is simply wrong. There are huge projects in specialized domains that are delivered on time and on budget and use this approach.
The problem is lack of knowledge. The successful projects mentioned above did not have a lack of knowledge, and so they were finished successfully.
When there is a lack of knowledge, then it makes sense to use the iterative approach...as knowledge is slowly gathered, the software gets improved. As with all things in life!
I like the article, it gets to the point. I would, however, change this: " 3. Hire the best engineers you can." to: "3. Hire and work hard to keep the best managers and engineers you can." As they mention, accumulating knowledge is important. Keeping that knowledge around is therefore also important (and sometimes difficult). The best managers will know what technical debt is, how to handle pressure from higher-ups, and how to keep a team happy, healthy and productive.
Years ago I wrote http://oss4gov.org/manifesto saying that governments needed to not only embrace OSS but that it is the only moral option to take.
Now we have government digital systems leading the charge across most western countries, and we have excellent polemics like this. I am just so happy to see this level of insightful ness at top levels of government.
> Overall, good engineers are so much more effective not because they produce a lot more code, but because the decisions they make save you from work you did not know could be avoided.
This is spot on, and very much my experience (of the good engineers I've come across).
Kind of : management had planned extensive and painful testing of a component that turned out to be discarded entirely (not because of functionality reduction but because it was actually unecessary).
>The better your engineers, the bigger your system can get before it collapses under its own weight. This is why the most successful tech companies insist on the best talent despite their massive size.
Translation: the successful tech companies have so much poorly documented legacy enterprise spaghetti code and tooling that they need the best talent they can get just to make sense of it and maintain it
Alternate translation: Bad devs are worse than no devs and all your competent devs will spend most of their time dealing with the former's crappy code until they quit. (my code is of course perfect and free of all technical debt)
The article lists the characteristics of a good engineer:
* has a better grasp of existing software they can reuse
* (has) a better grasp of engineering tools, automating away most of the routine aspects of their own job
* design systems that are more robust and easier to understand by others
* the decisions they make save you from work you did not know could be avoided
I obviously concord with the analysis (not sure about the 10X myth). It also states that:
* Google, Facebook, Amazon, Netflix, and Microsoft all run a dizzying number of the largest technology systems in the world, yet, they famously have some of the most selective interview processes
This sounds a bit like a paradox to me. Given the current state of "selective interview processes" (algo riddles, whiteboard coding, etc.), none of the above traits can be easily evaluated in a candidate during an interview. On the other hand, these companies do hire stellar engineers: the technological supremacy of FAANG is irrefutable.
Google views picking new engineers like picking quality construction metals. In the end, the machine melts you down and hammers you into a pristine cog.
The way I interpreted that last comment was as a counterpoint to the idea that large companies necessarily end up hiring many mediocre employees because the talent pool simply isn't deep enough to stack the deck. Instead of just being happy with what they can get, the big tech companies make it a real challenge to be hired.
It's not a paradox because the statement that the interview processes don't evaluate candidates is false. It's proven that this particular interview format has a very high correlation with the future candidate's performance.
Excellent article, well grounded in the reality of software development. New developers and managers would benefit from understanding the practical points made here as early as possible.
I do think perhaps there is too much emphasis on reuse and particularly cloud services. Ironically, this is partly for the reasons given elsewhere in the article. If you rely on outsourcing important things, you also naturally outsource the deep understanding of those important things, which can leave you vulnerable to problems you didn't anticipate. Also, any integration is a source of technical debt, so dependencies on external resources can be more fragile than they appear, and if something you rely on changes or even disappears then that is a new kind of potentially very serious problem that you didn't have to deal with before. Obviously I'm not advocating building every last thing in-house in every case, but deciding when to build in-house and when to bring something in can be more difficult than the article here might suggest.
> Software has characteristics that make it hard to build with traditional management techniques
Perhaps some software development techniques would work though...
> The main value in software is not the code produced, but the knowledge accumulated by the people who produced it.
Those people go on to work on other things or for other organization. So, while that statement might have some truth to it, it's still the case that the code has to be useful, robust, and able to impart knowledge to those who read it (and the documentation).
> Start as Simple as Possible
That's a solid suggestion to many (most?) software projects; but - if your goal is to write something comprehensive and flexible, you may need to replace it with:
"Start by simplifying your implementation objectives as much as possible"
and it's even sometimes the case that you want to sort of do the opposite, i.e.
"Start as complex as possible, leading you to immediately avoid the complex specifics in favor of a powerful generalization, which is simpler".
> > Software has characteristics that make it hard to build with traditional management techniques
> Perhaps some software development techniques would work though...
As you go up the management chain, you usually run into some layer where people are traditional managers, who want to run a software project like a traditional project. And behold, you're at this problem. Saying "software development techniques would work" is useless unless you can get those managers to change. And when you get them to change, the problem moves up one layer.
When faced with a standard solution, use a standard component if you can. If you can't use a standard component, build a standard component. Keep your components simple, well-understood, and easy to maintain.
Hiring the best engineers, technically-wise, is a good thing but it's not enough. In my experience it's better to hire somebody with a previous experience in the domain. Somebody that already built something similar or related. Those engineers will ask the right questions, make the customer think about the system in the right way, not lose time on worthless details. Even if the implementation is not shiny it will be working. It beats shiny but misguided. And if you can find great engineers with great skills, that's even better.
After a brief visit and further readings, I’ve learned to admire Singapore’s 1st world transformation. I’m a absolutely in awe that a government body can produce such a high quality article.
> The root cause of bad software has less to do with specific engineering choices, and more to do with how development projects are managed.
...While I do agree that "project-management" is important, I think the tools we are using today are really underpowered to deal with complexity/human-error - Which is the bigger problem IMO.
> The main value in software is not the code produced, but the knowledge accumulated by the people who produced it
The problem is most CEOs see the binary as the asset, not the knowledge gained. I've tried to explain this concept to multiple startup CEOs, who hire outside development firms, for which it rarely works out for them.
> Software has characteristics that make it hard to build with traditional management techniques; effective development requires a different, more exploratory and iterative approach.
Or the management techniques considered “traditional” are overlooking a century of iterative development outside of software. See Deming.
The author is very cavalier about open source licenses - they seem to be implying you can just use open source code whenever you want, even for closed-source, proprietary applications. Whether or not that is true depends on the licenses involved.
The lead image features two laptops and a desktop. And three hardcopies of code. All with a light-on-dark color scheme. I'd wager they had a bit of fun taking this programmery photo.
What excellent article. It summarizes things that sometimes need decades to learn by ourselves. Reading books and good articles like this give us a shortcut for such wisdom.
What is the definition of "best engineers"? Those with extensive experience? those who follow design patterns and coding standards religiously? those who solve algorithms on a whiteboard? I would like to see if there is a definition for this.
I would say build the right culture (collaborative, always learning from mistakes and revise decisions and no blame or pointing fingers).
You can get a bunch of great coders/engineers _who follow code standards, break down codes to zillions of functions/methods ... etc_ but will fail to work together and conflicts will raise quickly.
Industry this days is more about headcount than quality itself. Why hire two good engineers when you can have three mediocre ones for the same price?
On simplicity, common wisdom these days dictate that we should use bloated kitchen-sink backend MVC frameworks that generate dozens of directories after `init`, because supposedly nobody knows how to use routers. Frontend compiler pipelines are orders of magnitude more complex than the reactive frameworks themselves, because IE11. And even deployment now requires a different team or expensive paid services from the get go. We're definitely not seeking simplicity.
The second point is also something that most developers and managers would balk at: "To build good software, you need to first build bad software, then actively seek out problems to improve on your solution". Very similar to the Fred Brooks "throw one away" advice that no one ever followed.
I disagree with that, if you describe it as stated in the article: "Overall, good engineers are so much more effective not because they produce a lot more code, but because the decisions they make save you from work you did not know could be avoided."
I've seen plenty of poor decisions that cause 10x the work, and end up with something 10x less maintainable.
> Surprisingly, the root cause of bad software has less to do with specific engineering choices, and more to do with how development projects are managed. The worst software projects often proceed in a very particular way:
> The project owners start out wanting to build a specific solution and never explicitly identify the problem they are trying to solve. ...
At this point, it looks like the article will reveal specific techniques for problem identification. Instead, it wraps this nugget in a lasagna of other stuff (hiring good developers, software reuse, the value of iteration), without explicitly keeping the main idea in the spotlight at all times.
Take the first sentences in the section "Reusing Software Lets You Build Good Things Quickly":
> Software is easy to copy. At a mechanical level, lines of code can literally be copied and pasted onto another computer. ...
By the time the author has finished talking about open source and cloud computing, it's easy to have forgotten the promise the article seemed to make: teaching you how to identify the problem to be solved.
The section returns to this idea in the last paragraph, but by then it's too little too late:
> You cannot make technological progress if all your time is spent on rebuilding existing technology. Software engineering is about building automated systems, and one of the first things that gets automated away is routine software engineering work. The point is to understand what the right systems to reuse are, how to customise them to fit your unique requirements, and fixing novel problems discovered along the way.
I would re-write this section by starting with a sentence that clearly states the goal - something like:
"Paradoxically, identifying a software problem will require your team to write software. But the software you write early will be quite different than the software you put into production. Your first software iteration will be a guess, more or less, designed to elicit feedback from your target audience and will deliberately built in great haste. Later iterations will solve the real problem you uncover and will emphasize quality. Still, you cannot make technical progress, particularly at the crucial fact-gathering stage, if all your time is spent on rebuilding existing technology. Fortunately, there are two powerful sources of prefabricated software you can draw from: open source and cloud computing."
The remainder of the section would then give specific examples, and skip the weirdly simpleminded introductory talk.
More problematically, though, the article lacks an overview of the process the author will be teaching. Its lack makes the remaining discussion even harder to follow. I'll admit to guessing the author's intent for the section above.
Unfortunately, the entire article is structured so as to prevent the main message ("find the problem first") from getting through. As a result, the reader is left without any specific action to take today. S/he might feel good after having read the article, but won't be able to turn the author's clear experience with the topic into something that prevents more bad software from entering the world.
Nice Post. But everyone needs to understand something. Even if you follow these principles to the letter T, you can still produce very bad software. In fact you can also find many cases where people did the exact opposite of what this guy said and still produced great software. I'm sure many people can name examples of software that just came together out of blind luck.
Why?
Because there is no formal definition for what is bad or good software. Nobody knows exactly why software gets bad or why software gets good or what it even exactly is... It's like predicting the weather. The interacting variables form a movement so complex that it is somewhat impossible to predict with 100% accuracy.
What you're reading from this guy is the classic anecdotal post of design opinions that you literally can get from thousands of other websites. I'm seriously tired of reading this stuff year over year rehashing the same BS over and over again, yet still seeing most software inevitably become bloated and harder to work with over time.
What I want to see is a formal theory of software design and by formal I mean mathematically formal. A axiomatic theory that tells me definitively the consequences of a certain design. An algorithm that when applied to a formal model produces a better model.
We have ways to formally prove a program 100% correct negating the need for unit tests, but do we have a formal theory on how to modularize code and design things so that they are future proof and remain flexible and understandable to future programmers? No we don't. Can we develop such a theory? I think it's possible.
We know a great deal about dynamics,kinematics, thermodynamics and generally the physics that governs car components, yet we are a long way from an algorithm that applied to a car will produce a better car. My guess is that doing that for software is as
hard, if not harder.
Also the sentence 'algorithms that applied to algorithms produce a better model' has a strong smell of halting problem, at least to this nose.
There's a saying in most other fields of engineering (civil, chemical, mechanical, etc.): "Regulations are written in blood." A whole lot of bridges collapsed and a whole lot of people died before strong requirements were put in place.
It seems we are on the path to repeat history with software engineering, what with how software and the internet is being developed with such little regard for public safety and long term consequences.
Unfortunately, it appears that the "free love" phase of software engineering is coming to an end, as society now relies more and more on software and major tech players for life and safety. It's starting to get real for software engineering.
Luckily, other engineering fields have been here before, so this sort of transition shouldn't be anything new.
If some part of the software has problems, runs slow or has bugs but nobody is complaining, then there's no problem.
This depends very much on context. To pick an extreme example, if you're writing the control software for a nuclear weapon and you know you have a bug that might cause it to activate unintentionally if you eat a banana while it's raining outside, I think we can reasonably agree that this is still a problem even if so far you have always chosen an apple for lunch on wet days.
mr_tristan|6 years ago
I've experienced more issues caused by management passing around tasks between teams and never paying attention to knowledge and knowledge transfer.
What's amazing, is that in over 18 years as a software engineer, I've seen this so many times. Teams will function well, then the institution tries to change. Often they will try to open up the "innovation" by throwing money at R&D, basically trying to add bodies in order to grow. Then you have tons of teams, and communication becomes very challenging, so then they grow some kind of "task management" layer. Management that never understands who actually _knows_ something, just tracks how much "theoretical bandwidth" they have and a wishlist of features to create. And then the crapware really starts flowing. And then I get bored and move on to the next place.
clumsysmurf|6 years ago
The company I work for uses Scrum. They consider the User Stories + the code to be everything you need. I struggle with this, but my manager says they don't want to get tied up doing documentation "because it goes out of date". Beside, they are being Agile which "prefers working code over comprehensive documentation".
I am wondering what other companies do to capture this "distilled knowledge". The backend services I rely on are undocumented beside some paltry swagger that leaves much to be desired. The front end has no product-level "spec", if you want to rebuild the thing from scratch. There isn't even a data dictionary, so everyone calls the same thing by different terms (in code, and conversation).
There are just user stories (thousands) and code.
Does anyone have any suggestions on how to fix this?
civicsquid|6 years ago
I think about that whenever I get frustrated about a vague spec or lack of details. It's the job!
mmatants|6 years ago
cntlzw|6 years ago
I know as a software developer you don't want to do that. More fun refactoring code than dealing with management. More fun writing that piece of SQL than sitting in a meeting. Easier to whine about missing specifications than to understand the big picture.
Once I stepped back from coding and looked at the software from a birds eye view, I had actually a much easier time programming features than before. More knowledge, less writing code.
JamesBarney|6 years ago
kgwxd|6 years ago
hising|6 years ago
communicationChannels = nrOfTeams(nrOfTeams-1)/2
More people should read The Mythical Man-month
_pmf_|6 years ago
Managers are very unhappy when I tell them of all the knowledge I've developed.
drderidder|6 years ago
unknown|6 years ago
[deleted]
atoav|6 years ago
- the problem you are trying to solve
- how you could solve it
- how you actually did solve it
- which solutions come with which flaes and merits
stygiansonic|6 years ago
“Beware of bureaucratic goals masquerading as problem statements. “Drivers feel frustrated when dealing with parking coupons” is a problem. “We need to build an app for drivers as part of our Ministry Family Digitisation Plans” is not. “Users are annoyed at how hard it is to find information on government websites” is a problem. “As part of the Digital Government Blueprint, we need to rebuild our websites to conform to the new design service standards” is not. If our end goal is to make citizens’ lives better, we need to explicitly acknowledge the things that are making their lives worse.”
dehrmann|6 years ago
jrumbut|6 years ago
The following is a wonderful point I have hardly ever heard said directly:
"The main value in software is not the code produced, but the knowledge accumulated by the people who produced it."
lifeisstillgood|6 years ago
unityByFreedom|6 years ago
"value your knowledge workers"
"your employees are your most valuable asset"
Some companies don't treat employees well, and some employees at good companies feel they are not treated well enough
If the above quotes do not strike a chord with you, you might just be a software engineer who thinks you're more important than non-SEs.
iEchoic|6 years ago
It also introduces unknown amounts of debt and increases the likelihood that you'll end up with intractable performance/quality/velocity problems that can only be solved by re-writing large portions of your codebase.
This can be a dangerous cultural value when it's not presented with caution, which it isn't here. I think it's best to present it alongside Joel Spoelsky's classic advice: "If it’s a core business function — do it yourself, no matter what".
https://www.joelonsoftware.com/2001/10/14/in-defense-of-not-...
yowlingcat|6 years ago
```
The best advice I can offer:
If it’s a core business function — do it yourself, no matter what.
Pick your core business competencies and goals, and do those in house. If you’re a software company, writing excellent code is how you’re going to succeed. Go ahead and outsource the company cafeteria and the CD-ROM duplication. If you’re a pharmaceutical company, write software for drug research, but don’t write your own accounting package. If you’re a web accounting service, write your own accounting package, but don’t try to create your own magazine ads. If you have customers, never outsource customer service.
```
This all rings true in my experience. You should write the software that's critical to your core business competency yourself, because the maintenance cost is worth paying if you can achieve better software. But if it's not a core competency and your business isn't directly going to benefit from having best in class vs good enough, then it may be worth outsourcing.
jeffmcmahan|6 years ago
(1) If a problem can be exhaustively specified in a formally well-defined way (mathematical logic), it will be wise to adopt a mature implementation - if it exists.
(2) If a problem can't be so specified, all implementations will be incomplete and will contain trade-offs. I have to address these problems myself to ensure that limits and trade-offs suit as well as possible what the business needs. If I can.
So, (1) says I shouldn't parse my own JSON. (2) says I should avoid the vast majority of what shows up in other people's dependency trees.
anderspitman|6 years ago
nneonneo|6 years ago
The author seems like an unknown in the software development world, but they’re one of the managers for Singapore’s fairly successful digital government initiative. So it does feel safe to say they have some experience.
angelsl|6 years ago
I suppose he wrote this for other people in the Singapore civil service.
tony|6 years ago
In python, I typically follow a pattern of keeping stuff in __name__ == '__main__' block and running it directly, then splitting to functions with basics args/kwargs, and finally classes. I divide into functions based on testability btw. Which is another win, since functional tests are great to assert against and cover/fuzz with pytest.mark.parameterize [1]
If the content of this post interested you: Code Complete: A Practical Handbook of Software Construction by Steve McConnell would make good further reading.
Aside: If the domain .gov.sg caught your eye: https://en.wikipedia.org/wiki/Civil_Service_College_Singapor...
[1] https://docs.pytest.org/en/latest/parametrize.html
ptx|6 years ago
9nGQluzmnq3M|6 years ago
http://theindependent.sg/li-hongyi-singapore-has-a-lot-of-pr...
hnick|6 years ago
I came across this article: https://mothership.sg/2015/03/lee-hsien-yang-reveals-the-sto...
> I have taught my children never to mention or flaunt their relationship to their grandfather, that they needed to make their own way in the world only on their own merits and industry.
wenc|6 years ago
steventhedev|6 years ago
A good example of this is:
- Add worker thread for X to offload Y
When the actual problem is more along the lines of:
- Latency spikes on Tuesdays at 3pm in main thread
Which may be caused by a cronjob kicking off and hogging disk IO for a few minutes.
A good rule of thumb I've found is that task tickets tend to have exactly one way of solving them, whereas problem tickets can be solved in many ways.
Dumblydorr|6 years ago
ak39|6 years ago
1. Making sure what you build is what was really requested (correct), and
2. Making sure what you've built doesn't have a higher running "cost" than the thing it replaced (either manual process or old automated solutions).
Everything else, IME, is ancillary. Performance, choice of platform, frameworks, methodology to build, maintainability etc are sub-objectives and should never be prioritized over the first two objectives. I have worked on many projects where the team focussed mostly on the "how to build" parts and have inevitably dropped the ball on the "what" to build of the projects. Result: failure.
Sauce: personal experience with several years of different projects (n = 1; episodes = 20+ projects that have gone live and have remained live versus 100+ projects lying by the wayside).
Writing software is not easy.
0x445442|6 years ago
siempreb|6 years ago
This is where most companies fail. Yes, they do want the best developers, but for the budget of an average junior/medior dev.
For some reason most companies/managers I worked for do not understand the financial impact of a not so good developer. Or the other way around; they fail to value the best developers and are unable recognize them.
I've worked for plenty companies where they let mediocre dev's build a big app from scratch (including the architecture), in an Agile self managed team.. These are the codebases that always need to be rewritten entirely because they have become an unmanageble buggy mess of bad ideas and wrong solutions.
lelima|6 years ago
If every single company wants that, where is he space to grow and learn from mistakes?
Maybe I'm wrong but I think those "mediocre dev's" learned a lot building a big app from scratch, solving bugs and refactoring.
jshowa3|6 years ago
Then the project turns out to be months late, even though I called the timeline of the project virtually unfeasible, and we have to go back and make several changes that could've been caught early on with a better strategy.
The problem with hiring the "best" engineers is as follows:
1. Nobody can ever tell you what the best means. People just throw 10x around without any explanation.
2. Most people in the world are average. You simply don't have enough of the best people to handle the work load, even if they're 10x average. So much existing software and new problems exist that it's nigh impossible to have the best everywhere.
3. Many of the best people are able to write really good code, but they consider it so easy that they often write code that they think is correct and it gets put in production. Since they're loners, they often don't do the necessary leg work either because of their own arrogance, or because the company hasn't clearly defined its processes and the developer can't even reach this goal despite numerous efforts. So management just believes the code is correct without any verification.
4. Many average developers support the best ones by taking needed work away from them through comparative advantage. Just because X employee is awesome at Y task, doesn't mean he meets the highest utility by doing Y task all the time. Especially when there are conflicting priorities.
5. The best engineers aren't going to be working at a small company in most cases. They also aren't likely to be paid well outside a large company either. The article sites Google, Facebook, and all the large tech companies and their supposed stringent interview process as a reason. But these companies have written terrible software (Google+, AMP pages) and become ethically compromised easily. Plus their interview process is often so outside the daily work flow because it involves answering algorithm questions, that it often makes no sense. Even worse, it teaches people to do katas instead of build actual projects. Project based interviews make much more sense.
6. Rewriting code bases is one of the worst things you can do and is what caused Netscapes downfall. Companies with supposedly the best engineers (ie. Netscape), can't even do it well.
So while hiring the best engineers is an awesome goal. It isn't feasible in a lot of cases.
I admit I have some bias as I consider myself pretty average. But I do a lot of crap on the side that "10x devs" don't even hear about because they're working on something more urgent. Does that mean I'm worthless?
akersten|6 years ago
The claim is:
> Stakeholders who want to increase the priority for a feature have to also consider what features they are willing to deprioritise. Teams can start on the most critical objectives, working their way down the list as time and resources allow.
In other words, the argument is "competing priorities in a large-scale project make it more likely to fail, because stakeholders can't figure out which ones to do first." Actually, in this very paragraph, the author glosses over the real issue: "Teams can start on the most critical objectives, working their way down the list" - treating development as an assembly line input-to-output process.
I argue that it's not time constraints that complex programs bad, but instead the mere act of thinking that throwing more developers at the work will make it any better. Treating the application as a "todo list" rather than a clockwork of engineering makes a huge difference in the quality of the work. When developers are given a list of customer-facing features to achieve, more often than not the code winds up a giant ball of if-statements and special cases.
So yes, I do agree that complex software is worse and more prone to failure than simple software - but not for the reason that there's "too much to do" or that prioritizing is hard. Complex software sucks because it's requirement-driven, instead of crafted by loving hands. No one takes the time to understand the rest of the team's architecture or frameworks when just throwing in another special case takes a tenth of the time.
Mertax|6 years ago
There are different personalities of engineers, those who thrive on explicit requirements and can accomplish difficult engineering tasks when they are given clear requirements. But those engineers should only be given those requirements once the job that the customer is trying to get done is clearly understood. Some engineers have the ability to find creative solutions, that customers or product managers can’t see, when they are provided with problems and jobs rather than requirements and tasks.
Managers would be wise to distinguish between the type of engineers they are managing and play to their strengths. Whatever type you have, understanding the job the end user is trying to get done must occur, preferably by an engineer that’s capable of articulating that, if needed, to team members as technical requirements.
JohnBooty|6 years ago
But it absolutely does not need to be the case.
If you treat engineers as interchangeable cogs who only need to know about one story at a time, and never tell them about the medium- and long-term goals of the business and the application? Then yes. Then you get an awful code base with tons of if-then crap.
However, it doesn't need to be this way. If you give engineers visibility into (and some level of empowerment with regard to) those longer-term goals, they can build something more robust that will allow them to deliver features and avoid building a rickety craphouse of special cases.
I have experienced both scenarios many times.
kilburn|6 years ago
This is a misinterpretation of the article's claim. The article very explicitly begins by saying that the best recipee to increase a project's chances to success is to:
> 1. Start as simple as possible;
> 2. Seek out problems and iterate;
The priority part reads to me as a way to determine which features are critical (and hence part of the as simple as possible set) and which ones are not (and hence you should not build "yet"). The underlying vibe being that these other features should probably never get implemented because once the critical ones get built and the software is put to use you will actually find other critical fearures that solve actual problems found through usage.
That is, only when you find that one of the initially non-critical features has become a hindrance for users actually using your software you should seek to implement it.
I really think this would be a better way to build software, just as much as I think that you will have a very very hard time getting any management on board with it...
andy_ppp|6 years ago
This means that instead of lots of issues with business logic being separate from the data the business logic and data sit together and prevent your system from getting into bad states.
Thinking about this, maybe I just stole this thought from Derek Sivers: https://sivers.org/pg
dajonker|6 years ago
A database in my opinion is not a good place to write business logic with functions and triggers, since there is lack of tooling that would make development and debugging easy. Let the database do what it does well, which is storing and querying data.
nine_k|6 years ago
This all takes a bird-eye view and a long perspective, very unlike quarter-results-driven development.
hnick|6 years ago
This one struck me, because as soon as I read it I knew it was true yet had never considered it:
> Most people only give feedback once. If you start by launching to a large audience, everyone will give you the same obvious feedback and you’ll have nowhere to go from there.
I've been on both sides of that fence and it rings true.
joes223|6 years ago
DantesKite|6 years ago
smacktoward|6 years ago
ssijak|6 years ago
lifeisstillgood|6 years ago
This article is full of good ideas, an antidote to creeping corporate take over of software projects - make this required reading for software projects.
axilmar|6 years ago
The problem is lack of knowledge. The successful projects mentioned above did not have a lack of knowledge, and so they were finished successfully.
When there is a lack of knowledge, then it makes sense to use the iterative approach...as knowledge is slowly gathered, the software gets improved. As with all things in life!
fbr|6 years ago
But starting a "gather requirements - write software - deliver it" lifecycle because you are confident that you have all the knowledge is one as well.
zero_k|6 years ago
lifeisstillgood|6 years ago
Now we have government digital systems leading the charge across most western countries, and we have excellent polemics like this. I am just so happy to see this level of insightful ness at top levels of government.
I am so glad they listened to me :-)
ptidhomme|6 years ago
This is spot on, and very much my experience (of the good engineers I've come across).
Kind of : management had planned extensive and painful testing of a component that turned out to be discarded entirely (not because of functionality reduction but because it was actually unecessary).
acd|6 years ago
Reusing good modules and software will make the software work.
Kiss engineering still works keep it simple stupid. Make it as simple as possible. Simple software and systems are easy to maintain and understand.
Use modules as these can be swapped out.
Use proven boring technology such as SQL and JSON. Boring tech has been tried by others and generally works well.
tester344|6 years ago
What makes you think so?
soup10|6 years ago
Translation: the successful tech companies have so much poorly documented legacy enterprise spaghetti code and tooling that they need the best talent they can get just to make sense of it and maintain it
abacadaba|6 years ago
koevet|6 years ago
unicornmama|6 years ago
Google views picking new engineers like picking quality construction metals. In the end, the machine melts you down and hammers you into a pristine cog.
hnick|6 years ago
joes223|6 years ago
Silhouette|6 years ago
I do think perhaps there is too much emphasis on reuse and particularly cloud services. Ironically, this is partly for the reasons given elsewhere in the article. If you rely on outsourcing important things, you also naturally outsource the deep understanding of those important things, which can leave you vulnerable to problems you didn't anticipate. Also, any integration is a source of technical debt, so dependencies on external resources can be more fragile than they appear, and if something you rely on changes or even disappears then that is a new kind of potentially very serious problem that you didn't have to deal with before. Obviously I'm not advocating building every last thing in-house in every case, but deciding when to build in-house and when to bring something in can be more difficult than the article here might suggest.
einpoklum|6 years ago
Perhaps some software development techniques would work though...
> The main value in software is not the code produced, but the knowledge accumulated by the people who produced it.
Those people go on to work on other things or for other organization. So, while that statement might have some truth to it, it's still the case that the code has to be useful, robust, and able to impart knowledge to those who read it (and the documentation).
> Start as Simple as Possible
That's a solid suggestion to many (most?) software projects; but - if your goal is to write something comprehensive and flexible, you may need to replace it with:
"Start by simplifying your implementation objectives as much as possible"
and it's even sometimes the case that you want to sort of do the opposite, i.e.
"Start as complex as possible, leading you to immediately avoid the complex specifics in favor of a powerful generalization, which is simpler".
AnimalMuppet|6 years ago
> Perhaps some software development techniques would work though...
As you go up the management chain, you usually run into some layer where people are traditional managers, who want to run a software project like a traditional project. And behold, you're at this problem. Saying "software development techniques would work" is useless unless you can get those managers to change. And when you get them to change, the problem moves up one layer.
einhverfr|6 years ago
When faced with a standard solution, use a standard component if you can. If you can't use a standard component, build a standard component. Keep your components simple, well-understood, and easy to maintain.
pmontra|6 years ago
unicornmama|6 years ago
opvasger|6 years ago
...While I do agree that "project-management" is important, I think the tools we are using today are really underpowered to deal with complexity/human-error - Which is the bigger problem IMO.
exabrial|6 years ago
The problem is most CEOs see the binary as the asset, not the knowledge gained. I've tried to explain this concept to multiple startup CEOs, who hire outside development firms, for which it rarely works out for them.
zeckalpha|6 years ago
Or the management techniques considered “traditional” are overlooking a century of iterative development outside of software. See Deming.
fooblitzky|6 years ago
driverdan|6 years ago
This site is an empty page without JS.
davidperrenoud|6 years ago
mcgwiz|6 years ago
k__|6 years ago
This is also the real problem with vendor lock-in.
You are more often locked in by the knowledge of your employees than by your tech stack.
edpichler|6 years ago
wwarner|6 years ago
Oras|6 years ago
What is the definition of "best engineers"? Those with extensive experience? those who follow design patterns and coding standards religiously? those who solve algorithms on a whiteboard? I would like to see if there is a definition for this.
I would say build the right culture (collaborative, always learning from mistakes and revise decisions and no blame or pointing fingers).
You can get a bunch of great coders/engineers _who follow code standards, break down codes to zillions of functions/methods ... etc_ but will fail to work together and conflicts will raise quickly.
mychael|6 years ago
ikll|6 years ago
Industry this days is more about headcount than quality itself. Why hire two good engineers when you can have three mediocre ones for the same price?
On simplicity, common wisdom these days dictate that we should use bloated kitchen-sink backend MVC frameworks that generate dozens of directories after `init`, because supposedly nobody knows how to use routers. Frontend compiler pipelines are orders of magnitude more complex than the reactive frameworks themselves, because IE11. And even deployment now requires a different team or expensive paid services from the get go. We're definitely not seeking simplicity.
The second point is also something that most developers and managers would balk at: "To build good software, you need to first build bad software, then actively seek out problems to improve on your solution". Very similar to the Fred Brooks "throw one away" advice that no one ever followed.
dajonker|6 years ago
blue_devil|6 years ago
Aeolun|6 years ago
unknown|6 years ago
[deleted]
dwipurnomo|6 years ago
kitsune_|6 years ago
dajonker|6 years ago
I've seen plenty of poor decisions that cause 10x the work, and end up with something 10x less maintainable.
apo|6 years ago
> The project owners start out wanting to build a specific solution and never explicitly identify the problem they are trying to solve. ...
At this point, it looks like the article will reveal specific techniques for problem identification. Instead, it wraps this nugget in a lasagna of other stuff (hiring good developers, software reuse, the value of iteration), without explicitly keeping the main idea in the spotlight at all times.
Take the first sentences in the section "Reusing Software Lets You Build Good Things Quickly":
> Software is easy to copy. At a mechanical level, lines of code can literally be copied and pasted onto another computer. ...
By the time the author has finished talking about open source and cloud computing, it's easy to have forgotten the promise the article seemed to make: teaching you how to identify the problem to be solved.
The section returns to this idea in the last paragraph, but by then it's too little too late:
> You cannot make technological progress if all your time is spent on rebuilding existing technology. Software engineering is about building automated systems, and one of the first things that gets automated away is routine software engineering work. The point is to understand what the right systems to reuse are, how to customise them to fit your unique requirements, and fixing novel problems discovered along the way.
I would re-write this section by starting with a sentence that clearly states the goal - something like:
"Paradoxically, identifying a software problem will require your team to write software. But the software you write early will be quite different than the software you put into production. Your first software iteration will be a guess, more or less, designed to elicit feedback from your target audience and will deliberately built in great haste. Later iterations will solve the real problem you uncover and will emphasize quality. Still, you cannot make technical progress, particularly at the crucial fact-gathering stage, if all your time is spent on rebuilding existing technology. Fortunately, there are two powerful sources of prefabricated software you can draw from: open source and cloud computing."
The remainder of the section would then give specific examples, and skip the weirdly simpleminded introductory talk.
More problematically, though, the article lacks an overview of the process the author will be teaching. Its lack makes the remaining discussion even harder to follow. I'll admit to guessing the author's intent for the section above.
Unfortunately, the entire article is structured so as to prevent the main message ("find the problem first") from getting through. As a result, the reader is left without any specific action to take today. S/he might feel good after having read the article, but won't be able to turn the author's clear experience with the topic into something that prevents more bad software from entering the world.
crimsonalucard|6 years ago
Why?
Because there is no formal definition for what is bad or good software. Nobody knows exactly why software gets bad or why software gets good or what it even exactly is... It's like predicting the weather. The interacting variables form a movement so complex that it is somewhat impossible to predict with 100% accuracy.
What you're reading from this guy is the classic anecdotal post of design opinions that you literally can get from thousands of other websites. I'm seriously tired of reading this stuff year over year rehashing the same BS over and over again, yet still seeing most software inevitably become bloated and harder to work with over time.
What I want to see is a formal theory of software design and by formal I mean mathematically formal. A axiomatic theory that tells me definitively the consequences of a certain design. An algorithm that when applied to a formal model produces a better model.
We have ways to formally prove a program 100% correct negating the need for unit tests, but do we have a formal theory on how to modularize code and design things so that they are future proof and remain flexible and understandable to future programmers? No we don't. Can we develop such a theory? I think it's possible.
carapace|6 years ago
The Applied Category Theory folks have some very interesting stuff, like Categorical Query Language.
https://www.appliedcategorytheory.org/
https://www.categoricaldata.net/
But it sounds to me what you mean is more like if "Pattern Language" was symbolic and rigorous, eh?
al_form2000|6 years ago
Also the sentence 'algorithms that applied to algorithms produce a better model' has a strong smell of halting problem, at least to this nose.
known|6 years ago
johnfisher57|6 years ago
commandlinefan|6 years ago
diafygi|6 years ago
It seems we are on the path to repeat history with software engineering, what with how software and the internet is being developed with such little regard for public safety and long term consequences.
Unfortunately, it appears that the "free love" phase of software engineering is coming to an end, as society now relies more and more on software and major tech players for life and safety. It's starting to get real for software engineering.
Luckily, other engineering fields have been here before, so this sort of transition shouldn't be anything new.
Relevant Tom Scott video: https://www.youtube.com/watch?v=LZM9YdO_QKk
nerdponx|6 years ago
ensiferum|6 years ago
This is bad advice. It's like saying "go into a bar and start picking up fights".
If some part of the software has problems, runs slow or has bugs but nobody is complaining, then there's no problem. Why waste time improving it?
Almost 100% of the time when you solve a problem you just create new problems of different kind in turn.
Be lazy. The less code you write the better off you are.
Silhouette|6 years ago
This depends very much on context. To pick an extreme example, if you're writing the control software for a nuclear weapon and you know you have a bug that might cause it to activate unintentionally if you eat a banana while it's raining outside, I think we can reasonably agree that this is still a problem even if so far you have always chosen an apple for lunch on wet days.
unknown|6 years ago
[deleted]