Even if business schools start lecturing their students about details of software development, and even if these details actually sink in, there will still be many other kinds of work their students don't learn anything about. The real problem, I think, is graduates of these schools who believe they can manage people in a generic way without understanding the details of the work.
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.
> 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.
Software will always be a spread of reliability requirements, from pacemakers on one side to excel reports on the other. Part of being a responsible user is choosing software with the right balance of economics and reliability for the job.
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.
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.
> There are engineers who can accomplish difficult engineering tasks when they are given clear requirements and engineers have the ability to find creative solutions when they are provided with problems and jobs rather than requirements and tasks.
I feel like I could perform adequately in either environment. The problem is I've previously found myself in environments where I'm expected to come up with creative solutions to a problem, but I have no access to the customer or even a simulated environment where I could try to do something similar to what a customer would do.
In this kind of case, it's impossible to really know how to articulate your requirements, because all you can use is a fantasy model of hypotheticals. But requests for more precise requirements are potentially brushed off as wanting to be spoon-fed what you need to do and having inability or unwillingness to think creatively.
> 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 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.
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 like to do it early also, to make sure that the new script, if imported from by a sibling module, is inert.
An example would be a scripts/ folder and sharing a few functions between scripts w/o duplicating.
In some cases I don't have a choice. Initialization of a flask app/ORM stuff/etc has to be done in the correct order.
I think the general rule of thumb I follow is: avoiding keeping code that'd "run" in the root level. Keep it in blocks (normally to me functions) has the added effect of labeling what is does.
What I don't do: I don't introduce classes until very late. In hindsight, every time I tried to introduce a complicated object model, I feel I tended to overengineer / encounter YAGNI
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.”
I don't understand the point of replying like this. Clearly we agree that the Singaporean government is very good at getting things done, and we agree that the things it wants to get done are horrible. Why are you speaking as if our opinions differ? Why manufacture conflict where none exists? Is calling something a quasi-Orwellian dystopia now too subtle an expression of disapproval?
Comments like this are part of the reason why people like Sam Altman stopped posting here. Can you just give the poster the benefit of the doubt that they just admire the efficiency of the Singaporean government, not that they're endorsing authoritarianism as long as it's effective?
Never acknowledge any quality of the Enemy. The Enemy is Bad, therefore it is also weak, stupid, lazy, cowardly… Because the risk of being perceived as praising the Enemy always trumps the consequences of underestimating it.
>Can you just give the poster the benefit of the doubt
Perhaps you should do the same for barrkel? I read your parent as a simple explanation to solveit why their comment may have been misconstrued by bsder -- a question solveit directly asked.
You're probably right. I just get frustrated when people insist on reading value judgments in literally everything. Sometimes the curtains are just blue, you know?
> Clearly we agree that the Singaporean government is very good at getting things done, and we agree that the things it wants to get done are horrible.
Singaporean here. The government's mainly effective for tasks that are on a happy path. If your particular case falls through the cracks, it often takes phone calls, printing, postage, and weeks or months of waiting to get stuff done.
(Personal experience trying to get business stuff done not as a Private Limited company.)
I replied that way because, if we moved this to a tech subject, people here would be horrified at your definition of "effective".
If someone produced an insulin pump that you implanted, worked perfectly for life, but killed 1 person in 1,000 randomly, people would be screaming for the head of the CEO of that company rather than calling it "effective".
But that wouldn't be effective because it's random, not because it kills people. A better analogy is if the pump worked perfectly, but killed anyone who the CEO disliked. That would be effective, yet monstrous.
Effective just means it achieves the intended outcome, it's not a value judgment on the goodness of that intention.
Indeed, I couldn't live there, and I don't think it's right for humans to not have a choice not to live there, but for those who have chosen to be there and agree with the state, I'm sure it satisfies them.
I like being partially or fully nude in the home, occasionally chewing gum, and having the right to freely criticize or endorse ideology on its own merits; even if it sometimes sucks to see dirty black spots on the sidewalk, or to hear people making weak arguments just to upset eachother.
Certainly a weird cosmopolitan fascist (u|dys)topia.
The difference, for me, is that neither of those quotes explain why you should value knowledge workers or why employees are valuable (maybe hiring is expensive, maybe turnover reduces morale, etc), nor do they suggest the mechanism that creates this value.
I'm sure another author has put the same sentiment out there before, but it's not every day I see such a nice phrasing of it.
> neither of those quotes explain why you should value knowledge
I mean, the point of short quotes is to be memorable and get future listeners to hunt for the reason behind them. "The sun will rise tomorrow" may also be meaningless for some people on its own.
Nothing wrong with elaborating on this subject again via a blog post, I was just pointing out to the commenter who's never heard this expressed before that it has a long history, that's all.
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
This is not what I have experienced, at least not in real world software with mediocre documentation. Usually the software encodes only the "how", but the important parts are "why" and what aspects of the original problem led to that design.
Good teams learn how to transfer and adapt in the next project. Starting with the software only, lots of that can only be reverse engineered.
That was something I picked up from one of the more experienced software devs when I started - in his code there were far fewer comments saying "This section does x and y", than there were comments saying "We are doing x and y because ..."
Sorry - the son of Singapore's Prime Minister is a Scala Hacker ...
I keep on saying that Software Literacy is a real thing. And that this current generation of leaders are like Charlemagne - he was the first Holy Roman Emperor and the last who was illiterate.
> One of them browsed a book and said, 'Here, read this.'" It was a textbook on the Haskell programming language, Lee recounted. "One day that will be my retirement reading."
Even Singapore's PM has to put up with smug Haskell programmers
>I keep on saying that Software Literacy is a real thing. And that this current generation of leaders are like Charlemagne - he was the first Holy Roman Emperor and the last who was illiterate.
And probably he was the best of what followed as well, so this literacy thing didn't go as well, where power figures were concerned...
> 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.
Singapore's older generations speak/spoke Chinese "dialects" like Hakka (Lee Kuan Yew's heritage), but there has been a massive government-led push towards standardizing on Mandarin as the one true Chinese. Hence Lee Hsien Loong's children all have their names officially romanized in Mandarin pinyin (Li), not Hakka (Lee). The underlying character, 李, is still the same.
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.
I get where you're coming from. I think your intuition is off.
Intuitively, software can be modeled as a graph of modules with lines representing connections between modules. An aspect of "good software" can be attributed to some metric described by the graph, let's say the amount of edges in the graph... the less edges the less complex. An optimization algorithm would probably take this graph as an input and output a graph that has the same functionality but less edges. You can call this a "better design." This is all really fuzzy and hand wavy but if you think about it from this angle I'm pretty sure you'll see that a axiomatic formalization can be done along with an algorithm that can prune edges from a graph (or in other words, improve a design by lowering complexity)
A computer program is a machine that translates the complexity of the real world into an ideal system that is axiomatic and highly, highly simplified. Such a system can be attacked by formal theory unlike real world issues like what constitutes a good car.
The halting problem bit is a shower thought with no supporting evidence whatsoever, so your complexity lowering scenario may well be doable. However, paring complexity is a strictly developer-side measure of goodness (that is assuming that the low complexity result is still readable, maintainable...) - we can agree that reducing bugs is also a very good user side metric, but that tells only a (little) part of the story.
In my experience, developer-side evaluation has a very low impact (I was about to write: zero) on the perceived and actual goodness of the software itself. Which is tied mostly to factors such as user experience, fit to the problem it was designed for and to the organization(s) it is going to live in (user experience again). These properties do not strike me as amenable to algorithmic improvement, no more than "pleasant body lines and world class interiors" in the original car analogy. But they are a (big) part of good software design, besides being the 'raison d'etre' of the darned thing to begin with.
But let's forget cars, as hard as it is. Few months ago HN was running the story about developing software in Oracle. Now, Oracle may be by now a little soft around the edges, but I think that most would agree that it has been setting the standard for (R)DBMS for decades. Success may not on itself be the tell-all measure of software goodness, but the number of businesses that have been willing to stake the survival of their data on Oracle is surely a measure of its perceived goodness (as that other elusive factor - hipness - tends not to be paramount in the DBMSs business).
The development side story, taken as face value, was pure horror (https://news.ycombinator.com/item?id=18442941). Everything in it spoke bad, outdated, rotting design. The place must be teeming with ideas on how to improve just about everything in that environment. And yet if that came to be, maybe by some nifty edge pruning algorithm, it would do nothing to improved the goodness-to-the-world measure of the software, not until the internals' improvement translated to observables in the user base experience.That type of improvements will still require vaste amount of non-algorithmic design and, in the meantime, a very concrete risk will be run of deteriorating the overall user experience (because ehi, snafus will happen).
This (internals are just a small part of the story) is one of the reasons why so many reimplementations I have seen failed ("ehi, let's rewrite this piece of shit and make it awesome") and the reason because everyone resists the move from IPV4 to IPV6. I could think of many more examples.
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.
I can see it working both ways - in many cases, I'd like my ambiguity distilled down to one specific point, while the rest of the project deals with lower specific ambiguity (where ambiguity in my mind is equal to "is this thing possible").
I only have one year of formal CS education but that paper is one of my favorites on the topic. Naur is also the founder of CS at the University of Copenhagen, the place where I studied :)
"...the designers job is not to pass along "the design" but to pass along "the theories" driving the design. Knowledge of the theory is tacit in owning..."
I would prefer people read the original paper than any second-hand explanation of it. The paper is very readabale and understandable, and is probably relevant as long as into the future as human beings write code.
I was about to suggest the same thing. This paper should be mandatory reading for anyone that is professionally involved in a software development project.
> "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?
This is not necessarily in opposition to what TFA states: that programming is about knowledge engineering. It just happens that knowledge flows through user stories and code. This might work well or not so well for your team, and there's nothing to fix here. Managers should be aware, though, that this means you no longer have a project, but a line organization put up indefinitely, and where when the teams is disbanded, no "product" as such does remain; nor would it be possible to hand-over the "project" to an offshore team.
"prefers working code over comprehensive documentation" does not mean "don't do documentation".
Documentation is essential. How things work is an important thing to document. Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date. It still has problems (What do you do when the code and the documentation disagree? Which is correct?), but they're not as severe as the problems that arise when there is no documentation at all.
What is less useful is having comprehensive documentation for those things that are yet to exist. Writing a few hundred pages of specification and handing it over to the dev team is waterfall, and it is _this_ that the Agile manifesto signatories were interested in making clear.
I'd fix it with strategic DDD - I'd develop at least a "ubiquitous language" (or a UL): I'd get others to work with me on having clear terminology and making sure that is used consistently both in user stories and in the code base. That's table stakes.
I'd then event storm the contexts I'm working in and start to develop high level documentation.
Even at this point relationships between systems emerge, and you get to draw circles around things and name them (domains, contexts), and the UL gets a bit better. At this point you can start to think about describing some of your services using the UL and the language of domains and contexts.
By that point, people should start to click that this makes life easier - there is less confusion, and you're now all working together to get a shared understand of the design and the point of DDD is that the design and the code match.
The first part (all 100+ pages of it), of the Millet and Tune book on DDD will pay you dividends here.
If that doesn't work, look around for somewhere else to work that understands that software development is often a team sport and is committed to making that happen.
Thanks for the thoughtful response, this is helpful.
> Ideally it should be in version control and be generated from the code ..
May I ask if you have suggestions for tooling to capture the high level documentation. We use javadoc a little, but it seems best for lower level reference. Also for diagrams, like sequence diagram and/or state machines, how do you capture this?
Use graphviz (dot tool for example) for state machines.
It is a text format where you list state machine transitions and it generates a visual representation.
Or better yet: generate your state machines from same format you would use to generate visual representation.
Don't be afraid of building a product specification, and doing it in Markdown and auto-generating a mini-website out of it.
Just build a product specification for how the product works (which is useful documentation), not how the product will work (which is waterfall).
We're experimenting with this a little, and I'm getting into document-driven development a little: if the product spec is in markdown, why not create a pull request on it as part of your story/project planning that shows the changes that would happen as a consequence of your work. Once the story is done, you can merge the pull request, even. We're not quite there with this yet, but I'm optimistic.
Documentation is essential. How things work is an important thing to
document. Ideally it should be in version control and be generated
from the code, because then it's less likely to go out of date.
My solution to this is old and fairly unpopular, but I stand by it: anything in the codebase that's not obvious to a new maintainer should have a brief, explanatory code comment.
Generally, this falls into two categories.
1. Hacks/kludges to get around bugs in hardware, external services, or included libraries. These manifest in code as incomprehensible, ugly bits of code that are difficult to distinguish from code that is simply "sloppy" or uninformed. More importantly, they represent hard-won knowledge. It often takes many programmer-hours to discover that knowledge, and therefore many dollars. Why throw it away? (Tip: include the version of the dependency in the comment, ie)
# work around bug in libfoo 2.3, see blahblahblah.com/issues/libfoo/48987 for info
# should go away once we can upgrade to libfoo 3..
if error_code == 42 reset_buffer()
...so that future programmers (including you) can more easily judge whether the kludge is still needed in the future.
2. Business logic. This too is difficult/impossible to discern from looking at code. Often, one's git commit history is sufficient. But there are any number of scenarios where version control history can become divorced from the code, or require a fair bit of git/hg/svn/whatever spelunking to access. And this of course becomes increasingly onerous as a module grows. If there are 200 lines of code in a given module, it is a significant time investment to go git spelunking for the origins of all 200 lines of code. Some concise internal documentation in the form of code comments can save an order of magnitude or two of effort.
It still has problems (What do you do when the code and the
documentation disagree? Which is correct?), but they're not as
severe as the problems that arise when there is no documentation at all.
This is pretty easy to enforce at code review time, prior to merging.
In the first place, only a true maniac would intentionally update
# no sales tax in Kerplakistan on Mondays
return nil if country_code==56 and day_of_week==1
...without updating the associated comment. If they do neglect to update it, that's an easy catch at review time.
While I still would add a comment about the why, your last bit of code probably should be written without magic constants.
# Some countries have sales tax rules dependent on the day of the week
return nil if country_code==KERPLAKISTAN and day_of_week==MONDAY
The exact comment here could probably be more specific (e.g. where do you find these rules), but it also most likely shouldn't repeat the code (and the code should make clear what it represents).
If you do the substitution as you suggest and then add a unit test, then you have something ;-) Something on the lines of "describe countries with sales tax dependent upon the days of the week => Kerplakistan doesn't have sales tax on Mondays" So now it's self documented and self testing.
But I agree with your statement that there should be a pointer to the business rules somewhere. Otherwise it's difficult to have a meeting with the business side and ask, "Has anything here changed?" I think that's the biggest thing people miss out -- It's not that hard to find the thing in the code if things change. It's super hard to make sure you are on top of all the business requirement changes.
It was a very enterprisey Java codebase from the bad old days of J2EE - it had somewhere over 30 layers of abstractions between the code in a JSP and a web service call.
[NB 30 isn't an exaggeration - I think the vast team who wrote it were paid by the abstraction or something].
Comments are often a code smell. In lots of examples, better variable naming, breaking something out into a function, or constants often reduces the need for a code comment.
I disagree. Code ages and people move on. 2 years down the line some new guys are maintaining the code base. Some new guy is testing the system and notices that sales tax values seem to be "strange" for Kerplakistan on certain days of the week so they create a ticket for it. Then that goes through the typical pipeline. Another member of the team gets assigned the issue and looks into it. They come across the line:
return nil if country_code==KERPLAKISTAN and day_of_week==MONDAY
Hmm.. Well that's strange. I don't have a background in Kerplakistan monetary policy so I don't know why we aren't assessing sales tax on Monday. Perhaps Kerplakistan is a special case. Is that being handled somewhere downstream? Then 1-2 hours later, after shuffling through source and eventually just Googling Kerplakistan sales taxes, you discover what someone found out 2 years ago when they wrote that line. Now you resolve the ticket and move on with your day but you just wasted a couple man-hours on a non-issue that could have been resolved instantly from a code comment.
Comments are as much for the next guy as they are for you.
I worked on an enterprisey line of business app that assigned sales leads to salespeople.
The algorithm to do this was a multi-step process that was (1) rather complex (2) constantly being tweaked (3) very successful (4) contained a number of weighting factors that were utterly arbitrary even to veterans of this app.
It was full of many `if country_code==KERPLAKISTAN && day_of_week==MONDAY` -style weighting factors. Each represented some hard-won experience And when I say "hard-won" I mean "expensive" -- generating leads is expensive business.
We had a strong culture of informative commit messages, but this file had hundreds if not thousands of commits over the years.
It was the kind of code that resisted serious refactoring or a more streamlined design because it was a recipient of frequent change requests.
A few human-readable comments here and there went a loooong way toward taming the insanity and allowing that module to be worked on by developers besides the original author.
Knowing the why for many of these rules made it much easier to work with, and also allowed developers to be educated about the business itself.
Count me in as another old timer who agrees. I had a friend once throw the "code should be self-documenting" line at me once and it upsets me. That only really applies for code that is so simple it writes itself, and never has any gotchas hiding (and which useful project is like that?).
Leaning towards commenting "why" not "what" is another good general rule. "Self-documenting code" with sensible function and variables names and logical flow already cover the "what" fairly well.
>anything in the codebase that's not obvious to a new maintainer should have a brief, explanatory code comment
I'm not at all convinced that this is unpopular, but I think it's a whole lot harder than you're letting on. Unless you have a constant stream of new people coming in and you can convince them to give honest feedback, you don't actually know what's not obvious.
Except this doesn't retain the crucial information: why? It looks arbitrary. The thought that "some countries have sales tax rules dependent on the day of the week" may or may not be obvious from the context. At the very least, the comment pins a point in the space of all possible reasons for that piece of code - with it, you know it's related to sales tax and week days, and isn't e.g. a workaround for the bug with NaNs in tax rates that you saw on the issue tracker last week.
This is admittedly a trivial example, but ideally you want developers who understand why we're doing this.
Is this a quick thing somebody hacked in for a special, one-off, tax-free month in Kerplakistan as the country celebrates the birth of a princess?
Is this a permanent thing? Will there eventually be more weirdo tax rules for this country? Will there be others for other countries?
Knowing the "why" would help a developer understand the business, and reason about how best to work with this bit of code... should we just leave this ugly little special case in place? Should we have a more robust, extracted tax code module, etc.?
Commit messages help to accomplish this too, and can offer richer context than inline comments. Each has their place. Sifting through hundreds of commit messages in a frequently-updated module is not a great way to learn about the current state of the module, as the majority of those commit messages may well be utterly stale.
Ultimately the cost of having some concise inline comments is rather low, and the potential payoff is very large.
Remember that the longer term goal (besides the success of the business) of software is to have your developers gain institutional knowledge so that they can make more informed engineering decisions in the future.
I agree. The most obvious place to find an explanation of a piece of code, is right beside that code. Not hidden away in some git commit message or nested away in confluence.
I never understood why generated API docs are "documentation". That is source, trivial technical info which is easy to find in the source anyway.
I never got documentation about the thought processes, the iterations, the design meeting, the considerations, etc. Which is way, way more important to understanding a system in context than knowing "convertLinear" takes 2 unsigned ints.
> Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date
Interestingly, this has been a big point of discussion in the Dota 2 playerbase. Dota 2 is one of the most complex games ever created and it rapidly changes on the order of days or weeks. At one point, the in-game descriptions of spells were months or years out of date because they were being updated manually. After much hue and cry from the community, the developers finally made the tooltips get generated from the same code that determined the spells' effects. Things are a bit better now.
There is still a quite a bit of ways to go though, in terms of generating documentation for all the other mechanics in the game, which are crucial for gaining competency in the game, but which are only available due to third-party community efforts (often via people reading the game's codebase to understand subtleties), instead of being available inside the game.
This is a good example of a general rule of thumb I learned, if you need to do something once or twice do it by hand, but if you do something three or more times make it a function! Looks like Dota 2 updated their spells a few more than 3 times ;)
I use this rule for introducing abstraction: don't do it unless you have at least 3 different use cases you're abstracting, and the test suite doesn't count.
It's surprising that wasn't being done in the first place. I used the Warcraft 3 map editor, and it was simple to include references to attribute values in an object's description. Don't know why the DotA2 team didn't port that feature over when moving to the new engine.
> Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date
Not always - when you want to document the requirements (in whatever format), having them be separate from the code is often a plus. The code might implement the requirements incorrectly, so being able to recognise that is important.
I find this very similar to writing tests that are separate from your implementation. In fact, Cucumber/BDD tests try to make product requirements executable to validate the software has been written correctly to meet the requirements.
> Documentation is essential. How things work is an important thing to document.
I agree with this 100%. However, to be useful it needs to hit the right level of crudity. For most projects, a short (<10 pages) description of goals, design principles, architecture and an overview of interfaces is sufficient.
It is best when this exists as a standalone document which is a required reading for any new developer. After this they can look at module descriptions, function docs, code, etc. and understand how to make sense of it and how to add their code without breaking general principles of the project.
> Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date.
With this, I have some beef. In my experience the best documentation is the one that complements the code. Usually this means a short description by a human that explains what this chunk of code does and assumptions or limitations (e.g., "tested only for points A and B in troposphere") and IME most useful information is not derivable automatically. Auto-generated docs are very useful, but cannot replace clean explanations written by a human. My 2c.
I think there is room for this to be two documents if a project is large enough - one which resides inside source control which explains the design and how it works, and one which is external (sometimes managed by corporate level document control) which explains the "so what", including top level requirements and so forth.
These could be just one document if the project is small enough.
I think there's a lot of ambiguity in the phrase "generated from the code". When I hear it, I think if docs generated from doc-comments embedded in the code, which hare clean explanations written by a human. They just have the advantage of being right next to the code, so they're a lot more likely to be updated when the code changes than an entirely external document.
"Documentation" that is nothing more than the interface definitions in HTML for is worse than useless. I can get all of that from just reading the code.
> Writing a few hundred pages of specification and handing it over to the dev team is waterfall, and it is _this_ that the Agile manifesto signatories were interested in making clear
That doesn't sound too bad from a dev point of view, better than the opposite - half arsed specifications with no thought given to the important details. Though I can imagine a lot depends on what exactly you are trying to build.
I've been on a couple of projects like that, and in my experience the real reason behind this logic is that manager and product owner this way may make themselves indispensable, they can't ever get fired without practically killing the project (until it becomes completely unmaintainable and slowly dies off)
prefers working code over comprehensive documentation
This is funny because “working code” might just mean that it doesn’t crash. But does it actually do what it’s supposed to do or does it reliably deliver the wrong results? How would you know without documentation?
The software in the Therac didn’t crash, it quite reliably killed people with its “working code”.
> So I think "working code/application/program" is when it does what it is supposed to do.
And the point of the comment you're replying to is to ask what is "what it is supposed to do". How do you know what the answer to that question is, without documentation or a specification? And if you try to rely on just verbal communication, in a group of people probably larger than about 1, they're going to have different ideas about what the software is supposed to do.
Some of the most challenging problems I've encountered have been looking at code that does something. What it does is clear enough from the code. But why it does it, or should it do that, that is much harder to answer, particularly if the person who wrote it has left the company or it's been >6 months and they just don't remember.
My experience is you want to move fast by reusing good software. This means that well understood components should be well engineered and documented components, while poorly understood problems might reserve documentation for the future.
Agility requires a stable foundation. And a lot of places forget that.
Isn't this the old Unix tools idea, where programs are tools that ideally do one thing well, and with good inter-program communications developers can combine basic tools to build more complex programs?
I've worked in a company where I enforced as a PM to write Technical Document of every project we did along with the PID, the Functional Document (design and interactions). That Technical Document was all about to describe the essentials, and not go deeper into every single class written. It was intended for those developers who wanted to join the team and update that old project. With it was useful document and barely updated.
When it's only part of the ticket? Some teams call everything a "user story" when it might actually be it starts with the story format then adds a whole bunch of detailed acceptance criteria, the background for the story, etc.
The user story is a promise to have a conversation. I think that is usually well understood. From there I think you can fall into two camps: that conversation should result in a Jira/whatever ticket with all the requisite documentation for an agile team versus that conversation IS the essential information required to properly build the expected valuable working software.
Back to the question - what do you do about poor knowledge transfer in a project? I think a moderate de-emphasis on thinking of the user story text and the additional info like acceptance criteria etc. as self-sufficient documentation and adding more emphasis on that close relationship between developer, user, and maybe a tester, can help fill in big knowledge gaps.
Many years ago, I worked for a company where we were writing complex distributed telecom software and they had a wiki for documenting the system. I spent a few weeks meticulously documenting everything I did and anything that was touched by it (including defining all of the industry jargon and such). It was a great way to get a quick understanding of any part of the system, but I was the only person keeping it up to date so after a while I ran out of steam and stopped doing it. :(
I've come across the "documentation becomes quickly outdated" argument a lot, but nobody has ever been able to suggest a good alternative. The best I've found is to write design logs for proposed changes (which you then let other team members/stakeholders can review/comment on before it gets implemented) and decision logs for any decisions that are made. This way, them going out of date is expected and ok, as they become a history of ideas and decisions with their context and outcomes laid out. You don't necessarily have a snapshot of "the system right now" but you have a log of all the ideas and decisions that lead up to the current system.
We create "blueprints" that have system design and goals on new projects and how they fit into the ecosystem. We are supposed to update them after they go into production as things change, but seldom do. Still, going back and reviewing a design document helps.
I believe it is equally important to determine the level of abstraction for the documentation, such that updating it is an infrequent task (essentially, every line of code change should not trigger a document change). It is easier said than done, but that's the best compromise I have arrived it.
At the very least, the document should capture high-level (again this is relative term) design, possibly an architecture diagram of major interacting functional units. The success measure should be the relative ability to build a mental model of the system by looking at this document for any newbie.
That design document would be a start, and most likely not "quickly outdated".
My personal beef with the agile camp is precisely this: when they let go of documentation, they don't do the design doc as well, and all that remains of the system is thousands of incoherent stories and huge amount of code.
If you document via design logs and decision logs, then you don't need to document every line of code because its already done in the design log. If something unforeseen arises, then you have a discussion, make note on the outcome in a decision log and move on. That is, the documentation logs proposed decisions and outcome decisions, which should contain enough context that you can read them in isolation. Then you don't need to worry about documenting as you're coding or documenting the code.
If you diverge too far from the original design, you should probably have a rationale as to why, that gets reviewed by others: another design log and decision log.
These documents don't need to be long either, just a couple of sentences for each of context, what you propose, impact on other teams or systems, decision made may be enough for smaller things (so a paragraph or two) and for larger changes, you probably need the detail for everyone to really understand what, why and its impact. The alternative is to do these things blind.
> when they let go of documentation, they don't do the design doc as well, and all that remains of the system is thousands of incoherent stories and huge amount of code.
Yes, I agree that treating most documentation as project history is the practical way to go.
Another thing that helps is to write good commit messages giving the business context for a change. When code is reviewed, the commit messages should be reviewed as well. If they don't agree then that's a problem.
> I've come across the "documentation becomes quickly outdated" argument a lot
Me too, but I still feel that saying "documentation quickly becomes outdated" and refusing to write any, is not that different from saying "software quickly becomes full of bugs" and refusing to write unit tests. Yes, if you believe that something is doomed, and therefore you refuse to even try, it becomes a self-fulfilling prophecy.
Yes, documentation quickly becomes outdated, if no one updates it. Duh. If a person creates/modifies a part of code, they should also create/modify the corresponding documentation accordingly. (And the person reviewing the code should also review the docs.) If you don't do it, then yes, obviously, the documentation becomes outdated. Did you expect it to update magically by itself?
If you believe that documentation is useless in principle, go ahead and don't write it. Then you won't have to maintain it. Also, make sure to include memory tests to your interview process. If you believe that documentation is useful, write it, and maintain it. But if you have a documentation that you never update, you get the worst of both worlds.
Yes, thank you. A mindset which thinks that documentation is wasted due to a need to constantly update, is cousin to the mindset which thinks that software, once written, is a purchased asset which needs no further attention nor maintenance.
In Scrum, you don’t write code based off User Stories. The scrum team agrees to a set of Stories for the sprint, and then the scrum team breaks those stories into a set of Tasks which are the actual work that must be done. The User Stories are just something the product owner uses to show stakeholders that the project was successful.
1) In the Hermes Conrad sense, this is technically correct.
2) In my experience, this basically never happens.
Your comment encapsulates a lot of what I have come to call "Scrumbutt." It's Scrum, but. And while I have no idea if it's intended on your part, the sentiment is a fantastic way for a Scrum consultant--only some shade thrown; I've been a "DevOps consultant" before, after all--to come in and pull from deep in their Scrumbutt something to the effect of "you're doing it wrong, Scrum has not failed, you have failed Scrum."
Within epsilon of nobody does Scrum "as prescribed"--because the amount of responsibility that must be undertaken at all levels is virtually impossible to get full buy-in on--and as such the boil on our collective behind that it is persists because criticism is immediately bedeviled by Scotsmen of unknown provenance.
People might be interested in what Scrum is. I know I am. That’s why I pointed out the error. It was a shock to me to learn I wasn’t doing anything close.
Readers can do with the info what they want.
I’m not sure if I can say the same of your comment. You seem to be trying to make me feel bad for commenting? Or accusing me of hawking pointless info for consulting fees? I really can’t tell.
Traceability is where I'd start. First, ensure your stories are being linked to your code / pull requests / issues. That way you can figure out why something was changed in the future. This is key to determining whether you can change something down the road. Stories directly traceable to code can be powerful for capturing knowledge.
I might also recommend creating user stories for non-feature development like infrastructure and tech debt paydown (if you don't already). That way, all of the value flow is captured in one place and you're not just leading managers to see new features only.
Second, in addition to the user stories I'd advocate for strong background information about the context of the story as well as detailed acceptance criteria if you don't have that in place already.
They consider the User Stories + the code to be everything you need
Then they are Doing It Wrong™. Note that there's nothing in the Agile Manifesto OR the Scrum Guide that says "don't write documentation." The closest you get is in the AM where it says "We have come to value ... Working software over comprehensive documentation". But note that immediately after that it says "That is, while there is value in the items on the right, we value the items on the left more." IOW, the Agile Manifesto explicitly endorses the value of documentation!
Remember this the next time somebody tries to tell you that "we don't do documentation because we're Agile." Anybody running that line is Full Of Shit™.
> Does anyone have any suggestions on how to fix this?
Have a product wiki (e.g. MediaWiki).
Have documentation in source code that compiles to HTML code, which can be linked to/from the product wiki (e.g. JavaDoc in Java, Natural Docs for languages that do not directly support compilable documentation). Make building and publishing this documentation a part of the continuous integration.
When you have this, make it a part of code reviews to ask "where is this documented?" for those kinds of things that are easy to remember today, but no one will remember it a few months later. In other words, make it a "code+doc review".
(Don't be dogmatic about whether the information should go to code documentation, unit test documentation, or wiki. Use common sense. If it only related to one method, it's probably the code; if it related to a use case, it's probably the unit test that verifies that use case; if it is a general topic that has an impact on many parts of the program, it probably deserves a separate wiki page.)
> Have documentation in source code that compiles to HTML code, which can be linked to/from the product wiki (e.g. JavaDoc in Java, Natural Docs for languages that do not directly support compilable documentation). Make building and publishing this documentation a part of the continuous integration.
Are you referring to something like Knuth's Literate Programming (en.m.wikipedia.org/wiki/Literate_programming)? As a non-professional who's learning to develop on the side, something that follows more of a natural language approach appeals to me, as sometimes I have a few months between working on my project, and comments on my source code help me not to forget why I do certain things in the code. However, I'm not doing Literate Programming, just python with comments.
No. I think one should organize the code as the code needs to be organized, and the documentation can either follow along (if it describes parts of code contained within the same file) or be placed separately (if it relates to multiple files), where "separately" could still be a package-level JavaDoc, or an external wiki.
I have never tried the Literal Programming, so perhaps I am out of my depth here, but I strongly suspect it only works after one has already mastered the usual ways of programming. That you do not have to structure the code qua code, because you can already do it in your head. But it's hard to imagine what one has never done before.
For example, if you never tried programming the usual way, how do you know when and why to put "Header files to include" in your Literal code? It's only because you can imagine the constructed code, you know where the header files go in the result, so you know where to place them in the Literal version. Otherwise, it would look quite arbitrarily.
I don't know about documentation in Python, but the JavaDoc (and Natural Docs) work like this: You put comments to classes and methods, or packages (and files), along with the code. So you can read them and write them while you are looking at the code. But then you run a "documentation compiler" that extracts the comments and builds a separate HTML website out of them. Here you can browse and read about what the individual classes and methods do. The idea is to make this a part of the continuous integration, so that whenever you update the source code and the related comment, the HTML website also gets updated.
Java supports this out of the box. When you install the Java compiler, you also install the Java documentation compiler. When you read the official documentation to the standard Java classes, those were made using exactly the same tools you are encouraged to use.
I don't know whether Python has something like this. If yes, go ahead and use it. If not, look at Natural Docs -- it is a system to provide this functionality to languages that do not support it out of the box. Just try it: document a part of your existing project, compile the docs, and see whether you can imagine any value in reading that.
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.
+ 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.
Good point: it's far, far better to be proactive, than wait for management to "recognize you".
Being a part of the early decision making processes has been a challenge for me as a remote employee. In larger companies, there are lots of meetings, discussions, and decisions that happen before anyone talks to the engineering staff is brought in. But, by basically being nice, asking questions, and really getting involved, I've been able to "weasel" my way into some of these discussions.
Once you get involved early on, there's so much more clarity around the one liner "requests" that often get farmed out.
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.
>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)
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.
>>> 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.
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.
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.
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.
Anyone know how to demonstrate this to management? I’m quite certain that my boss think I’m a crappy developer, because I usually take longer than other to produce the same amount of code. But I’ve reduce the amount of code we need to write with three quarters, but that is harder to demonstrate.
Reducing the amount of code shouldn't be the end goal, but a way of increasing quality.
You should seek to demonstrate instead that you're making software that is more malleable, has less bugs, is easier for new hires to understand, is easy to add new features, etc.
Of course it is not an end goal. But a quarter as much code has (in general, everything else equal) a quarter as much bugs, a quarter of the amount of code to read and understand for new hires a quarter as much code to take into account when adding new features. But none of these things are easy to measure or demonstrate. It is just easier to see that Ma8ee took 1.5x weeks to write 10,000 loc while other developer wrote 40,000 loc in x weeks.
I'm not disagreeing with the idea that there is variability in developer productivity. However, quantifying the most productive engineers by throwing around a specific random factor such as "10x" is rather idiotic.
You have entire blog posts by Steve McConnell of Code Complete fame devoted to defending the 10x claim by citing 20 to 50 year old research that shows 5x to 20x differences across certain dimensions and then him falling back to the 10x thing. Not one single sentence where he is being self aware enough to spell out the most likely reason for "10x" being so prominent: 10 is the base of the decimal system and as such psychologically attractive to use.
> Both Steve Jobs and Mark Zuckerberg have said that the best engineers are at least 10 times more productive than an average engineer.
I know I'm venturing into ad hominem territory with this, but first of all: Steve Jobs wasn't a programmer. Mark Zuckerberg, well does he even qualify as a programmer nowadays? How well can he quantify programmer productivity? His decision to use PHP led Facebook to create HHVM and Hack. Is this the 10x developer way?
Anyways, the question to me is: Is it possible for average software engineers to write good software?
Perhaps "10X engineer" is just an easier thing to say than "5 to 20X engineer as described by this paper." Perfect numerical accuracy is not needed to make the point that there is a lot more variance in the productivity of engineers than there is with most jobs.
If someone suggests you focus on the 20% of customers who make 80% of your revenue, and you run the numbers and find a 75-25 distribution, should you call the person making the suggestion an idiot?
> 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).
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.
I think feedback fatigue is a real thing though. The comment about only leaving feedback once hit home to me. It's rare I bother reviewing something twice even if asked, and especially if my original round of feedback didn't seem to change anything (which I understand is totally reasonable in many cases, but still a little disappointing).
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.
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.
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.
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.
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.
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[ 0.20 ms ] story [ 241 ms ] threadIt 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
> 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.
Software will always be a spread of reliability requirements, from pacemakers on one side to excel reports on the other. Part of being a responsible user is choosing software with the right balance of economics and reliability for the job.
This all takes a bird-eye view and a long perspective, very unlike quarter-results-driven development.
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.
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.
> There are engineers who can accomplish difficult engineering tasks when they are given clear requirements and engineers have the ability to find creative solutions when they are provided with problems and jobs rather than requirements and tasks.
I feel like I could perform adequately in either environment. The problem is I've previously found myself in environments where I'm expected to come up with creative solutions to a problem, but I have no access to the customer or even a simulated environment where I could try to do something similar to what a customer would do.
In this kind of case, it's impossible to really know how to articulate your requirements, because all you can use is a fantasy model of hypotheticals. But requests for more precise requirements are potentially brushed off as wanting to be spoon-fed what you need to do and having inability or unwillingness to think creatively.
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...
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.
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
I like to do it early also, to make sure that the new script, if imported from by a sibling module, is inert.
An example would be a scripts/ folder and sharing a few functions between scripts w/o duplicating.
In some cases I don't have a choice. Initialization of a flask app/ORM stuff/etc has to be done in the correct order.
I think the general rule of thumb I follow is: avoiding keeping code that'd "run" in the root level. Keep it in blocks (normally to me functions) has the added effect of labeling what is does.
What I don't do: I don't introduce classes until very late. In hindsight, every time I tried to introduce a complicated object model, I feel I tended to overengineer / encounter YAGNI
“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.”
And, if you are on the wrong side, it is very "effective" at ruining your life.
Most of us would take a bit less "effective" in order to avoid that, thanks.
Have you compared it to others? Strained is the last word I'd use to qualify how effective it is...
"The tool is squeaky but it gets the job done" - you wouldn't expect the speaker to do anything about the squeaks. Squeaking is tolerable.
"The tool does the job but it's squeaky" - you would expect the speaker to do something about the squeaks. Doing the job isn't good enough.
Your comment is most easily read as not disapproving of authoritarian government when it is effective.
Not the best example of crowd wisdom.
Perhaps you should do the same for barrkel? I read your parent as a simple explanation to solveit why their comment may have been misconstrued by bsder -- a question solveit directly asked.
Singaporean here. The government's mainly effective for tasks that are on a happy path. If your particular case falls through the cracks, it often takes phone calls, printing, postage, and weeks or months of waiting to get stuff done.
(Personal experience trying to get business stuff done not as a Private Limited company.)
That sounds like the happy path for dealing with the Canadian government. Well, except the months part.
If someone produced an insulin pump that you implanted, worked perfectly for life, but killed 1 person in 1,000 randomly, people would be screaming for the head of the CEO of that company rather than calling it "effective".
Effective just means it achieves the intended outcome, it's not a value judgment on the goodness of that intention.
I like being partially or fully nude in the home, occasionally chewing gum, and having the right to freely criticize or endorse ideology on its own merits; even if it sometimes sucks to see dirty black spots on the sidewalk, or to hear people making weak arguments just to upset eachother.
Certainly a weird cosmopolitan fascist (u|dys)topia.
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."
"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.
I'm sure another author has put the same sentiment out there before, but it's not every day I see such a nice phrasing of it.
I mean, the point of short quotes is to be memorable and get future listeners to hunt for the reason behind them. "The sun will rise tomorrow" may also be meaningless for some people on its own.
Nothing wrong with elaborating on this subject again via a blog post, I was just pointing out to the commenter who's never heard this expressed before that it has a long history, that's all.
http://theindependent.sg/li-hongyi-singapore-has-a-lot-of-pr...
I keep on saying that Software Literacy is a real thing. And that this current generation of leaders are like Charlemagne - he was the first Holy Roman Emperor and the last who was illiterate.
Interesting to see it in practise
Even Singapore's PM has to put up with smug Haskell programmers
And probably he was the best of what followed as well, so this literacy thing didn't go as well, where power figures were concerned...
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.
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.
Also the sentence 'algorithms that applied to algorithms produce a better model' has a strong smell of halting problem, at least to this nose.
Intuitively, software can be modeled as a graph of modules with lines representing connections between modules. An aspect of "good software" can be attributed to some metric described by the graph, let's say the amount of edges in the graph... the less edges the less complex. An optimization algorithm would probably take this graph as an input and output a graph that has the same functionality but less edges. You can call this a "better design." This is all really fuzzy and hand wavy but if you think about it from this angle I'm pretty sure you'll see that a axiomatic formalization can be done along with an algorithm that can prune edges from a graph (or in other words, improve a design by lowering complexity)
A computer program is a machine that translates the complexity of the real world into an ideal system that is axiomatic and highly, highly simplified. Such a system can be attacked by formal theory unlike real world issues like what constitutes a good car.
In my experience, developer-side evaluation has a very low impact (I was about to write: zero) on the perceived and actual goodness of the software itself. Which is tied mostly to factors such as user experience, fit to the problem it was designed for and to the organization(s) it is going to live in (user experience again). These properties do not strike me as amenable to algorithmic improvement, no more than "pleasant body lines and world class interiors" in the original car analogy. But they are a (big) part of good software design, besides being the 'raison d'etre' of the darned thing to begin with.
But let's forget cars, as hard as it is. Few months ago HN was running the story about developing software in Oracle. Now, Oracle may be by now a little soft around the edges, but I think that most would agree that it has been setting the standard for (R)DBMS for decades. Success may not on itself be the tell-all measure of software goodness, but the number of businesses that have been willing to stake the survival of their data on Oracle is surely a measure of its perceived goodness (as that other elusive factor - hipness - tends not to be paramount in the DBMSs business).
The development side story, taken as face value, was pure horror (https://news.ycombinator.com/item?id=18442941). Everything in it spoke bad, outdated, rotting design. The place must be teeming with ideas on how to improve just about everything in that environment. And yet if that came to be, maybe by some nifty edge pruning algorithm, it would do nothing to improved the goodness-to-the-world measure of the software, not until the internals' improvement translated to observables in the user base experience.That type of improvements will still require vaste amount of non-algorithmic design and, in the meantime, a very concrete risk will be run of deteriorating the overall user experience (because ehi, snafus will happen).
This (internals are just a small part of the story) is one of the reasons why so many reimplementations I have seen failed ("ehi, let's rewrite this piece of shit and make it awesome") and the reason because everyone resists the move from IPV4 to IPV6. I could think of many more examples.
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?
(PDF available here: http://pespmc1.vub.ac.be/ASHBBOOK.html )
Cybernetics might be the "missing link" for what you're talking about.
I'm looking more for a theory of modules and relationships. Something that can formalize the ways we organize code.
It sounds like CT is what you're after (to the extent that we have it at all yet...)
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.
I think about that whenever I get frustrated about a vague spec or lack of details. It's the job!
I hope he meant separating out the ambiguity rather than concentrating it. :)
"...the designers job is not to pass along "the design" but to pass along "the theories" driving the design. Knowledge of the theory is tacit in owning..."
Well said. Thank you!
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?
Documentation is essential. How things work is an important thing to document. Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date. It still has problems (What do you do when the code and the documentation disagree? Which is correct?), but they're not as severe as the problems that arise when there is no documentation at all.
What is less useful is having comprehensive documentation for those things that are yet to exist. Writing a few hundred pages of specification and handing it over to the dev team is waterfall, and it is _this_ that the Agile manifesto signatories were interested in making clear.
I'd fix it with strategic DDD - I'd develop at least a "ubiquitous language" (or a UL): I'd get others to work with me on having clear terminology and making sure that is used consistently both in user stories and in the code base. That's table stakes.
I'd then event storm the contexts I'm working in and start to develop high level documentation.
Even at this point relationships between systems emerge, and you get to draw circles around things and name them (domains, contexts), and the UL gets a bit better. At this point you can start to think about describing some of your services using the UL and the language of domains and contexts.
By that point, people should start to click that this makes life easier - there is less confusion, and you're now all working together to get a shared understand of the design and the point of DDD is that the design and the code match.
The first part (all 100+ pages of it), of the Millet and Tune book on DDD will pay you dividends here.
If that doesn't work, look around for somewhere else to work that understands that software development is often a team sport and is committed to making that happen.
> Ideally it should be in version control and be generated from the code ..
May I ask if you have suggestions for tooling to capture the high level documentation. We use javadoc a little, but it seems best for lower level reference. Also for diagrams, like sequence diagram and/or state machines, how do you capture this?
Thanks.
Or better yet: generate your state machines from same format you would use to generate visual representation.
Just build a product specification for how the product works (which is useful documentation), not how the product will work (which is waterfall).
We're experimenting with this a little, and I'm getting into document-driven development a little: if the product spec is in markdown, why not create a pull request on it as part of your story/project planning that shows the changes that would happen as a consequence of your work. Once the story is done, you can merge the pull request, even. We're not quite there with this yet, but I'm optimistic.
Putting design assets into your repo is also acceptable, and also paying time and attention to commit messages can be really, really helpful. I love this talk, for example: https://brightonruby.com/2018/a-branch-in-time-tekin-suleyma...
Generally, this falls into two categories.
1. Hacks/kludges to get around bugs in hardware, external services, or included libraries. These manifest in code as incomprehensible, ugly bits of code that are difficult to distinguish from code that is simply "sloppy" or uninformed. More importantly, they represent hard-won knowledge. It often takes many programmer-hours to discover that knowledge, and therefore many dollars. Why throw it away? (Tip: include the version of the dependency in the comment, ie)
...so that future programmers (including you) can more easily judge whether the kludge is still needed in the future.2. Business logic. This too is difficult/impossible to discern from looking at code. Often, one's git commit history is sufficient. But there are any number of scenarios where version control history can become divorced from the code, or require a fair bit of git/hg/svn/whatever spelunking to access. And this of course becomes increasingly onerous as a module grows. If there are 200 lines of code in a given module, it is a significant time investment to go git spelunking for the origins of all 200 lines of code. Some concise internal documentation in the form of code comments can save an order of magnitude or two of effort.
This is pretty easy to enforce at code review time, prior to merging.In the first place, only a true maniac would intentionally update
...without updating the associated comment. If they do neglect to update it, that's an easy catch at review time.But I agree with your statement that there should be a pointer to the business rules somewhere. Otherwise it's difficult to have a meeting with the business side and ask, "Has anything here changed?" I think that's the biggest thing people miss out -- It's not that hard to find the thing in the code if things change. It's super hard to make sure you are on top of all the business requirement changes.
country_code==FIFTY_FIVE and day_of_week==ONE
[NB 30 isn't an exaggeration - I think the vast team who wrote it were paid by the abstraction or something].
> "There is a famously bad comment style: ...
Don't laugh now, wait until you see it in real life."
But in the trade-off in code readability was probably the cause of many other mistakes, so probably ended up further behind.
Comments are as much for the next guy as they are for you.
Code smell doesn't mean you should never do it, just that often there's a better way.
I worked on an enterprisey line of business app that assigned sales leads to salespeople.
The algorithm to do this was a multi-step process that was (1) rather complex (2) constantly being tweaked (3) very successful (4) contained a number of weighting factors that were utterly arbitrary even to veterans of this app.
It was full of many `if country_code==KERPLAKISTAN && day_of_week==MONDAY` -style weighting factors. Each represented some hard-won experience And when I say "hard-won" I mean "expensive" -- generating leads is expensive business.
We had a strong culture of informative commit messages, but this file had hundreds if not thousands of commits over the years.
It was the kind of code that resisted serious refactoring or a more streamlined design because it was a recipient of frequent change requests.
A few human-readable comments here and there went a loooong way toward taming the insanity and allowing that module to be worked on by developers besides the original author.
Knowing the why for many of these rules made it much easier to work with, and also allowed developers to be educated about the business itself.
Leaning towards commenting "why" not "what" is another good general rule. "Self-documenting code" with sensible function and variables names and logical flow already cover the "what" fairly well.
I'm not at all convinced that this is unpopular, but I think it's a whole lot harder than you're letting on. Unless you have a constant stream of new people coming in and you can convince them to give honest feedback, you don't actually know what's not obvious.
Is this a quick thing somebody hacked in for a special, one-off, tax-free month in Kerplakistan as the country celebrates the birth of a princess?
Is this a permanent thing? Will there eventually be more weirdo tax rules for this country? Will there be others for other countries?
Knowing the "why" would help a developer understand the business, and reason about how best to work with this bit of code... should we just leave this ugly little special case in place? Should we have a more robust, extracted tax code module, etc.?
Commit messages help to accomplish this too, and can offer richer context than inline comments. Each has their place. Sifting through hundreds of commit messages in a frequently-updated module is not a great way to learn about the current state of the module, as the majority of those commit messages may well be utterly stale.
Ultimately the cost of having some concise inline comments is rather low, and the potential payoff is very large.
Remember that the longer term goal (besides the success of the business) of software is to have your developers gain institutional knowledge so that they can make more informed engineering decisions in the future.
I never got documentation about the thought processes, the iterations, the design meeting, the considerations, etc. Which is way, way more important to understanding a system in context than knowing "convertLinear" takes 2 unsigned ints.
Interestingly, this has been a big point of discussion in the Dota 2 playerbase. Dota 2 is one of the most complex games ever created and it rapidly changes on the order of days or weeks. At one point, the in-game descriptions of spells were months or years out of date because they were being updated manually. After much hue and cry from the community, the developers finally made the tooltips get generated from the same code that determined the spells' effects. Things are a bit better now.
There is still a quite a bit of ways to go though, in terms of generating documentation for all the other mechanics in the game, which are crucial for gaining competency in the game, but which are only available due to third-party community efforts (often via people reading the game's codebase to understand subtleties), instead of being available inside the game.
Not always - when you want to document the requirements (in whatever format), having them be separate from the code is often a plus. The code might implement the requirements incorrectly, so being able to recognise that is important.
I find this very similar to writing tests that are separate from your implementation. In fact, Cucumber/BDD tests try to make product requirements executable to validate the software has been written correctly to meet the requirements.
I agree with this 100%. However, to be useful it needs to hit the right level of crudity. For most projects, a short (<10 pages) description of goals, design principles, architecture and an overview of interfaces is sufficient.
It is best when this exists as a standalone document which is a required reading for any new developer. After this they can look at module descriptions, function docs, code, etc. and understand how to make sense of it and how to add their code without breaking general principles of the project.
> Ideally it should be in version control and be generated from the code, because then it's less likely to go out of date.
With this, I have some beef. In my experience the best documentation is the one that complements the code. Usually this means a short description by a human that explains what this chunk of code does and assumptions or limitations (e.g., "tested only for points A and B in troposphere") and IME most useful information is not derivable automatically. Auto-generated docs are very useful, but cannot replace clean explanations written by a human. My 2c.
These could be just one document if the project is small enough.
"Documentation" that is nothing more than the interface definitions in HTML for is worse than useless. I can get all of that from just reading the code.
That doesn't sound too bad from a dev point of view, better than the opposite - half arsed specifications with no thought given to the important details. Though I can imagine a lot depends on what exactly you are trying to build.
Not to be rude, but yes: switch employers. This is not something you can fix on the employee level, it is a management issue.
It might be a team culture or company culture issue, and even radical changes in the management are not enough to fix it.
This is funny because “working code” might just mean that it doesn’t crash. But does it actually do what it’s supposed to do or does it reliably deliver the wrong results? How would you know without documentation?
The software in the Therac didn’t crash, it quite reliably killed people with its “working code”.
So I think "working code/application/program" is when it does what it is supposed to do. Including not crashing.
And the point of the comment you're replying to is to ask what is "what it is supposed to do". How do you know what the answer to that question is, without documentation or a specification? And if you try to rely on just verbal communication, in a group of people probably larger than about 1, they're going to have different ideas about what the software is supposed to do.
Some of the most challenging problems I've encountered have been looking at code that does something. What it does is clear enough from the code. But why it does it, or should it do that, that is much harder to answer, particularly if the person who wrote it has left the company or it's been >6 months and they just don't remember.
Agility requires a stable foundation. And a lot of places forget that.
If you have sufficiently detailed user stories, they can be.
Back to the question - what do you do about poor knowledge transfer in a project? I think a moderate de-emphasis on thinking of the user story text and the additional info like acceptance criteria etc. as self-sufficient documentation and adding more emphasis on that close relationship between developer, user, and maybe a tester, can help fill in big knowledge gaps.
I've come across the "documentation becomes quickly outdated" argument a lot, but nobody has ever been able to suggest a good alternative. The best I've found is to write design logs for proposed changes (which you then let other team members/stakeholders can review/comment on before it gets implemented) and decision logs for any decisions that are made. This way, them going out of date is expected and ok, as they become a history of ideas and decisions with their context and outcomes laid out. You don't necessarily have a snapshot of "the system right now" but you have a log of all the ideas and decisions that lead up to the current system.
At the very least, the document should capture high-level (again this is relative term) design, possibly an architecture diagram of major interacting functional units. The success measure should be the relative ability to build a mental model of the system by looking at this document for any newbie.
That design document would be a start, and most likely not "quickly outdated".
My personal beef with the agile camp is precisely this: when they let go of documentation, they don't do the design doc as well, and all that remains of the system is thousands of incoherent stories and huge amount of code.
If you diverge too far from the original design, you should probably have a rationale as to why, that gets reviewed by others: another design log and decision log.
These documents don't need to be long either, just a couple of sentences for each of context, what you propose, impact on other teams or systems, decision made may be enough for smaller things (so a paragraph or two) and for larger changes, you probably need the detail for everyone to really understand what, why and its impact. The alternative is to do these things blind.
> when they let go of documentation, they don't do the design doc as well, and all that remains of the system is thousands of incoherent stories and huge amount of code.
Absolutely agreed.
Another thing that helps is to write good commit messages giving the business context for a change. When code is reviewed, the commit messages should be reviewed as well. If they don't agree then that's a problem.
Me too, but I still feel that saying "documentation quickly becomes outdated" and refusing to write any, is not that different from saying "software quickly becomes full of bugs" and refusing to write unit tests. Yes, if you believe that something is doomed, and therefore you refuse to even try, it becomes a self-fulfilling prophecy.
Yes, documentation quickly becomes outdated, if no one updates it. Duh. If a person creates/modifies a part of code, they should also create/modify the corresponding documentation accordingly. (And the person reviewing the code should also review the docs.) If you don't do it, then yes, obviously, the documentation becomes outdated. Did you expect it to update magically by itself?
If you believe that documentation is useless in principle, go ahead and don't write it. Then you won't have to maintain it. Also, make sure to include memory tests to your interview process. If you believe that documentation is useful, write it, and maintain it. But if you have a documentation that you never update, you get the worst of both worlds.
2) In my experience, this basically never happens.
Your comment encapsulates a lot of what I have come to call "Scrumbutt." It's Scrum, but. And while I have no idea if it's intended on your part, the sentiment is a fantastic way for a Scrum consultant--only some shade thrown; I've been a "DevOps consultant" before, after all--to come in and pull from deep in their Scrumbutt something to the effect of "you're doing it wrong, Scrum has not failed, you have failed Scrum."
Within epsilon of nobody does Scrum "as prescribed"--because the amount of responsibility that must be undertaken at all levels is virtually impossible to get full buy-in on--and as such the boil on our collective behind that it is persists because criticism is immediately bedeviled by Scotsmen of unknown provenance.
People might be interested in what Scrum is. I know I am. That’s why I pointed out the error. It was a shock to me to learn I wasn’t doing anything close.
Readers can do with the info what they want.
I’m not sure if I can say the same of your comment. You seem to be trying to make me feel bad for commenting? Or accusing me of hawking pointless info for consulting fees? I really can’t tell.
I might also recommend creating user stories for non-feature development like infrastructure and tech debt paydown (if you don't already). That way, all of the value flow is captured in one place and you're not just leading managers to see new features only.
Second, in addition to the user stories I'd advocate for strong background information about the context of the story as well as detailed acceptance criteria if you don't have that in place already.
Then they are Doing It Wrong™. Note that there's nothing in the Agile Manifesto OR the Scrum Guide that says "don't write documentation." The closest you get is in the AM where it says "We have come to value ... Working software over comprehensive documentation". But note that immediately after that it says "That is, while there is value in the items on the right, we value the items on the left more." IOW, the Agile Manifesto explicitly endorses the value of documentation!
Remember this the next time somebody tries to tell you that "we don't do documentation because we're Agile." Anybody running that line is Full Of Shit™.
Have a product wiki (e.g. MediaWiki).
Have documentation in source code that compiles to HTML code, which can be linked to/from the product wiki (e.g. JavaDoc in Java, Natural Docs for languages that do not directly support compilable documentation). Make building and publishing this documentation a part of the continuous integration.
When you have this, make it a part of code reviews to ask "where is this documented?" for those kinds of things that are easy to remember today, but no one will remember it a few months later. In other words, make it a "code+doc review".
(Don't be dogmatic about whether the information should go to code documentation, unit test documentation, or wiki. Use common sense. If it only related to one method, it's probably the code; if it related to a use case, it's probably the unit test that verifies that use case; if it is a general topic that has an impact on many parts of the program, it probably deserves a separate wiki page.)
Are you referring to something like Knuth's Literate Programming (en.m.wikipedia.org/wiki/Literate_programming)? As a non-professional who's learning to develop on the side, something that follows more of a natural language approach appeals to me, as sometimes I have a few months between working on my project, and comments on my source code help me not to forget why I do certain things in the code. However, I'm not doing Literate Programming, just python with comments.
I have never tried the Literal Programming, so perhaps I am out of my depth here, but I strongly suspect it only works after one has already mastered the usual ways of programming. That you do not have to structure the code qua code, because you can already do it in your head. But it's hard to imagine what one has never done before.
For example, if you never tried programming the usual way, how do you know when and why to put "Header files to include" in your Literal code? It's only because you can imagine the constructed code, you know where the header files go in the result, so you know where to place them in the Literal version. Otherwise, it would look quite arbitrarily.
I don't know about documentation in Python, but the JavaDoc (and Natural Docs) work like this: You put comments to classes and methods, or packages (and files), along with the code. So you can read them and write them while you are looking at the code. But then you run a "documentation compiler" that extracts the comments and builds a separate HTML website out of them. Here you can browse and read about what the individual classes and methods do. The idea is to make this a part of the continuous integration, so that whenever you update the source code and the related comment, the HTML website also gets updated.
Java supports this out of the box. When you install the Java compiler, you also install the Java documentation compiler. When you read the official documentation to the standard Java classes, those were made using exactly the same tools you are encouraged to use.
I don't know whether Python has something like this. If yes, go ahead and use it. If not, look at Natural Docs -- it is a system to provide this functionality to languages that do not support it out of the box. Just try it: document a part of your existing project, compile the docs, and see whether you can imagine any value in reading that.
- 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
communicationChannels = nrOfTeams(nrOfTeams-1)/2
More people should read The Mythical Man-month
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.
Being a part of the early decision making processes has been a challenge for me as a remote employee. In larger companies, there are lots of meetings, discussions, and decisions that happen before anyone talks to the engineering staff is brought in. But, by basically being nice, asking questions, and really getting involved, I've been able to "weasel" my way into some of these discussions.
Once you get involved early on, there's so much more clarity around the one liner "requests" that often get farmed out.
Managers are very unhappy when I tell them of all the knowledge I've developed.
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.
What makes you think so?
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
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.
I suppose he wrote this for other people in the Singapore civil service.
This article is full of good ideas, an antidote to creeping corporate take over of software projects - make this required reading for software projects.
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 :-)
I've seen plenty of poor decisions that cause 10x the work, and end up with something 10x less maintainable.
You should seek to demonstrate instead that you're making software that is more malleable, has less bugs, is easier for new hires to understand, is easy to add new features, etc.
/sarcasm
Edit: fwiw id work with ya though. Caring enough to try is half the battle.
You have entire blog posts by Steve McConnell of Code Complete fame devoted to defending the 10x claim by citing 20 to 50 year old research that shows 5x to 20x differences across certain dimensions and then him falling back to the 10x thing. Not one single sentence where he is being self aware enough to spell out the most likely reason for "10x" being so prominent: 10 is the base of the decimal system and as such psychologically attractive to use.
> Both Steve Jobs and Mark Zuckerberg have said that the best engineers are at least 10 times more productive than an average engineer.
I know I'm venturing into ad hominem territory with this, but first of all: Steve Jobs wasn't a programmer. Mark Zuckerberg, well does he even qualify as a programmer nowadays? How well can he quantify programmer productivity? His decision to use PHP led Facebook to create HHVM and Hack. Is this the 10x developer way?
Anyways, the question to me is: Is it possible for average software engineers to write good software?
If someone suggests you focus on the 20% of customers who make 80% of your revenue, and you run the numbers and find a 75-25 distribution, should you call the person making the suggestion an idiot?
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).
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.
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.
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.