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Comment by sillysaurus3 | Hacker News Reader

I think it's self-evident that there is no theoretical basis for software development in the way that would satisfy your criteria. Software dev is generally a scattershot haphazard endeavor that involves trying dozens of angles until one of them works. That's an unsatisfying answer, but if we try to hide from the implications just because we don't like it, we'll end up creating companies that fail to startups without these constraints.

It's also self-evident that in most situations, correctness and reliability aren't a concern. The counterexamples account for maybe 1% of the field. 99% of the time, if your program breaks, you can pay someone to go fix it and no serious harm was done. Even Github outages, which affect almost all of us, hardly matter.

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>I think it's self-evident that there is no theoretical basis for software development in the way that would satisfy your criteria.

Yes. Writing software is not math. Does it use math concepts? Of course, but so does just about everything else. While we're at it, writing software is also not engineering, even though there are engineering concepts that can be applied.

Writing software is its own thing. Pretending that it's something else (like math or engineering) invariably leads to category errors.

Think about food recipes. They certainly use measurements and timing, and engineering principles can certainly be applied (especially when executing them on an industrial scale) but they are not math (or engineering) either. Examining the measurements, timing, and the production chain doesn't tell you anything about whether the recipe is delicious or inedible.

Arguing that a piece of software should be "proven correct" makes about as much sense as arguing that a recipe should be "proven correct". You might as well judge the recipe by the standards of poetry ("Does it have evocative imagery? Does it rhyme or alliterate well?").

People have been chasing the unicorn of software correctness proofs for 60 years, with a notable lack of generalizable success (there are plenty of toy examples, of course). What usually happens is that the "programming is math" people come up with some bizarre academic language that no real-world programmer would use unless forced to do so at gunpoint (followed by the new language sinking without a trace). Alternatively, the "programming is engineering" people come up with some baroque formal process that requires you to write a 500 page document and get six committees to sign off on it before you can write "Hello, world". I'm old enough that I've seen these things happen multiple times.

>It's also self-evident that in most situations, correctness and reliability aren't a concern.

I wouldn't say they aren't a concern at all, but if you're wasting six months screwing around with formal proofs, UML diagrams, or things of that nature, while in the meantime your competitor is iterating three or four times, that is definitely a concern. Operate that way and your milkshake is going to be drunk, yo.

>Writing software is not math.

You're wrong, and I've explained this upthread.

>Think about food recipes.

Do you have experience with non-imperative programming paradigms? I'm sorry to say that the comparison to recipes in this context seems fairly naive.

>People have been chasing the unicorn of software correctness proofs for 60 years, with a notable lack of generalizable success (there are plenty of toy examples, of course).

Static type systems are arguably a product of this, especially advanced ones like Haskell's.

>What usually happens is that the "programming is math" people come up with some bizarre academic language that no real-world programmer would use unless forced to do so at gunpoint (followed by the new language sinking without a trace).

Now you're just being anti-intellectual. The whole point is that the real-world programmers are stumbling into all this crap constantly without realizing it. It's completely fucking unavoidable and very much tied up with the fact that programming is math. The only question is what you choose to do about that: learn the math, or stay ignorant.

I don't mean to be condescending but I find comparing UML diagrams and proof assistants a little offensive (among other things), and it suggests you don't know what you're talking about. Modern proof assistants and other formal techniques like dependent typing happen while you're programming (Idris/Agda) or generate programs themselves (Coq), they aren't some sort of Waterfall-ish thing where you have to deal with all the ceremony before you start to get shit done. On the contrary, you get shit done, and it works better when you're done with it too.

Your post contains a lot of unnecessary aggression. Rather than suggesting someone "doesn't know what they're talking about", just provide evidence to the contrary.

That aside, there seems to be something missing in your analysis, or there would be a lot of successful startups stealing the market using proof assistants and formal techniques. It's not anti intellectual to point out that programmers don't want to use academic languages that have poor usability, steep learning curves, and garbage for standard libraries.

Consider when a regular house is being built. There are many problems that could be avoided if an engineering firm spent an entire year analyzing the designs and their interactions with the target site. However, that's not done because it takes significantly longer and costs obscene amounts of money.

It's easier for the construction crew to fix problems as they encounter them and for the owner to do repairs on the house 40 years later. Yeah, the house isn't as reliable, but it cost 100,000 instead of 1,000,000.

If you want developers and managers on your side, you need to show them benefits over the quick development of python/php/Javascript other than bugs in edge cases being less frequent. Don't just bemoan how unenlightened everyone is.

Well, all the naysayers could also do some research instead of being as dismissive as they are. Here's an example of actual use of formal methods: http://lamport.azurewebsites.net/tla/amazon.html Why aren't they used more widely? Because when people hear"math", they immediately think of it as academic. It would also be overkill for most projects.

TLA is one of the systems that are actually very practical. You can go up or down as many abstraction layers as you need . There's a great introduction written by @pron on his blog [1].

However, it's worth pointing out that you don't magically get the final program out of the TLA proof. The proof only works for the abstraction level that you chose to write it at.

[1] https://pron.github.io/

While it is true a full formal proof of a C++ program, for example can take significantly longer and cost obscene amounts of money, that is not true when starting with this approach from the ground up.

There is also a certain level of compromise. By relaxing the requirements a tad, you can still gain many of the benefits while maintaining the light and nimble feel.

So why don't startups use this? Well because there are entrenched technologies that make it very difficult that have nothing to do with the merits of the approach itself.

It is up to us, as developers to take the charge and push for these techniques through open source development, advocacy, and training.

But to claim these techniques are a failure simply because startups aren't using them is pretty ridiculous.

Higher assurance from the start requires something functionally similar to Ada's Spark.

I've never seen that used in the wild (though I'm in the wrong domain (web) these days).

>>Writing software is not math.

> You're wrong, and I've explained this upthread.

I suspect there is a difference in semantics, here. Software is inherently mathematical, yes. But the practice of writing software is not the practice of doing math.

The output of doing math is proofs. The output of writing software is...something that does something when run on a computer, hopefully interesting, meaningful, useful, or entertaining. In the vast majority of cases, we have not and will not need formal proofs of correctness for software to achieve these things.

If I want a blur effect on some portion of a UI, and choose to implement that with a Gaussian blur, what value is there in formally proving that a specifically Gaussian blur has been applied? All of this is inherently mathematical, but that doesn't imply a need for mathematical proof.

I agree. It's kind of a focus thing. When I'm writing code, I do it because I want stuff to happen - in real life, in our physical reality. Any concept of code-as-a-proof is not even on my radar, unless I'd be writing life-critical software for NASA or a hospital, or something.

Here I also thing that 'Turing_Machine is both wrong in details and correct in the general point with their recipe example:

> Examining the measurements, timing, and the production chain doesn't tell you anything about whether the recipe is delicious or inedible.

You could, in principle, apply the knowledge of medicine, chemistry and biology, coupled with process engineering and wide-scale people studies, to construct a theory of tasty foods, which could lead to the situation in which you could evaluate any recipe on a theoretical basis. But getting to that state would require tons of up-front work to be done (some of which is being done for unrelated reasons, so maybe in the future a "food theory" will assemble itself) - and in the meantime, getting a piece of tasty food is done much faster and cheaper by finding the solution instead of deriving it. This search is done through iteration.

Similarly, in software, 99% of the time we find a solution, not derive it from first principles - because the former is much cheaper when we care about the solution, and not solving the entire general class of a problem at the same time.

The same is true for math. It is the same thing, because of the Curry-Howard isomorphism.

The reason for all the confusion is that programmers are already doing math. They just don't realize it and reinvent the wheels invented by the math community in the past century. It's a matter of semiotics.

Curry-Howard isomorphism does not mean the same practices that are performed in mathematics research must be applied to writing software.

Some aspects of language design are reinventing wheels invented by the math community. This is far from constituting the set of "writing software" or "software engineering".

Nah, I still think it's about different goals.

But assuming you're right, I'd like to know - what mathematical wheels am I reinventing in my dayjob of building UIs that let people click up some stuff that later gets put in business-specific XMLs?

Math, at least applied math, is not the goal, but the method. Programming neither is the goal, it is the method. Understanding that both are language to express the path is of the essence.

The XML as a vessel of human-knowledge is limited. Good intentions have brought it OWL/RDF, XML Schema, XSLT; examples where others before us have tried to extend the XML into the domain of semantics and algorithms. Nevertheless, it was found that, without an expressive type system, large and complex business domains cannot be modeled. Apparently, in order to model abstract business domains, we need a language that composes both high- and low-level with near invisible seams.

So, that click-your-XML-application might benefit from a reflective logic, enabling the user to explore the possible state-spaces. If your app uses relational algebra from DBMSs, it might be able to combine the relational algebra with the algebra defined by your schema's. The UI state-space and the XML schema might be an isomorphism, which helps prove completeness of your UI-builder implementation.

Above all, the mathematical way of thinking helps reasoning, communication and correctness. It might not be the only way or perhaps the way is dated. Nevertheless, ignoring math as a programmer, feels like ignoring music theory as a musician or linear algebra as a structural engineer.

We haven't been arguing that programming can't benefit from math.

> ignoring math as a programmer, feels like ignoring music theory as a musician or linear algebra as a structural engineer.

We're not ignoring math.

You're defining relationships between types through functions.

The Curry-Howard correspondence says that a program is the same as a proof. A proof of what, though? Not that the program does what it's supposed to. No matter how far you go with formal methods, what the program is supposed to do is always informally specified. (There may be a formal specification. That specification wasn't handed down from on high at Mount Sinai, though. It's a formalization of the informal, badly-stated, half-unconscious informal specification that is the impetus for creating the program. Does the formal spec match the informal one? Can you prove it? No, you can't - certainly not formally.

It's like you read the article, and set about disproving it, without ever really understanding it.

> You're wrong, and I've explained this upthread.

No. I'm not.

Are formal math and engineering useful in cooking food? Yes, they can be (particularly if executing on an industrial scale). Are they necessary? Not really. Plenty of great cooks just throw in ingredients in the amounts that seem right to them, perhaps tasting the result once in a while. Are they sufficient? Nope. If the best mathematician and best engineer in the world collaborated, the result might be edible or it might be an inedible mess.

If neither formal math and engineering are necessary nor sufficient to produce good cooking, we can safely conclude that cooking is not math or engineering.

> Static type systems are arguably a product of this, especially advanced ones like Haskell's.

Haskell is used by, to a first approximation, no one. Which was my point.

> Now you're just being anti-intellectual.

No, I'm not.

> The only question is what you choose to do about that: learn the math, or stay ignorant.

I was one math class away from getting a dual BS in math and CS in undergrad. Rather than stick around for another semester, I took the BSCS and went to grad school.

You can safely assume that I "learned the math", and that I am not "anti-intellectual".

The point here is that while, on the most fundamental level, the universe may indeed be made of math, that doesn't mean that treating everything with the math toolbox is the best way to proceed. Expecting that math methods will produce great software is a fundamentally goofy idea -- just as it would be to expect math to produce great poetry, painting, architecture, or anything else (and the same for engineering).

>If neither formal math and engineering are necessary nor sufficient to produce good cooking, we can safely conclude that cooking is not math or engineering.

Bingo. Good thing we're talking about programming, and not cooking.

I asked if you understood what you were saying because you can't really cook declaratively, recipes are inherently imperative. The comparison to programming thus only fits for imperative languages.

>Haskell is used by, to a first approximation, no one. Which was my point.

If that's your point, then I agree. Not sure how that's in disagreement with my points though.

>No, I'm not.

So what then were you intending to convey by vague references to incomprehensible academia? Surely you weren't meaning to imply they're just wrong, were you?

>The point here is that while, on the most fundamental level, the universe may indeed be made of math, that doesn't mean that treating everything with the math toolbox is the best way to proceed.

Yes, but such a general claim is not what I'm arguing for.

>Expecting that math methods will produce great software is a fundamentally goofy idea -- just as it would be to expect math to produce great poetry, painting, architecture, or anything else (and the same for engineering).

Well, it of course depends on what you mean by "great" software. But I still think you're missing the point here. Computer science is a lot closer to math than poetry, painting, and architecture are. There is a direct, elegant, simple, formal correspondence between programs and proofs. The same cannot be said for those other disciplines.

My only claim is that proofs are slightly more solid intellectually and formally speaking than programs, so converting more programs into proofs will make easier to reason about, and since programs can be easily converted into proofs (relative to poems or architecture or paintings or whatever) that this is probably a good idea. I still don't understand what your objection to that claim is.

> The comparison to programming thus only fits for imperative languages.

I am not comparing recipes directly to programming. I used recipes as an example of something that has mathy and engineery facets, but that is not engineering or math.

> So what then were you intending to convey by vague references to incomprehensible academia?

I wasn't making "vague references" to anything, nor did I say that academic languages were "incomprehensible". I did say they were bizarre, which is a different thing entirely.

I'm not sure why you find it hard to believe that someone could understand academic languages of the sort you evidently prefer, and yet somehow still choose not to use them. Your attitude seems to be that anyone who doesn't use your preferred methods is "anti-intellectual", "ignorant", or any of the various other personal insults you've used.

Why not just go off and write some awesome software using your methods? If they work as well as you claim, you'll have some hard evidence to back up your assertions

>There is a direct, elegant, simple, formal correspondence between programs and proofs."

You are defining great software as "software that can be proved to behave in accordance with some formal spec", while people who actually use software (i.e., the people who pay the bills) define great software as software that performs the task they need to have done, can be written economically, and that is easy to use.

By your definition, a great recipe would be one that came out exactly the same every time, even if it tasted like shite, or took three weeks to make, or...

>>Haskell is used by, to a first approximation, no one. Which was my point.

> If that's your point, then I agree.

You are agreeing to something that is false. See my reply to the grandparent.

> Haskell is used by, to a first approximation, no one. Which was my point.

Unless you have a very loose definition of"no one" that simply is not true.

Just off the top of my head:

Haxl at Facebook Bond at Microsoft Supply chain management at Target

Also see:

https://wiki.haskell.org/Haskell_in_industry

>Unless you have a very loose definition of"no one" that simply is not true.

What part of "to a first approximation" was unclear?

https://www.tiobe.com/tiobe-index/

Haskell is in 47th place, which is consistent with where it ranks in every other popularity list I've ever seen.

I'm standing behind "to a first approximation, nobody".

Note that I'm not saying that Haskell is a bad language, or that Haskell programmers are bad people or anything like it.

I'm saying that the vast majority of programmers do not use Haskell. An anecdote about a particular group that uses Haskell (or even several groups) does nothing to refute that fact.

Surely you can see the part about recipes was an analogy to make a point and not directly equating two?

I think you're dismissing the post without engaging its arguments, so it hardly seems fair to start calling people naive, anti-intellectual, and ignorant. (btw, we all get that these are different ways of calling someone stupid, which is never productive and isn't justified in this case.)

To attempt to engage your argument, as far as I understand it... i think type systems and programming paragidms, however formal, can at best solve problems only in a corner of the problem set of software development. The limitation is because these do not take into account various kinds of constraints on software systems which nevertheless exist and are often the dominant constraints, depending on the project... Requirements, maintainability, usability, estimation, etc -- most of the stuff above the red line from the article.

What is there to prove in most cases though? I spend half my time redefining requirements.

I like Idris, and there's room for these languages. I think you give them too much credit though, programs written in them still have bugs. Your spec can be wrong. But above all else, they can't help you with scale, performance, recovering from hardware faults, and delivering what users wants.

The languages are still new, they'll gain traction, and for certain use cases they'll make sense, for others they won't.

The reason to use formal systems is to be able to reason about larger, more complex systems. Our brain is rather limited and to empower ourselves, we've found the divide and conquer approach. For that to work, we need assurances that our composition is correct due to the subcomponents being correct (and the composition operator). This is something we do all the time. You assume your compiler is correct, or your common libraries. However, if we want to grow larger systems, our foundations become more critical and we need stronger assurances.

I don't consider myself anti-intellectual, and I wrote a blog post on my claim that computer science is not math: http://www.scott-a-s.com/cs-is-not-math/ We discussed it a few years ago: https://news.ycombinator.com/item?id=3928276

well that pretty much nailed it.

I havent thought of this before but i was a mathematician that does software engineering, and Im starting to see some stark similarities between a mathematical proof and a "test" as in a unit test. I imagine if you went down this road you would end up with something very similar if not identical to TDD. What i was hoping this thread would discuss is how to turn software design patterns like the adaptor or factory patterns into a science in the same way that differential topology turns differential equations from a haphazard collection of methods into a rigorous science. I dont know why more people havent focused on formulating this more practical side of software engineering. Why is it that SOLID works so well, etc

Dijkstra spent a lot of his research effort on ways to prove that programs are correct.

"Today a usual technique is to make a program and then to test it. But: program testing can be a very effective way to show the presence of bugs, but it is hopelessly inadequate for showing their absence. The only effective way to raise the confidence level of a program significantly is to give a convincing proof of its correctness."

https://www.cs.utexas.edu/users/EWD/ewd03xx/EWD340.PDF

There is great wisdom in that observation, but I also enjoyed Knuth's take on the matter:

"Beware of bugs in the above code; I have only proved it correct, not tried it."

http://www-cs-faculty.stanford.edu/~knuth/faq.html

"I don't need to waste my time with a computer just because I am a computer scientist." - Dijkstra

This basically describes the dichotomy between CS and software engineering.

Yes, this is of extreme interest to me as well. The why behind SOLID. I think you could formulate more rigorous support based upon information and graph theory, maybe neuroscience, and other areas I'm less familiar with.

For example, the Single Responsibility Principle (SRP) is primarily concerned with making software more manageable on both an individual and team basis. How? By minimizing:

1. Communication overhead between teams/modules

2. Information overload in an individual

You could look at #1 from a graph-theoretic and information basis. I'm sure there are many interesting things to prove there. Like Amdahl's and the opposite of Metcalfe's Law [1][2] applied to team/communication/module dependencies. Just as a basic example, if one class has 10 responsibilities shared by 10 engineers with no boundaries specified, then the probability of conflict and unintended consequences rises. Thus the rate of development slows.

As for #2, applying more rigor and proof to the question of how these principles help a human understand quicker.

I don't have the necessary background right now to explore this in more detail, but like you, I'm very interested in any possible formulations.

[1]: https://en.wikipedia.org/wiki/Amdahl%27s_law

[2]: https://en.wikipedia.org/wiki/Metcalfe%27s_law

The problem is that even things like "how many people touch this class" and "how many external teams do we work with" aren't simple at all. Some external teams are much easier to work with than others. Sometimes you want your whole team to intimately understand an area of your code. Making software is an intensely human process, which is why managing software teams is almost entirely about considering the people on your team, and what makes each of them different.

Tests are negative proofs; you can show that a specific invocation doesn't fail. But unless they are exhaustive over the input space, they are never positive. You can't say something works universally.

I am not a full subscriber to SOLID. I think it promotes a certain kind of degenerate over-abstraction that leads to bugs of a different nature, premature decisions on what needs future substitution, and decreases agility in the medium term.

> I think it's self-evident that there is no theoretical basis for software development in the way that would satisfy your criteria. Software dev is generally a scattershot haphazard endeavor that involves trying dozens of angles until one of them works.

But the actual practice of doing mathematics (i.e. coming up with novel proofs) works exactly like this as well. The differences are in how much confidence we have in the results, and how much we're able to reuse them.

> It's also self-evident that in most situations, correctness and reliability aren't a concern. The counterexamples account for maybe 1% of the field. 99% of the time, if your program breaks, you can pay someone to go fix it and no serious harm was done. Even Github outages, which affect almost all of us, hardly matter.

I agree that we collectively don't currently care as much about correctness as we pretend we do. I believe software correctness is becoming more important (e.g. the rise of ransomware) and is going to become much much more important, but that's due to what I accept is a non-mainstream view of the future.

Not really familiar with RTOS/embedded/security/military/medical software then, are we.

If those examples are 1% of software, they take disproportionately more funding than 1%.

And I'm sure customers of software, from personal computers, to business apps, to corporate websites would appreciate more consistent results as well. Reckless software engineering has damaged the reputation of the field as a whole.

> scattershot haphazard endeavor that involves trying dozens of angles until one of them works

Sounds a lot like engineering/design/art. There's a large amount of overlap between the three.

I had the pleasure of speaking to the principal electrical engineer whose firm was responsible for designing the entire electrical system for One World Trade Center in Manhattan and the Citi field as well.

He described his work a lot like a software developer would describe their own. And then, in his words, when his company was done they "passed the plans over to the electricians to build it".

It just so happens, in our profession, we've automated the part that electricians are responsible for in his project. Our electricians are called compilers. They dutifully carry out the plan and from time to time they surface warnings/errors back to the engineer for input/correction.

People conflate the meaning of software development because one person shares so many different responsibilities, that are usually handled by separate people in other professions: architecture, design, analysis, implementation, maintenance, etc.

What a civil/electrical/mechanical engineer does isn't so different from what a software engineer does. It's a "scattershot haphazard endeavor that involves trying dozens of angles [based upon guiding principles] until one of them works" usually run through loads of simulation and analysis. Now, the difference is, when these engineers want to bring their idea into the world it takes physical labor, unlike software development where the feedback loop is near instantaneous. We bring our programs into the world with compilers and can run them immediately.

I mean, there are plenty of examples where civil/electrical/mechanical engineers failed in their design and thus created a bug in their project. See [1] or any contemporary CPU from AMD/Intel or automobile recalls or spacecraft failures, etc.

There are certain principles of software engineering that lead to more effective software. That's a fact. And the companies that understand this fact will not fail to startups, in fact they exhibit a severe technological advantage.

Google and Facebook are two companies that understand software engineering. Talk to the YouTube/Instagram teams and see whether they felt better off -- technologically -- before or after acquisition.

[1]: https://en.wikipedia.org/wiki/Citigroup_Center#Engineering_c...

Agreed. Reading [1] was a fantastic eye-opener for me. The code is the design, and design is always "trying until it works".

[1] http://www.developerdotstar.com/mag/articles/reeves_design.h...

That was a great read, thanks for that. Indeed that article really codifies a lot of the thoughts that have been floating around in my head.

>I think it's self-evident that there is no theoretical basis for software development in the way that would satisfy your criteria.

I don't think this is self-evident whatsoever. One of the problems in software engineering is that we never know when a solution is "right," we only know when it's vaguely not-wrong, and even then almost everything we create is still subtly wrong in a way we forgot to think about. Math is solid because there is certainty in the correctness of certain proofs, and these can be used as building blocks for further results. Philosophically speaking this is the closest we're going to get to "real" engineering practice in software, and we're pretty dang far from it if you know what that looks like.

>Software dev is generally a scattershot haphazard endeavor that involves trying dozens of angles until one of them works.

But this is a symptom of any pre-scientific field in engineering, it's not specifically endemic to software engineering. The main difference is that in software engineering we're applying math directly, and in other engineering fields we're applying science. In a certain sense, the natural sciences are purely empirical (modulo advanced physics of course, which overlaps with pure math and philosophy these days) while math and consequently computer science are purely rational. So, what are the solid elements in math? Proofs. Proofs are also how you ensure that the field actually moves forward and you're not stuck recreating solid results that already exist. Sound familiar? It happens constantly in software, but imperative and poorly-typed languages inhibit composability and reuse because they lend themselves easily to extremely specific solutions to general problems.

>It's also self-evident that in most situations, correctness and reliability aren't a concern. The counterexamples account for maybe 1% of the field. 99% of the time, if your program breaks, you can pay someone to go fix it and no serious harm was done. Even Github outages, which affect almost all of us, hardly matter.

This is preposterous. Just because lives are not in danger does not mean that it's not worth doing right by the solution, and frankly I think a lot more lives are waiting to be put in danger by crappy software with bad security than you realize. It's already become almost dogma that all software engineers need to have a deep understanding of security, and I don't understand why correctness can't fall under that rubric as well. If we're going to be having Geohot or even Google or whoever building self-driving cars for possibly billions of people, enormous critical infrastructure projects coming under computer control, etc, the whole industry from education on up is going to have to have a serious attitude adjustment to keep up with the demands of safety, security, and reliability.

It might not matter 99% of the time, (I think it's a lot more than that of course) but we need to make sure that we can as a discipline deliver that 1% when it is absolutely critical, and as of right now it doesn't seem like we can.

FWIW, we agree on this point. But it seems worth treating this 1% case as a separate discipline rather than trying to lump it together with software dev. No one would claim that NASA's software engineering is the same type of work as, say, writing a new HN feature.

It's already become almost dogma that all software engineers need to have a deep understanding of security

The most secure programs are those that undergo frequent penetration tests and have bug bounty programs. Speaking as a pentester, I think there's not much chance of regular software devs being any good at security. There's just too much to know.

I want to agree with your other points, because in principle it's the correct thing. Unfortunately experience has taught us that the correct thing usually loses in the real world. Being first to market mattered way more for Ethereum than the fact that the DAO had a bug in their smart contract, for example. But there are hundreds or even thousands of examples of this type.

If we pretend that a teenager hacking in their bedroom is doing something fundamentally different than what most developers do each day at their jobs, then we lose out on the ability of that teenager to innovate. We become an exclusionary clique rather than an inclusive group. Luckily market forces still prevent us from becoming that insular, but in the era of walled gardens it's easy to imagine we're not too far off from that fate.

The main issue is that if we try to restrict the free market e.g. with legislation, then the important work will simply move overseas to areas without those restrictions. And unless you're proposing legal restrictions on the software dev trade, it's unclear how to enforce any of the proposals upthread.

>No one would claim that NASA's software engineering is the same type of work as, say, writing a new HN feature.

Well no, but the same underlying principles are still operating. The only difference is how much you care about heeding them. You don't need an aerospace engineering degree to make a paper airplane or a short bridge or a raft or whatever, but that doesn't mean that your knowledge of how to do so reliably and correctly wouldn't be improved by such a degree, or that if you're going to sell a product that you hope people will pay you for and subsequently depend on that you shouldn't bother trying to make it functional (in the "it works" sense) to the best of your abilities.

>If we pretend that a teenager hacking in their bedroom is doing something fundamentally different than what most developers do each day at their jobs, then we lose out on the ability of that teenager to innovate.

Ok, that teenager can hack, sure, just the same as they can build a two-stroke engine or an electronic alarm for their door or play around with nuclear fusion or whatever. But if they're going to sell those things and make claims about their safety and reliability, the validity of those claims should be enforced by an industry guild accreditation program or legal regulations or whatever. There's more than one way to skin this cat, but it really needs skinning.

>The main issue is that if we try to restrict the free market e.g. with legislation, then the important work will simply move overseas to areas without those restrictions.

The goalposts are being moved here, though, near as I can tell. I told you what I wanted done and why I thought it would work, and now you're telling me I have to figure out how to do it specifically in such a way that it can't be circumvented. I haven't thought up a specific solution to this question you pose, and as such I would point you in the direction of how liability works in other disciplines for similar cases and so on. I do actually think a lot of the same systems could work for enforcement, the biggest difficulty is actually figuring out what the principles should be. If the biggest problem with enforcement is that teenage hackers can't innovate anymore, I'm not really all that concerned. Romanticizing that image does nothing to change the hard realities of the industry.

> Well no, but the same underlying principles are still operating. The only difference is how much you care about heeding them. You don't need an aerospace engineering degree to make a paper airplane or a short bridge or a raft or whatever, but that doesn't mean that your knowledge of how to do so reliably and correctly wouldn't be improved by such a degree, or that if you're going to sell a product that you hope people will pay you for and subsequently depend on that you shouldn't bother trying to make it functional (in the "it works" sense) to the best of your abilities.

Not really. The time scales are completely different: that HN feature that is schedule a week of dev time is incomparable to that probe feature that is scheduled years of dev time even if the amount of code involved is the same. You could argue that both are "just programming", but the activities and process involved in both are going to be completely different.

>The time scales are completely different: that HN feature that is schedule a week of dev time is incomparable to that probe feature that is scheduled years of dev time even if the amount of code involved is the same.

You missed the point though. Whether it takes you five minutes to code the feature or fifty years, you're still doing math. The so-called "engineering" principles might change, with regards to division of labor and so on, but the underlying science/math you're dealing with doesn't significantly.

And this is the difference between math and engineering: in engineering you just have to be close enough to perfect that it doesn't break in the real world. It can never be absolutely perfect, because that would be either physically impossible or too expensive. This is true for mechanical, civil, chemical, and yes, software engineering.

In engineering the time it takes to implement the design/proof/code/output is one of the constraints. In math this constraint is ignored.

How are you "doing math"? Math might be involved in the feature, but many features just require lots of pattern matching and decision making. Maybe for some vaguely definite non-specific definition of meth that also encompasses most of human thinking this is true, but I fail to see how that is useful.

"If we pretend that a teenager hacking in their bedroom is doing something fundamentally different than what most developers do each day at their jobs, then we lose out on the ability of that teenager to innovate. "

That all contributors don't have the capability to formalize their output has never been a viable argument against formalization.

Before music education was formalized music was a mysterious craft you could only learn by learning with a master for a decade if you weren't incredibly talented.

Once the orphanages of Naples formalized music teaching in the 17th century it became something much easier to learn and teach.

Sound familiar?

Yet, music teaching did not eliminate the capability of non-formal craftmen to innovate. They just have collaborators to help formalize their thought process.(John Lennon did not know music theory and still made awesome stuff. But without formal theory his output could not live on in sheet music, and it would be a lot harder to reproduce it).

Even Einstein needed help with his math. But without math, theory of relativity would not have been much of anything.

It's all fine to imagine one is traveling in a traincar, but once one needs to compute, say, the orbit of mercury all need formal methods.

Creativity and formalism go hand in hand. You need both for a superpowered discipline.

> I think there's not much chance of regular software devs being any good at security. There's just too much to know.

I have over 30 years of experience and I couldn't agree more. The security field - heck, the website security field - is way too complex for me to navigate it properly. Sure, I know about SQL injection, but "authentication is not authorization" is something I tend to forget, and I am pretty sure I have no clue about at least half of OWASP top ten.

Looking at the discussion around your and Turing_Machine's points, I think one could generalize the problem like this: in a large and complicated search space, finding a solution is much faster and cheaper than trying to comprehend and formally describe the search space (to later derive the solutions). The up-front costs of doing the latter are so high (I don't think we even have a good bounds on them) that nobody who needs a solution bothers with it. Iterative search is the only way individuals and teams can feasibly find the solution they're looking for.

This way, I think formalizing software development is a worthwhile goal - just like formalizing cooking is - but it's also obviously so uneconomical that we can't expect the industry to bother with it. Formal methods are pretty much basic research - not useful for us in any meaningful timeframe, but hopefully our grandchildren will get some mind-blowingly amazing tools out of it.

> Software dev ... involves trying dozen angles until one of them works

It is a way to solve mathematical problems, See "Guess and Check" from this book https://en.m.wikipedia.org/wiki/How_to_Solve_It

> Software dev is generally a scattershot haphazard endeavor that involves trying dozens of angles until one of them works.

Maybe in an agile web startup. SW engineering in a big industry project is a very deliberate process. You start by a requirements engineer writing very precise requirements. Then a SW engineer turns this into a module design and a test specification. These are turned into source code (for which we use code generators to an ever higher degree) and test cases by yet other SW engineers. In the end everything gets reviewed and/or tested.

Trying things until they work is just not done. That would be way too dangerous for SW that controls cars, airplanes, nuclear power plants, rockets etc.

Safety critical software is a small subset of the software that gets written in "big industry" projects.

There are hugely more systems not written to that standard.

Yes, but those systems are engineered in the exact same processes. Just with less testing and fewer documents.

> Software dev is generally a scattershot haphazard endeavor that involves trying dozens of angles until one of them works.

So software engineering isn't engineering, either? I would imagine any civil engineer who actually knows what it takes to build a bridge would tend to agree, at least on the basis of the points you have put forward so far.

if you look at civil engineering at it's childhood stages that is, back when pre-historic man tried to build huts and lean-tos, you'd find that they too, didn't use any solid engineering practises, but simply tried different things and found out what worked. Being constrained physically makes it easier to determine what works, but the essense isn't any different to what software engineering is today.

I bet if we fast forward 1000 years, you'd find that software engineering will have become as rigorous as what we have today in civil engineering.

This. Someday software developers will look back on us the way doctors look back on barbers' bloodletting.

Now that we brought out the doctor analogy, I have news for you....doctors deal with an unknown system, gain personal and institutional experience through trial and error, are basically detectives, are rarely working with full information, and have, despite their heroic efforts, a significant task failure rate (the patient dies).

How is that not like software engineering?

i dont think doctors fail as often as software projects. and they only fail on the fringes of medicine - like treating cancer, or rare diseases. You don't often see doctors failing to treat the cold or a broken angle badly that they kill their patients!

But in the software world, it seems the equivalent of the cold is a CRUD app, but still fails so often that it's newsworthily talked about when such a software project succeed!

No, that's not equivalent. A doctor treats a cold the same in every case. Software engineers are building different systems for each case, or else they would just use existing software.

Part of that is because software development is usually concerned with optimizing things for their sale value, not for being useful. In my example, a lot of problems could easily be solved with the same CRUD stack, if not for the needs concerning the design (i.e. it can't look similar to that competitor's thing) and other goals unrelated to actual use of the product.

A doctor doesn't really treat a cold though. They can treat an infection with anti biotics, they can treat something more specific than a cold with something. But if you come in with just a typical cold and say "treat me," they'll give you a placebo and prescribe lots of rest and water.

> I bet if we fast forward 1000 years, you'd find that software engineering will have become as rigorous as what we have today in civil engineering.

This isn't evident at all. In software, every situation is novel, so there is no room for repeatable processes.

You can build a "bridge library" once and tweak it for each situation, but you never need to develop a rigorous process to build that library again.

> every situation is novel

this is the point i m contesting - that most situations aren't as novel as the stakeholders think it is. The failure happens because the assumption that it's novel is there!

In general there may not be that much novelty per project, but that isn't the novelty that one needs to worry about in software projects. The relevant novelty is the novelty to the project team. Also lot of the novelty comes not from the technical side, but domain and organization that will be using the software.

This is a big argument in favor of experienced devs, who have deep technical and domain expertise.

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