For those people, unless something fit within an existing (but large!) range of use cases, they were out of luck without having an engineer or mathematician figure it out for them. Suddenly, there is a glimmer on the horizon that all of that possibility the computer science people see every day could be unlocked for the users, and even if it only works 5% of the time, that is enough to get them excited in ways that are hard to describe to the computer science people.
Imagine going to school, a boot camp, or being self taught in everything about screwdrivers and screws. You can discuss at length the advantages and disadvantages of different shapes (Robertson bits > all), materials, screw threads, etc. You can custom design a screwdriver and screw for a specific application, taking into account all of the relevant constraints.
Now imagine the guy who needs to tighten a loose cabinet door.
Their relationships with the tools are entirely different. Screwdrivers don’t have nearly the complexity or ability to generate work leverage that computers do, moving even a few percent of those capabilities from the first group to the second is huge. It is, at minimum, Excel huge.
For the rest of the world, while some might be excited by what you describe (and it that works for them, that's great!), I believe in general the interpretation is far simpler: me like shiny.
Could you expand on this?
> Something that works 99 times out of 100 is 99% correct from the first perspective and 100% wrong from the second
Interesting. From a _manufacturing_ perspective, you can't achieve 100%, you can only get asymptotically closer to it with statistical process control. And of course there are limits to the perfectibility of humans.
This suggests that the big deployment of AI will be in areas where there is no clear boundary between right and wrong answer.
> Could you expand on this?
Not important, it's just a rhetorical flourish. In the second book of the Aeneid, Thymoetes is the guy who says (paraphrasing) "let's bring the horse inside" and Laocoon is the guy who says (literally) "beware of Greeks bearing gifts".
> This suggests that the big deployment of AI will be in areas where there is no clear boundary between right and wrong answer.
"AI" is an umbrella term at this point. If by AI we mean LLMs or similar technology, then my hunch is to agree with the statement. I don't think this is particularly controversial though, IIRC Yann LeCun said something similar.
Roughly, "I fear Greeks even when they come bearing gifts".
However, there is a pragmatic school of hacking, which says that results are all the matters. If you're in a startup, you should be pragmatic, and worse is better.
Nobody truly believes that CS is engineering.
What reasoning are you using to come to conclusion that software is not engineering?
>The creative application of scientific principles to design or develop structures, machines, apparatus, or manufacturing processes, or works utilizing them singly or in combination; or to construct or operate the same with full cognizance of their design; or to forecast their behavior under specific operating conditions; all as respects an intended function, economics of operation and safety to life and property
It is purely software engineering.
Whenever you have to qualify a noun with something else, the result is something narrower than the original noun, and often completely different:
- Software Engineering is not Engineering
- Street Justice is not Justice
- Covert Intelligence is not Intelligence
SE is way, way younger than other engs.
>to produce a physical thing
Why physical thing would be a requirement here?
>This is why an engineer sometimes has to say "no, that won't work".
But similar scenerios can occur in SE world too, so what does it even mean? like some unsound design of distributed system
The surprising thing to many of us is that the "software engineer" title has been specifically associated with deprofessionalization of the job and the view that is moving away from true engineering. See the Dijkstra link I posted elsewhere in this thread.
My parents were very respected traffic engineers. One was concerned with traffic inside cities, another with road design. One couldn't give less care about "nature of materials and physical force" while figuring out where to put traffic lights and close roads, while another had a set of standards (say a lorry's turning radius, sign sizes etc) which they've applied without thinking about costs or even producing a pysical thing. That was done by some other contractor in a sense anyway.
A friend of mine is an electrical engineer. He maintains electric motors and I guess he would fit your definition better. At the same time, how much an electrical engineer has in common with traffic engineer? Or say an air traffic engineer? Or a construction engineer? I would say what they mostly have in common is the "engineer" part as they are doing completely different jobs in completely different industries. I might even go further and say when someone calls "Alice is an engineer", it is just a shorthand for "Alice is a mechanical [or some other] engineer".
So those were the differences, but lets see the similarities. When a traffic engineer gets a project to see if they can increase the traffic flow from point A to B it usually follows the common pattern of finding out the current situation, figuring out a solution, testing/simulating it out and then making the project/solution on what should be done. Then when the solution gets implemented, some details can be re-adjusted etc. I did simplify it a bit, and I'm unsure in the exact english phrases, but I think you get my point. Software engineers that I know follow the exact same process. Oh, a database is overloaded, lets see what we can do about it. Can we give it more hardware? No, as thats too expensive? What about if we scale up/down the services/workers/instances/nodes/pods calling that database? Can we simulate that? What do the metrics say? Etc etc. You see where am going with this? In essence, there is no difference.
My point is, if you cannot call Software Engineering only by the word "Engineering", then you cannot call anything else (just) Engineering. You can dance around this whatever you like, and define Engineering either narrowly or widely enough not to include Software Engineering (just like you did), but at the end of the day this isn't a natural science like say Maths or Physics. You cannot say 2+2=5, but you can say Engineering is X. But then, lets be honest here, and I suspect this is the root cause of this: it's about exclusivity and status. Engineers, doctors, lawyers, electricians, plumbers and a myriad of different professions like having guilds (or similar organizations, speaking in general here), and like having artificial scaricity. This brings status, it brings money, it brings power and influence. It cannot work if everyone is allowed in. It's what's simply called gatekeeping. It's what hiding behind a dismissive, elitist sentence I've heard too many times: "Oh, but he's no engineer". So if we're honest here we can call a spade a spade.
Let's resort to definitions, with apologies.
Engineering
> Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and buildings.
-- Wikipedia[1]
That certainly doesn't make Software Engineers what are traditionally thought of as "engineers." So... on to Software Engineering:
Software Engineering
> Software engineering [is] the application of a systematic, disciplined, quantifiable approach to the development, operation and maintenance of software and the study of these approaches; that is, the application of engineering and computer science to software. [2]
That description does not fit what most of us do when we write or create software. Perhaps it should. We'd be better off in many cases. But programmers are often closer to gardeners than engineers in that we approach solving problems through empirical processes, testing and verifying as we go. TDD is an admission of the need to do just that. So is Scrum (empirical process control). There absolutely are cases where algorithm optimization using the latest research must be applied just so. There absolutely are cases where applying gradient descent and convolutional neural nets in specific fashions applies. Most of us are gardeners growing our systems, or carpenters building out a feature, though. Programmers. Software engineer makes it sound loftier, just like sanitation engineer makes trash collection sound loftier.
I will absolutely concede that I still use the "engineer" terminology on a day to day basis, my opinion on the internet notwithstanding. But it is a label that is weakly applied for fashion and connotation, rather than for its distinct meaning, and I suppose that is what I tilt at here on HN. Apologies for the pedantry.
[1] https://en.wikipedia.org/wiki/Engineering
[2] https://en.wikipedia.org/wiki/List_of_engineering_branches
I'm sure that say a conteporary civil engineer would scoff at calling Nikola Tesla an [electrical] engineer, just like you're virtually scoffing at calling a Software Engineer only by Engineer.
Admittedly that the software field is young, but does it make it "worth" less? To entertain your argument, do you consider a person programming PLCs an electic engineer? What's the fundamental difference between a software programmer and them? I don't see any. So you cannot call one an [Electrical] Engineer and another one "just" Software Programmer.
Gardener is not an engineer. On a ship there are usually at least two departments: Deck, and Engineering. The latter are people in charge to make sure that ship's systems are up and running at all times. There is no theory behind it, or pretty much any maths. It is mostly boring maintenance. And I would be surprised that anyone would call those people non-engineers. So why bring this up? Engineering definitely has a vague connotation with certain terms like electrical power, mechanics, devices, construction, materials etc. As the gardener or a trash collector doesn't deal with any of those, noone is considering a gardener an Engineer.
One can say, oh it's the title inflation, but that actually applies to any profession then. Or to put it differently, what makes a person an engineer? The work that person does, or the title it was given to them by some institution? Is it both? Is someone an engineer but is a career politician? I sure know one, and the guy will always be legally an engineer. This is a classic "what makes an art, Art?" question which is another can of worms I'm not going to open.
So I'm not sure what you're arguing then when all of this is on a very shaky ground. My position is that it is just a matter of a title and social convention. If you're a part of a engineering department, then I'm sure people outside of that department will call you an engineer. Inside of that department you might be a programmer of say a backend service, I could be a platforms guy, Alice could be QA engineer, and Bob could be a hardware engineer. It just doesn't really matter in the end. All of those are just social constructs which change with time. Or if we take it to a institution level: in some countries you have legally recognized Software Engineers (as I found out in other threads), in a country like mine you don't have one, whether we like it or not. So as I said in my previous post, this isn't maths or physics, and it is just a social construct which varies all over the world. So arguing about it is like arguing about the definition of art. I like spending time on engineering more so that's it from me ;)
However, there are some ideas clustered around that seem to have something to do with it. Engineering on a ship has to do with electrical and mechanical systems, and in a highly constrained set of outcomes, essentially reducible to a single bit at any point in time. (Either the systems are up and running right now, or they aren't.) Within this system of evaluation of outcomes, it's not surprising if the engineers in this context aren't using maths every day but are engaged mainly in more practical actions. However, you can be sure that they know a lot of safety tolerances and operational characteristics of various ship systems that would be characterized as mathematical, even if they are mostly operating well within tolerances that make these operations routine.
One reason why people argue about "software engineering" is that there are authors who define it specifically to include scientistic or bureaucratic rituals that have no mathematical underpinning, while excluding the difficult mathy bits of engineering. The further you get from actual engineering, the more common this definition gets.
EWD1165 "There is still a war going on.":
Urban development can be seen as a balance between careful planning (akin to the mathematics camp) and organic growth (resembling the engineering camp). A city designed with a focus on aesthetics and theoretical frameworks might be visually appealing, but it could lack adaptability. On the other hand, a city that grows organically may not be as cohesive, but it's more practical and responsive to its inhabitants' needs.
This parallel can help us better understand the emergent properties of LLMs, which arise from their complex interactions. By appreciating both the engineering and mathematics perspectives, we can gain a more comprehensive understanding of these properties.
Moreover, the balance between early adoption and risks, as seen in urban development, can also apply to LLMs. Early adopters of LLMs can tap into their potential, but they must also be aware of potential risks, such as biases and ethical concerns.
Oh yeah ChatGPT wrote this answer.
Math - the study of well defined concepts and their relationships. Solving problems with proofs.
Engineering - solving well characterized problems based on math and physics (which can include materials with known properties, chemistry, approximations, models, …), and well defined areas of composability (circuits, chemical processes, structural design, …)
Craft - solving incompletely characterized problems with math, physics, engineering and enormous amounts of experience, intuition, heuristics, wisdom, patterns, guesses, poorly understood third party modules, partial solutions pulled from random web sites …
Art - Solving subjective problems by any means necessary.
I recall a self taught dev (or maybe from a bootcamp) coming up with a cascade of nested if-else, nested 8 deep. Someone with a background in CS asked him what he was trying to do and basically concluded that what he was trying to do could be expressed as a state machine. To which the initial dev replied that it was "way too fancy" and that he didn't need the code to be fancy, just work.
The ugly part: The nested-8-deep solution was faster to market and costs less. And, it will be thrown away in 6 months during the "big rewrite after we scale". So the perfect-is-the-enemy-of-good state machine solution written by an expensive engineer has less value. Oompf.
What about maintainability? Extensibility and ease of debugging?
I've seen chunks of projects re-written, just because it was simply impossible to extend them without significant efforts!
Are they? Source readability will still matter if you end up using a debugger!
Eh, I think you’re overselling how precise and well defined engineering is in other fields. Engineering in other fields is just as much dealing with poorly characterised problems as it is when writing code (it takes quite a lot of characterisation to go from “we want a bridge here”, to an actual damn bridge, and that’s all an engineers work).
Really the core of engineering is just a very broad set of practices and principles that allows people to solve poorly characterised problems using maths, physics, enormous amounts of experience, intuition, heuristics, wisdom, patterns, educated guess etc in a reasonably consistent and repeatable manner. Doesn’t matter if you’re building a web browser, a motherboard, or a bridge. You don’t get a good result without a healthy dollop of wisdom, experience, educated guesses, and a handful of fuckups (which hopefully you notice before you let people use the thing).
Engineering in other disciplines is no less messy, haphazard, and experimental than it is in software. It just isn’t as publicly documented as it is software, probably because it’s hard to build an open source bridge.
Logic in digital circuits.
Algebra and calculus for analog circuits, most physical objects, properties and processes.
Differential equations for dynamical systems and dynamical behaviors.
Sure there is a lot of creativity in engineering, but there is usually a whole area of math known to be suitable for expressing solutions clearly, given the area of engineering.
Contrast with the utter lack of standard notation across software tools and implementations, for describing all the trade offs, gotchas, glue, historical drift & complexity, theories of memory, caching, user affordances, potential overflows, races, etc. that is implied by a program’s code.
Sometimes a language provides islands of engineered code, like message passing in Erlang, or memory management in Rust, or a precise mathematical library like BLAS.
But most aspects in most software programs are created ad hoc, or inherited from someone else’s rats nest of an implementation, and never formalized completely, if at all!
Any clarity in representation quickly leaves planet applied math.
Take it from someone who’s studied the maths you’ve described and applied it in a professional capacity. Just knowing the maths isn’t anywhere near enough. It’s like knowing how quick-sort works, interesting and useful, not even close to enough to actually build anything.
> Contrast with the utter lack of standard notation across software tools and implementations, for describing all the trade offs, gotchas, glue, historical drift & complexity, theories of memory, caching, user affordances, potential overflows, races, etc. that is implied by a program’s code.
The entire field of computer science is dedicated to developing and using this type of notation to describe and understand the basic principles that underpin every programming language, database and algorithm you’ve ever touched. The notation exists, you just don’t use it. In the same way an engineer in another field doesn’t bother doing structural analysis, or circuit analysis from first principles, they just grab a pre-finished tool and apply it to their problem. Normally by just passing the problem to a computer that does all the heavy number crunching, and checking the outputs make sense.
> But most aspects in most software programs are created ad hoc, or inherited from someone else’s rats nest of an implementation, and never formalized completely, if at all! > > Any clarity in representation quickly leaves planet applied math.
Again, I think you’re vastly overestimating the precision of other fields of engineering. There might be more rigour in design in some places, but only because “just making a thing and see if it works” is expensive, but other engineers absolutely spend huge amounts of time just making things to see if stuff works.
There’s a reason why “safety factors” are a thing, and reason why they’re usually 10x or greater. That safety factor is also the “we’re not sure how well this works, so we made it ten times stronger than we think we need, just in case, factor”. Engineering in other fields is people doing maths all day long, it’s mostly reading data sheets, assembling Lego brick components, and hoping to hell the manufacturer didn’t lie too much on their data sheet. Plus some design and simulation on a computer for good measure.
You wanna see “ad-hoc or inherited from someone else’s rats nest of an implementation” in a different field of engineering. Then go look at any electronics catalog, or lookup YouTube videos of people testing parts against the specsheet and discovering how wildly different they can sometimes be.
Dodgy, badly implemented, never formalised engineering exists everywhere. That’s why bridges collapse when they shouldn’t (Genoa Bridge), why planes crash when they shouldn’t (Boeing 737 Max), why cars emit more emissions than they should (VW), why buildings get emergency modifications after being built to prevent them from being blown over (601 Lexington Avenue). Software engineering does not have a monopoly on botches, last minute hacks, and dodgy workarounds. Engineers in other fields were merrily employing all of them to great effect for centuries before software turned up.
The division of labor into software developers and non software developers isn't any different than farmers vs non farmers or any other profession.
As a counterpoint: Look at the history of the libxcb: https://en.wikipedia.org/wiki/XCB
[Bart] Massey and others have worked to prove key portions of XCB formally correct using Z notation.
Mathy projects, formally driven: matrix multiply libraries, symbolic computation, constraint resolution, ...
Engineered projects, formally (or close to it) verifiable: 3D rendering pipeline, distributed database management, garbage collection process, ...
And craft. Which, based on the internet I have experienced, many apps unjustly inflicted upon me, and some memorable restarts between game saves, is most code.
Craft code necessarily involves amateur code, code which isn't economically worth engineering (when you can just throw unit tests at it. Or just wait for user reports!), code referencing weakly characterized libraries or interfaces, and code involving features that have become complex enough that the best reference model for its expected and unexpected behaviors is now itself.
Bzilion's Law of Coding Formalism Levels: "Any ambitious enough software project will descend into an exercise of pure desperate craft. Just before it becomes gambling."
[otherwise a (code) monkey could do it] is missing the point of programming.
I know managers who code (occasionally) who think similar. I thought so personally before I had actual prolonged experience with professional programming.
It is hard to express it concisely: why it is fundamentally wrong (category error: like thinking that perl regexes can be reduced to DFA--it is impossible in the general case even if DFAs can [sometimes even should] be used in many cases instead).
It is the same reason why waterfall programming fails most of the time. It is the same reason why generating code from UML diagrams produced by analysts is also a failure in the general case. It is the same reason why log normal distribution can be a good model for software estimation https://news.ycombinator.com/item?id=26393332
And no, you can't replace all programmers with a LLM prompt for the same reason (at least until [if ever] it reaches AGI and then humanity would have much bigger problems).
"agile" became a noun but if you look at the origins, you might get why "craft" may be applied to programming. Try "The Pragmatic Programmer" book.
Coding and software construction is engineering or craft, and is not Computer Science.
LLMs are neither. They are power tools for concept realization.
It's the difference between stone chisels and a suite of shop tools. We had pen and paper, or small steps up from those, and now we have LLMs.
So much of programming is rote boilerplate garbage simply linking things together and so little of it is actual creative thought. If LLMs could actually generate the rote boilerplate, programming would be soooo much better.
Alas, my optimism isn't that high.
Since its inception, computer science has had two "camps": those who believe CS is engineering, and those who believe CS is mathematics. The reason why we are seeing all of this fuss around LLMs is that they are a new front of this feud. This "extends" the usual debate on emerging technologies between Thymoetes and Laocoon.
Something that works 99 times out of 100 is 99% correct from the first perspective and 100% wrong from the second.
LLMs are therefore a step forward if you take the first view, a step back if you take the second.
If you accept this interpretation, an interesting consequence of it is that your outlook on LLMs is entirely dependent on what amounts to your aesthetic judgement.
And it's very hard not to have rather strong aesthetic judgements on what we do 40 hours a week.