Hacker News Reader

Comment by pron | Hacker News Reader

> with the first style, productivity is constant at best—getting things together in the first place is a struggle, and then adding features or fixing bugs continues to be a struggle. On the other hand, the second style of project is even more of a struggle at first, but once it works it's like magic: new features are easier to add than you'd expect, and I've had way more things work after my first attempt than anyone has a right to expect.

I would like to challenge that by pointing out that not a single piece of large software (except maybe a compiler or two) has ever been written using the skills/concepts of the higher levels of this chart. What you say may be true if generalized to better upfront design etc., but there's also no evidence that this is better done using the approaches discussed. It's not even about measuring productivity; it's about arguing over the properties of an empty set. When it comes to small (<100KLOC) and non-large (<1MLOC) programs, then the difficulties are not that hard to begin with, and depend mostly on the essential complexity of the problem, rather than abstraction/code organization etc..

> it's because I'm willing to put effort up front for a long-term reward.

You're equating upfront effort with a particular choice of technique, and one that has never been put to the test.

View on HN

Again, I answered this for you last week. Both Standard Chartered Bank and Barclays have many millions of lines of very successful production Haskell code. Both codebases are solving complex problems not solved at other banks and both make extensive use of types and purity. We do not regard pure functional programming as "aesthetics".

You are not addressing my point at all, and millions of lines of code (that include a Haskell compiler) do not necessarily make a large software system. If you are building software that is significantly more complex than could be achieved by other, simpler means, or you're building comparable large software systems for significantly cheaper, you'd only do Haskell and the world a great service by collecting and publishing relevant data. Without it, I have no idea how big your systems are, how complex they are compared to other projects, and how costly they are to build and maintain. I have no doubt you're happy with Haskell, but there are plenty of far more mainstream languages that people are happy with. Without any data, we can't make any comparison, so claims of superiority are nothing more than just claims. I find it puzzling that you don't see my reaction as a reasonable one for a marketing campaign that has been going on for nearly two decades, that has so far produced no evidence and negligible adoption. I truly and honestly want to be convinced. I am familiar with the theory of FP (up to about monad transformers, but not profunctor optics) and have programmed in SML. I just don't see any signs whatsoever that adopting Haskell can improve the bottom line significantly enough to be worth the cost and the risk, so the most logical thing to do is to wait and beg people for data.

You said:

"I would like to challenge that by pointing out that not a single piece of large software ... has ever been written using the skills/concepts of the higher levels of this chart."

To which I gave two counterexamples (today and on other occasions). All software systems should be modular to some degree, so I am not clear exactly what your criteria for a large software system is. In both my examples, the Haskell codebases are monolithic repositories where everything is typed-checked and built together.

You keep asking for quantitative data for a comparison with other languages. But my answer is the same as last week. It's good people that make software efficiently and cheaply. Give engineers PHP and they'll still manage to build something good. Haskell is just a tool, but it's a tool that increasingly good people are asking to use. The system at Barclays and Standard Chartered were built and are currently maintained very cheaply because good people were hired. Haskell just happened to be their preferred tool.

> I am not clear exactly what your criteria for a large software system is.

Let a "software system" mean any assembly of processes that communicate to provide some shared functionality, with the components being coupled to one another in some non-trivial way (i.e., there are correctness conditions that cross processes boundaries, so that changes to one program may necessitate changes in others). Excluding the compiler, how many lines of Haskell code do you have in your largest system (using my definition)?

You just described the entire bank! I prefer my single codebase/single build definition. I forget the current figure, but StanChart has at least 3M lines of (dense) Haskell. More details here: https://skillsmatter.com/skillscasts/9098-haskell-in-the-lar...

> I forget the current figure, but StanChart has at least 3M lines of (dense) Haskell

Oh, thank god, finally we get a number. It turns out that I was completely wrong, and that in its 20 years of hyped existence, someone has built something big with Haskell once. You may think I'm sneering, but only a little bit, because while one is almost nothing, it is much better than actually nothing because at least it is a first anecdote. Now, who do I have pester to get some more metrics?

> More details here:

Sadly, there are no more relevant details in that talk.

Just out of interest, are you skeptical of static type systems in general? Because AFAIK there has never been a quantitative study proving their effectiveness, only empirical studies.

There is a lot of evidence that "primitive" static type systems add value via enabling better tooling.

Low cost of adoption + clear minor tooling benefits is usually enough evidence to adopt Java/C# style static types.

Haskell style static typing has a very high cost of adoption and so must conclusively show a strong benefit in order to be adopted by industry.

At the moment I feel Haskell companies can get away with using Haskell because PL enthusiasts are willing to absorb the training costs.

I am not skeptical of type systems in general and TBH I've never worked on a large piece of software written in an untyped language (I often program in Clojure, but so far never a large system -- and yeah, I am skeptical about Clojure too even though I love it). But you're mistaken if you think I'm looking for quantitative studies; that's far too high a bar. I am looking for well-researched anecdotes, and there are plenty of them for type systems in general.

I am, however, very skeptical of the interpretation some people, especially in typed FP, give to types and the reasons they believe types provide a benefit. For example, the relationship between useful type systems and software correctness is not direct. I am currently using a formal verification tool that is completely logic based (and it has an interactive theorem prover, a model checker, and is backed by decades of careful mathematical analysis of its soundness) which is completely untyped, and yet it is as powerful as Coq for proving correctness of algorithms. If direct, formal, proofs of correctness is what you're after, types might not be the best solution. Types, however, have other clear benefits that are not related to formal correctness, or, at least, not correctness of global program properties.

>out that not a single piece of large software

What are you talking about? I know for a fact this is untrue. How do you continually justify making up things and passing them off as facts?

> I know for a fact this is untrue.

Why, because I missed a point of data in the ocean of hype and there is one? Two? Please, set the record straight, and provide us with some facts. Maybe in Haskell's 20 year history as the world's most hyped language there was one or two or maybe three non-compiler programs written in it that aren't very small. Maybe there is even one anecdote out there with some actual information in it, although I've looked for one -- a lot -- and couldn't find any. So right now, the people who are making stuff up and passing them off as fact are those who claim significant impact over and over and over without a shred of even the tiniest of anecdotal data. How is that justified?

I have absolutely no problem saying that Haskell works better for large interactive software than other languages, once there are a couple of anecdotes around, but the fact is that currently there aren't any (at least none that I could find). What we have at the moment is a lot of vague claims with zero metrics.

But perhaps I should explain the source of my skepticism. First, it stems from the almost unprecedented gap between hype and evidence. I would imagine that after so many years, given the grand claims there would at least be some good anecdotes. That there aren't any, inspires skepticism. Someone here likened Haskell's abstractions to load bearing materials as opposed to other language's mud. If that were true, the reasonable prediction would be to see Haskell skyscrapers towering over a sea of mud hats; that we actually observe the opposite, inspires skepticism. Second, it stems from my general skepticism (based on CS theory and 20 years of experience) towards the impact any language can make. I.e., I have not encountered a case where the choice of language was the determining factor. Haskell is perhaps the most notable example of a language that claims to make a significant difference by virtue of language-level features (as opposed to runtime features, like GC). I would very much like to see how big that contribution is, if it exists at all.

I'm not talking about Haskell, i'm talking about Scala written in a functional style where we've used a lot of the concepts from Haskell. We're using it at Verizon for extremely large projects and it's working quite well. I know you've been pointed that out by others, so when you say there's no anecdotal data, how can you justify that? I've talked to others who work at extremely large corporations finding success with it too in extremely large projects.

I am not looking for anecdotes that it is possible to write large programs in a pure functional style. I know it is possible. But, given the high cost of the approach (training, new libraries, maybe a new language and even a new platform) I am looking for anecdotes that the approach provides benefits that significantly outweigh its cost. I have not found any.

BTW, "extremely large projects" are anything above, say 20MLOC. What projects of that size have been written in pure functional style? What large projects (>5MLOC) have?

> not a single piece of large software (except maybe a compiler or two) has ever been written using the skills/concepts of the higher levels of this chart.

I wonder: to what extent this is because those higher level concept tend to shrink programs in the first place? I mean, big is bad, there's no debating this. Big programs can only arise from necessity or stupidity. And if those fancy features are any use, they must be reducing the need for big.

I would ask myself a slightly different question: what kind of program still have to be big, even if you have all these fine concepts at your disposal?

And of course, big is risky, and that tend to make us chose more conservative options. Why use Haskell where C++ has shown in the past it could do that kind of job? Not to mention the network effects: even if Haskell as a language was better than C++ as some specific job, you may still choose C++ because of libraries, commercial support, and developer availability.

> When it comes to small (<100KLOC) and non-large (<1MLOC) programs

Oh, so that's how you're calibrated… My, to me, small means <10KLOC. 100KLOC is already big, and 1MLOC is gigantic. Besides, I've seen a couple multi-million lines programs, and I don't believe for a second they had to exceed 100KLOC. Such programs are more about piling historical accident on top of historical accident than about encoding a complex problem domain.

A small compiler takes a couple thousand lines of code. With the proper tools, it can often be squeezed into 2KLOC (Source: the STEPS project from http://vpri.org). It won't optimize like GCC, but you rarely have to anyway. Now you have a DSL for writing an executable specification. What kind of specification is so complex that it cannot even fit in 50 books?

Of course you have to keenly understand the problem domain to pull that of, and that often means solving it the crappy way the first time around. Which means you're never going to rewrite it the proper way: it would be way too risky. So of course it has seldom been put to the test. One does not just hinge an entire business on original research.

> You're equating upfront effort with a particular choice of technique, and one that has never been put to the test.

No, not never. I have at least one example: one of my uncles once had to write a number of database transactions. It was one of his first job. He had 1 year to do it. Seeing how tedious it would be, he first though about the problem, then devised a DSL in which he could write the damn transactions. Since he wasn't exactly senior, and had crappy tools (he used B), the DSL took him about 6-7 months to perfect. (During which management were on the verge of panic, because no transaction has been done yet.)

At the 8 month mark, all transactions were done, tested, and had a surprisingly low bug count. The client was very pleased and the contract was renewed for another batch of transactions. Same size, but to be done in 8 months this time. That was given to a co-worker, who used the my uncle's DSL to perform 8 months worth of contracted work in 1 month.

DSLs sometimes work.

> to what extent this is because those higher level concept tend to shrink programs in the first place?

None at all. No one, AFAIK, even claims a reduction of even a single order of magnitude in code size.

> I would ask myself a slightly different question: what kind of program still have to be big, even if you have all these fine concepts at your disposal?

All those that are big now. I'm not talking about a single executable, but about an entire system (specification, development and debugging have always been done modularly, regardless of whether there's a single process or a distributed system). I see no way to implement the requirements of, say, an air-traffic control system, complex avionics or a banking system in software that isn't very big.

> 100KLOC is already big

A mid-sized enterprise software system is ~5MLOC. Google and Facebook have codebases that are measured in the hundreds of millions LOC. You can use whatever definitions, but if you look at software actually being constructed, much (if not most) of development effort in the industry is systems that are about ~5MLOC.

> What kind of specification is so complex that it cannot even fit in 50 books?

My guess? The majority of software written today is part of such specifications. I once worked on a medium-sized air-traffic control system designed for a relatively small area and number of planes, whose informal functional specification was ~10 books. The specifications for the avionics software of a fighter jet developed in the 80s were ~2000 pages of structured natural language (source: http://www.wisdom.weizmann.ac.il/~harel/papers/Statecharts.H...)

> No one, AFAIK, even claims a reduction of even a single order of magnitude in code size.

http://vpri.org claims about 3, though most of it is not because of the languages, but because of the removed redundancies. The languages do seem to be responsible for at least 1 order of magnitude.

About the rest, of what you say, I won't claim anything. It just make me feel… uneasy. Okay, those specs are that big. Do they have to, though? I've seen a big fat list of requirements in my last gig, and many were duplicated into 2 slightly different versions. As were some pieces of the code. And that's the obvious stuff. There were more subtle waste, where simpler alternatives would have fit the bill, but weren't applied because of historical reasons (I asked the architect, there was a reason for everything).

Almost everywhere I look, I see a wasteland of useless code, and even the specs aren't that clean to begin with. It feels like proper DRY alone would have reduced the size of this stuff by 2 or 3. Maybe I was unlucky enough to work in especially crappy environments. But from what I hear, that's the norm. So far, you're the only one I met that challenges that perception.

> The languages do seem to be responsible for at least 1 order of magnitude.

Compared to what? C? I'm not talking about C, but about any modern language.

> Do they have to, though?

Yes. Or, at least, everybody (including me when I first saw them) says "this cannot possibly be this complicated", and after understanding them, everybody says, "oh, OK". But let me put it another way: if the modern world really only requires simple software, then our work is nearly done. Some would use Python, some would use Java, some would use Haskell -- but if the largest software system needs to be ~100KLOC, then none of it matters too much. Writing such a piece of software isn't hard regardless of what language you use (or, rather, the difficulty is in the essential complexity; there's not much accidental complexity in 100KLOC). Even assuming one methodology would be 15% than another, it wouldn't make much difference to the bottom line because producing 100KLOC software is cheap anyway. And if that were the case, investing in programming languages would be even a bigger waste, as investing in simplifying specifications would have a much bigger impact, and would cost a lot less.

But just to get a sense, GHC -- which is a compiler, and, as you've noted, compilers tend to be small -- is about 400KLOCs of Haskell. The Linux kernel is over 15MLOC of C. Reduce that by an order of magnitude, you still get 1.5MLOC, and that's just for an OS kernel.

> So far, you're the only one I met that challenges that perception.

I don't argue that there isn't a lot of waste. I argue that even without all that waste, we'd still need software that's very large (or that, alternatively, waste is unavoidable). There are no signs that Haskell reduces this waste at all, or that it dramatically reduces the size of programs.

> Compared to what? C? I'm not talking about C, but about any modern language.

The domain they tackle is personal computing, which means Kernel, Windowing system, remote communication (web/mail), multimedia… So, yeah: mostly C and C++, by the look of currently popular programs.

That said, much of the (apparently) needlessly complex stuff I have seen was written in C++, and it did look like they didn't have the real-time requirements or resources constraints that would justify the use of such a monster of a language.

> Or, at least, everybody (including me when I first saw them) says "this cannot possibly be this complicated", and after understanding them, everybody says, "oh, OK".

I have yet to reach the second stage. And on one occasion, I did reach a reasonable understanding of the whole system. It definitely had to be very complex to match the specification, but the specifications themselves didn't match the end user's needs.

> (or that, alternatively, waste is unavoidable)

That's the alternative I'm most scared of. I cannot comprehend unavoidable waste, but I can't rule it out either.

Alternatively, I've came across the idea of not solving some problems¹, because the return on investment is just crap. Okay, when safety is involved, you probably cannot do that. Still, the idea that the 80/20 rule is sometimes more like 99.9/0.1 is enticing. Sometimes, full automation is not best. For instance last I checked, the best Chess player ever is a human-computer team, not a computer.

[1] Stop Over-Engineering https://www.youtube.com/watch?v=GRr4xeMn1uU

> I've came across the idea of not solving some problems

That, too, cannot be solved by a programming language :)

But much of complex software deals with things that could not possibly have been solved more efficiently (or even efficiently enough) by humans (like sensor fusion, package tracking, manufacturing control etc.). Also, we're pretty far from full automation. Nobody trusts computers to make the decisions in air-traffic control systems, power plant control software, or even in ERP systems.

The reason we keep building large software is that -- in spite of many problems -- they really do work (in the sense of achieving their goal of higher-throughput; whether or not a higher throughput of flights or of business deals is good or bad for humanity is an entirely separate question).

> if the largest software system needs to be ~100KLOC, then none of it matters too much. Writing such a piece of software isn't hard regardless of what language you use

I think this is absolutely the difference between you and proponents of Haskell. Personally I have found working on 100k LOC codebases very hard in Python and easy in Haskell.

I wouldn't know because I've never written anything in Python. How many 100KLOC non-compiler programs would say have been written in Haskell? It would be great if the team behind one of them would write a technical report so we'd at least slowly get to find out if it's actually easier to work with Haskell than with Python, and if so, by how much.

I agree that would be great. I can't help thinking that you're holding Haskell up to a standard to which you do not hold Rust, Go or Julia. Have you asked their proponents for technical reports on Hacker News threads?

It is Haskell that holds itself to a higher standard. Rust, Julia and Go don't make claims that are anywhere as extreme as Haskell's fans (e.g., see on this page the claim that Haskell's high abstractions -- optical profunctors or whatever -- are "load-bearing materials" to other languages' "mud". Rust has presented itself as a safe alternative to C/C++; Go presents itself as a high-performance language with simple concurency (or Java without the JVM); Julia presents itself as a high-performance alternative to Matlab, R or NumPy. But Haskell has sort of painted itself into a corner. Because the approach is so foreign and the learning-curve so steep -- i.e., the adoption cost is high -- if it didn't make outlandish claims (like, if it compiles it works) then no one in industry would consider using it. I don't need to know by how much Go lowers development costs because it makes no claims that it does, so I simply assume that it doesn't. That it is faster than Python, easy to learn in a day or two, and that it compiles down to a native executable -- are all trivial to verify. If you want, all of its claims are supported by plentiful data.

But other than that: yes! It is trivial to verify that Rust indeed fulfills its claims, but it is not trivial to verify that that's enough, namely, that overall, the overall cost of developing in Rust is lower than in C++, which is why I wouldn't switch from C++ to Rust without seeing that at least the costs are comparable. I'm also eagerly waiting for data about Rust's concurrency approach.

I would also tell you this: while I find the pure-functional aesthetically unattractive for interactive programs and am very much impressed by Clojure's and Erlang's approaches to state, and while I've personally written a semi-popular Clojure library, I have expressed skepticism about Clojure's suitability for large-scale projects. How well a language works in big software is something that you simply cannot extrapolate from experience in small projects, and as much as I like Clojure, I have serious doubts about its applicability, and I would not use it to write a large system without the kind of data I expect from Haskell.

But all those languages (Erlang and Clojure included) have social advantages that make this data much more easy to come by: they are used by people who aren't enamored with the language itself, who aren't PL enthusiasts, and are much more goal-oriented. Their judgment stems mostly from how well things work, not how interesting the language is. So articles with pertinent data (maybe not enough to risk a large project, but certainly more than those you find for Haskell) are more abundant.

So I don't need to beg for technical reports as much because 1. no wild claims that aren't supported by data are made, and 2. there's data out there (for Go, Erlang, Clojure) or it's coming (Rust).

I think the simplest solution to all of this is for you to ignore the outlandish claims, or at the very least pay attention only to the claims of senior and respectable Haskell propenents, such as Simons Peyton Jones and Marlow, Don Stewart, Lennart Augustsson, Neil Mitchell etc.. Otherwise you're simply allowing yourself to be gently trolled.

By the way "if it compiles it works" is supposed to be somewhat tongue in cheek, as is "avoid success at all costs".

That's not a solution because my problem isn't with Haskell itself (and I do familiarize myself with the theory when I find it interesting, and I'm well aware that most of the researchers aren't like that), but with the tendency of people in the industry to market things so enthusiastically, that they basically encourage suspension of critical thinking (and this is doubly annoying when what they evangelize isn't something as cheap as a new profiler, but something as expensive as a whole new language with a new, unproven, programming paradigm). Ignoring it wouldn't solve the problem. And in case you think this isn't an actual problem, consider that over-excitement about promises that couldn't be kept has caused at least two "research winters" in CS: one in AI and one in formal methods. The industry started believing its own hype, academia didn't mind the extra funding, but when the industry ended up disappointed, funding dried completely and research slowed to a crawl.

So you think you are singlehandedly saving "the" industry from the insidious promotion of Haskell?

Singlehandedly? Absolutely not. Why, am I the only Haskell skeptic you know? There are more on this page alone. There are even PLT researchers who warn against overselling results in PLT, and especially typed FP.

And we're not saving the industry; the industry as a whole isn't suicidal and will never bet too much money on unproven technologies. The industry isn't so fragile, but research is. Given the amount of money in the industry, even small parts that do bet on unproven tech can cause a funding surge followed by a research winter when the disappointment hits. We're saving Haskell.

If those who adopt Haskell do it with clear vision and not by believing some messianic claims, there would be no great disappointment and no research winter. Nothing is more dangerous to research than wild claims. You need to promise less and deliver more, not the other way around. And because the industry is competitive, it is actually quick to adopt ideas once they show actual significant benefit -- i.e., once they're ready. The industry adopted garbage collection almost overnight; it was almost 40 years after it had been invented, but almost immediately after it's been productized well enough to provide a significant advantage.

If pure-FP is really the way to go in general-purpose programming, eventually the industry will adopt it in some well-productized form. Getting there does require some early adopters, but they're already here and overselling doesn't help to get more good ones. It helps to get precisely those adopters who will end up causing a research winter.

----

What bothers me in terms of harm to the industry is the waste caused by people switching from one language to another, rewriting libraries over and over and thinning out the effort. I think we're losing years of progress. But there's really nothing I can do about that because even if I can convince someone that a language that is 1% "better" than another does not justify the effort of porting libraries over, there are already too many languages and platforms around, and there's always the question of, so which few languages should we pick, and why should it be the ones you like and not the ones I like. Haskell actually does not contribute much to this problem because its adoption rate doesn't yet make a dent.

Reply on news.ycombinator.com