Flamewars over platforms & upgrades are so bitter not because people are jerks but because the choice will influence entire ecosystems, benefiting one platform through network effects & avoiding “bitrot” while subtly sabotaging the rest through “bitcreep”.
2020-06-15–2020-07-09 finished certainty: likely importance: 3
The enduring phenomenon of ‘holy wars’ in computing, such as the bitterness around the prolonged Python 2 to Python 3 migration, are not due to mere pettiness or love of conflict, but because they are a coordination problem: dominant platforms enjoy strong network effects, such as reduced ‘bitrot’ as it is regularly used & maintained by many users, and can inflict a mirror-image ‘bitcreep’ on other platforms which gradually are neglected and begin to bitrot because of the dominant platform.
The outright negative effect of bitcreep mean that holdouts do not just cost early adopters the possible network effects, they also greatly reduce the value of a given thing, and may cause the early adopters to be actually worse off and more miserable on a daily basis. Given the extent to which holdouts have benefited from the community, holdout behavior is perceived as parasitic and immoral behavior by adopters, while holdouts in turn deny any moral obligation and resent the methods that adopters use to increase adoption (such as, in the absence of formal controls, informal ones like bullying).
This desperate need for there to be a victor, and the large technical benefits/
costs to those who choose the winning/ losing side, explain the (only apparently) disproportionate energy, venom, and intractability of holy wars.
Perhaps if we explicitly understand holy wars as coordination problems, we can avoid the worst excesses and tap into knowledge about the topic to better manage things like language migrations.
If there is a communication platform for nerds, whether it’s Usenet, FidoNet, forums, Twitter, Github, Hacker News, Reddit or what have you, there will surely be holy wars—those intractable perennial arguments over whether technology A or B sucks and why users of the other technology are not just simple-minded, but sociopathic, sinning against all that is good and pure. The recurrent ‘holy war’ phenomenon in computing is defined in the Jargon File as:
flame wars…The paper by Danny Cohen that popularized the terms big-endian and little-endian in connection with the LSB-first/
MSB-first controversy was entitled “On Holy Wars and a Plea for Peace”…Great holy wars of the past have included ITS vs.: Unix, Unix vs.: VMS, BSD Unix vs.: System V, C vs.: Pascal, C vs.: FORTRAN, etc. In the year 2003, popular favorites of the day are KDE vs.GNOME, vim vs.elvis, Linux vs. [Free|Net|Open]BSD. Hardy perennials include EMACS vs.: vi…The characteristic that distinguishes holy wars from normal technical disputes is that in a holy war most of the participants spend their time trying to pass off personal value choices and cultural attachments as objective technical evaluations. This happens precisely because in a true holy war, the actual substantive differences between the sides are relatively minor.
The silent dog: where holy wars are not. One can probably name further ones. For example, the great console wars of the 1990s were accompanied by equally endless and often acrimonious debates over the merits of the SNES vs the Sega Genesis (then the N64 vs the PS1, the PS2 vs XBox…). Or moving 2 decades ahead, cryptocurrencies such as Bitcoin vs Ethereum. We should also note what things aren’t holy wars: the exact choice of string search algorithm in a tool like grep, one’s choice of FPS vs RPG video game genre, how large a hard drive or how many CPU cores1 to buy… There may be the occasional debate over these, but they will tend to be level-headed and productive in a way holy wars aren’t. It’s not mere “brand loyalty” either—there are countless brands out there with cults of followers but no holy wars, and to the extent they are debated, most shrug and conclude De gustibus non est disputandum.
Choices matter. Are holy wars just nerds being nerds? To some extent, sure, arguing is often a recreational activity; but this can’t possibly be the whole explanation, because they descend into highly acrimonious flamewars that no one enjoys and from which everyone comes away embittered. And contra ESR, the technical differences are often quite substantial. (Even using his own examples, ITS vs Unix or C vs Pascal or Emacs vs vi, they embody dramatically different technical philosophies.) Armin Ronacher, complaining about the “emotional distress” used to encourage upgrades like Python 2→3 which appear to “under-deliver” direct benefits commensurate with all the Sturm und Drang, is perplexed by the whole matter, and can come up with no better explanation than holy wars coming from people enjoying “suffering together” & being “on the moral right side”, which are radically inadequate (why suffer in the first place?) and he does not enquire any further, but revealingly notes in passing that “very few projects actually are large enough that a fork by some third party would actually survive”.
Network effects. What’s the difference? The difference is that holy wars (much like political debates) are always about platforms with network effects, and the indirect second-order effects are much more important than the first-order changes. What OS or programming language or binary number encoding you use matters to other people. People flame over their favorite MMO, but not their favorite Solitaire; even two neighborhood kids arguing over video game consoles benefit if they can agree on which console is best, because then they can easily share games & save files & video game magazines.
In contrast, what you do with them matters a lot less. Once you have settled on Microsoft Excel rather than VisiCalc or Lotus-1-2-3 for doing your spreadsheets on, the contents of said spreadsheets don’t matter nearly as much to other people as the fact that you are an Excel user.
“Should array indices start at 0 or 1? My compromise of 0.5 was rejected without, I thought, proper consideration.”
Grow the network, even with dirty tricks. If I use Python 3 and can convince everyone else to use Python 3 rather than 2, regardless of how much the Python 3 improvements themselves actually matter to them or how dishonest my arguments are, I am much better off. The path of a programmer who uses the most common language is a blessed path: libraries abound, bugs programmers of lesser languages routinely encounter daily will mysteriously fail to occur in relatively bulletproof codebases, documentation always addresses his use-case with helpful snippets to copy-paste, APIs miraculously return data formatted in a way convenient for his default data structures, which their rich featureful IDE will tab-complete the code for them, Stack Overflow will overflow with tips & tricks for any glitches (which come almost as fun puzzles, bagatelles between the real work), for all is for the best in this best of all possible worlds… There is a large personal and collective investment in explicit & tacit knowledge (one must even learn to think differently for specific tools), but once the price is paid, life is good. While those who venture away from the beaten path quickly discover that how many of their own libraries they will have to write, how under-specified many standards are, how many assumptions their OS or API makes (the better to stab them in the back), how few signposts there are or fellows to ask advice, how quickly the yak shaving kills the beast by a thousand cuts (and the more diligent they are about filing bugs or patches, the deeper they are sucked into the mire), and in their darkest moments, their faith waver as they wonder if perhaps their favorite language is not the best programming language in the world.
Not just zero, but negative-sum. Those positive network effects are clear enough. But one could acknowledge them and think they are not adequate to drive the fervor of a holy war. So let’s consider a subtler problem, which is how the success of one platform indirectly harms other platforms by wresting away shared resources.
Always in motion. The phrase bitrot encapsulates the problem of network effects for such platforms. Programs do not bitrot because they changed on disk, or because the mere passage of time rendered them buggy (with occasional exceptions like Y2K). Bitrot happens when the rest of the world changes around the program. APIs change a field name; or the name remains the same but the meaning changes; or an obscure function is broken by a change somewhere else and no one noticed it until your program tried to use it as always and it broke; or a version number changed and something else will no longer work because it assumed the old version number and is unsure if the new one is safe; or you need a particular program which can’t be installed without upgrading existing programs (thereby potentially breaking thousands of others); or a system backup uses keys which quietly expired or ran out of space or was never updated to backup a new server as well. The implicitness of dependencies and system interactions means that there is no way to avoid taking ‘the path of least resistance’ because one does not realize there is even a path or that one is being locked into anything. (“What do you mean, ‘a byte isn’t always 8 bits’‽”) Bitrot must be actively fought: if you are serious about not building in too many dependencies, you need tricks like chaos engineering, or deliberately crashing services which exceed their expected reliability.
No silver bullet. Technical fixes like type systems can help reduce bitrot by identifying precisely where things have changed dangerously, but there is always a system outside the type system, and the only truly end-to-end test is the end-user.3
What gets used, works. What doesn’t… There is no cheap way to avoid bitrot: what gets used gets maintained. Programs which are in wide use avoid bitrot less because of any intrinsically superior design but because of the ecosystem around them: because breaking changes are immediately detected by a cutting-edge user (sparing all the others), or the breaking changes are never made in the first place (because they tested & detected it, or were well-aware of the consequences, or simply because it broke their own system first!), and because everyone adapts their things to fit the popular program rather than vice versa. Thus constantly refreshed and updated, the program+ecosystem avoids bitrot—like living flesh, which avoids rotting (decomposition by bacteria etc) by constant renewal.
“We all have strength enough to endure the misfortunes of others.”
François de La Rochefoucauld, Maxim #19, Reflections; or Sentences and Moral Maxims
Dying systems ‘bitrot’, growing ones ‘bitcreep’. The flip side of bitrot is what we might call bitcreep: because there is only so much time and energy to go around, a system which avoids bitrot will also experience ‘bitcreep’, where other programs begin to ‘bitrot’ in that they increasingly assume, depend, and are tested only with that system, and that gradually creeps through the ecosystem. In a system with heavy bitcreep, getting things done in any way other than the dominant way means thrashing around in what is not so much a ‘Turing tarpit’ as a La Brea tarpit, diverting new programs towards it. It becomes a black hole, bending space around it; once a program has built in enough implicit and explicit dependencies, it has passed the event horizon, and it can no longer escape (because it would be easier to rewrite the program from scratch). And because the alternatives are not being used, they are not getting maintained, which means that as bitcreep spreads, anyone interacting with older programs in a way that used to work will discover their program has suffered bitrot, without having changed at all; all past investments are jeopardized, rotting away invisibly. (This suggests there are two evolutionary strategies for systems: to be so simple that no one would replace them, and to be so complex no one could replace them.)
“Embrace, extend, extinguish.” An example might be how systemd has metastasized in Linux: a boot script alternative has become involved in everything from desktop environments to audio daemons; increasingly, the only way to do something is via systemd. Things which used to be compartmentalized and usable with alternative tools now assume the user uses only systemd and tailor their capabilities to systemd. Increasingly, rooting out systemd ceases to be possible: it simply breaks too many things, even things which ostensibly have nothing to do with the original purpose of booting up Linux. Someone who discovers the hard way that a key script of theirs has been broken by systemd, through no fault of their own, and that systemd cannot be removed without bricking their system and the last OS version without systemd was many years ago and would break a dozen other programs and be extremely insecure, and who dislikes systemd for other reasons, could be forgiven for being upset. And for a partisan of systemd, it is not enough that systemd succeed—others must fail.
One man’s bitcreep is another man’s standardization. Bitrot/
Total war: best never to begin, but once begun—win! The consequence of the power of bitrot/
A bad compromise makes everyone unhappy. In the case of Python 2 vs Python 3, both are large communities, and could potentially go on indefinitely. The persistence of 2 Pythons is a perpetual headache for all Python programmers, as it does not just forfeit the benefits of scale (2 half-communities add up to less than 1 whole-community), but inflicts complexity and error on everyone dealing with Python, who must make sure they have multiple versions safely installed and always use the right one etc. And because of that, Python 2 will enjoy the benefits of being able to cause bitcreep in other systems, which must work around and cope with Python 2 (rather than vice versa). This is a passively-enjoyed subsidy, a ‘rent’, as it were, on the intellectual property built by past Python programmers (ironically, many of whom are behind Python 3). Why should the Python 2 users invest in learning all the new idiosyncrasies of Python 3? The users of Python 2 enjoy the benefits of a quiet life as their programs do not bitrot—but that comes at the steep triple cost of the opportunity cost of the Python 3 changes (so easy to forget in all this discussion of network effects), of bitcreep, and of dividing the community. And almost all of this triple cost is borne by others rather than the holdouts! (It would be hard to calculate, but considering the imbalance between library/
War, by other means. Given all this, it’s no wonder that arguments might become less than polite or some resort to bullying: the stakes can in fact be quite high, and even if not a matter of life & death, make a considerable difference to one’s quality of life. Still, such decentralized uncoordinated flamewars & bullying is a bad idea; if it worked, perhaps it could be justified, but the history of freelance flamewars shows that it almost never works and it is merely destructive. People should “be nice, at least until you can coordinate meanness”.
This explains why holy wars exist for some technical things but not others, why they persist, why they are often the most vicious between the most similar groups (it is not ‘narcissism’ but pragmatic because they are competing for the same scarce resources)8, why they are so intellectually dishonest and intractable, why participants feel forced to resort to bullying and emotional abuse, why they do in fact matter a lot, and how they tend.
This perspective also suggests some ways to reduce the damage.
Such coordination problems are not unique to computing. No one wants to be the first penguin off the iceberg—but those fish won’t catch themselves. Instead of ad hoc upgrades, and resorting to flamewars, propaganda, and bullying of people who have different needs or understandably simply do the selfish thing, could there be better ways?
Appeal to public-spiritedness. One better way would be to just raise awareness of the costs. Is an upgrade or alternative really necessary? If it really is, then holdouts like Armin Ronacher should be made aware of the costs they are creating in a reasoned manner, instead of making vague outraged noises at them.
Economic incentives? Given the need to do an upgrade, another option is to use economics approaches: create a fund to pay maintainers to do the transition, or sponsor a fork if need be (which can be returned to the original maintainers once the transition is a fait accompli and the status quo now creates bitcreep in the other direction). An assurance contract might be a useful social technology here (paying maintainers for their upgrade costs is smaller than the total gains and so is Kaldor-Hicks efficient), or perhaps simply a public commitment to do the transition at a specific date, similar to Python 2 being EOLed.
Deliberately centralize to solve coordination problems. From the perspective of bitcreep, attempts at making peace by bending over backwards to improve modularization and try to support multiple ecosystems in parallel are nothing but self-sabotaging folly: finding a ‘commanding height’ to do the transition may be the single most effective strategy, and it self-executes by default. (Such a strategy may seem underhanded, but in coordination problems, kindness is cruelty.) Indeed, perhaps we should reconceive the real role of a “BDFL” or maintainer as not being ordinary everyday project maintenance or organizing, but simply serving as a final authority to force the community into a new better equilibrium—a role the more valuable the more rarely exercised.
As opposed to which CPU brand or architecture.↩︎
As quoted in Expert C Programming: Deep C Secrets, Peter Van der Linden 1994; while this is the earliest I found, Van der Linden says he does not know where it came from, suggesting it was already folklore by 1994. (It is not in Kelly-Bootle’s The Devil’s DP Dictionary or The Computer Contradictionary.)↩︎
A corollary here is that a system which is also created end-to-end, like a deep learning system, may be able to reduce bitrot. In “Software 2.0”, conventional code like Tensorflow (itself notoriously bitrot prone) is minimized as much as possible in favor of learning all functionality. Consider a NN like GPT-3 when used for code completion or spreadsheets: even if the text formatting changes, which would immediately bitrot a conventional software system reliant on brittle regexps or parsers, they can be given examples to do few-shot learning (“prompt programming”) & smoothly adapt on the fly to “do what I mean”, and can retrain on future data without human intervention. As the ultimate input/
output pairs change, it can retrain itself end-to-end.↩︎
One might ask why software ecosystems don’t evolve steadily towards higher quality. A major reason that software (and corporations) do not evolve seems to be that, as Alan Kay puts it, “computing is pop culture”. Whatever progress and experience slowly accrete over time is swamped by random exogenous events. For programming languages in particular, it is better to be lucky than good.
It’s just Price’s equation. The lower the covariance between fitness and replicated phenotype, the less selection is possible. Shifting environments, poor replication of ‘culture’ & programmers, business models and ecosystems creating far higher fitness differentials than minor choices of language or library… then combine this with breathtakingly high ‘mutational targets’ (“this year, we are Agile!”)… Progress is slow, and every so often something like the PC or web browser or smartphone comes along, and everything must start over.↩︎
vim users are now natural allies of Emacs users simply because they both are threatened by creeping monolithic IDEs rendering it impossible for third-party editors to effectively integrate with compilers etc, and if Emacs can still interoperate with something successfully, then so too can vim (see eg the Language Server Protocol).↩︎
Early-adopters & computing pioneers are our bridge to the future—because we knife them in the back by taking their work without giving, and then step across the muddy ditch on their bodies.↩︎
Eg a Scheme Lisp programmer vs a Common Lisp programmer: if one Lisp programmer decides to change his preferred language, he’s probably not going to switch to Java!↩︎