Why a New Operating System?

François-René Rideau Dang-Vu Bân
<fare@tunes.org> 1

Abstract:

In this paper, we propose a reconstruction of the general architecture of an operating system. In a first part, we start from the very principles of cybernetics, and study the general nature, goals and means of operating systems. In a second part, we examine the crucial problem of the expressiveness of a computing system, conspicuously comprising both operating system and programming language. In a third and final part, we focus on particular services commonly found in operating systems, and criticize current designs at the light of the previous theory. All along, we sadly find that existing operating systems are deeply flawed, due to both historical and political reasons; happily, the advent of Free Software removes the obstructions to progress in this matter.

Table of Contents

1  Introduction

This paper aims at consistently demonstrating, out of sufficiently clear definitions, that while currently available computing system software provide a lot of expedient services, their low-level structure forbids them to provide useful services, which leads to huge, inefficient, slow, unusable, unportable, unmaintainable, unupgradeable, software. This paper tries to explain why the current design of "system software" is deeply and unrecoverably flawed, and proposes a new way for designing computing systems such as to achieve real utility. The proposed design method does not require but well-known, available, though sometimes unjustly deprecated, technologies.

2  Operating Systems and Utility

2.1  Utility

Between a good and a bad economist this constitutes the whole difference - the one takes account of the visible effect; the other takes account both of the effects which are seen, and also of those which it is necessary to foresee. Now this difference is enormous, for it almost always happens that when the immediate consequence is favourable, the ultimate consequences are fatal, and the converse. Hence it follows that the bad economist pursues a small present good, which will be followed by a great evil to come, while the true economist pursues a great good to come, - at the risk of a small present evil.

-- Frederic Bastiat, That Which is Seen, and That Which is Not Seen [2]
We herein call useful something that saves time, effort, money, strength, or anything valuable in the long run and for a lot of people. Utility is strictly opposed to Harmfulness, but we also oppose it to mere Expediency something being called expedient if it saves such valuable things, but most usually only in the short term, for special, personal, temporary purposes, and not (forcibly) for general, universal or permanent purposes.

Utility and Expediency are relative, not absolute concepts: how much you save depends on a reference, so you always compare the utility of two actions, even though one of the actions might be implicit. Utility of an isolated, unmodifiable, action is therefore meaningless. Particularly, from the point of view of present action, utility of past actions is a meaningless concept; however, the study of the utility that such actions may have had when they were taken can be quite meaningful. More generally, Utility is meaningful only for projects, never for objects. Projects here must not be understood in the restricted meaning of conscious projects, but in the more general one of a consistent, lasting, dynamic behavior.

Note that projects can be considered in turn as objects of a more abstract ``meta-'' system; but the utility of the objectized project becomes itself an object of study to (an extension of) the metasystem, and should not be confused with the utility of the studying metasystem. Sciences of man and nature (history, biology, etc) lead to the careful study of terrifying events and dangerous phenomena, but the utility of such study is proportional rather to some kind of relevance or amplitude of the studied projects, than to their utility from the point of view of their various actors.

Utility is a moral concept, that is, a concept that allows pertinent discourse on its subject. More precisely, it is an ethical concept, that is, a concept colored with the ideas of Good and Duty. It directly depends on the goal you defined for general interest. Actually, Utility is as well defined by the moral concept of Good, as Good is defined by Utility; to maximize Good is to maximize Utility.

Like Good, Utility needs not be a totally ordered concept, where you could always compare two actions and say that one is ``globally'' better than the other. Utility can be made of many distinct, sometimes conflicting criteria. Partial concepts of Utility can be refined in many ways to obtain compatible concepts that would solve more conflicts, gaining separation power, but losing precision.

However, a general theory of Utility is beyond the scope of this article (those interested can find a first sketch in J.S.Mill's ``Utilitarianism'' [6], and a more refined discussion in Henry Hazlitt's ``The Foundations of Morality'' [5]). Therefore, we'll herein admit that all the objects previously described as valuable (time, effort, etc) are indeed valuable as far as general interest is concerned.

2.2  Information

Obviously, a man's judgement cannot be better than the information on which he has based it. Give him the truth and he may still go wrong when he has the chance to be right, but give him no news or present him only with distorted and incomplete data, with ignorant, sloppy or biased reporting, with propaganda and deliberate falsehoods, and you destroy his whole reasoning processes, and make him something less than a man.

-- Arthur Hays Sulzberger
Judgements of Utility deeply depend on the knowledge of the project being judged, of its starting point, of its approach. Now, humans are no gods who have universal knowledge to base their opinions upon; they are no angels who by super-natural ways, receive infuse moral knowledge. Surely, many people believed it, and some still do. But everyone's personal experience, and mankind's collective experience, History, show how highly improbable such things are. Without any further discussion, we will admit an even stronger result: that, by the finiteness of the structure of the human brain, any human being, at any moment, can only handle a finite amount of information.

This concept of information should be clarified. The judicial term from the Middle Ages slowly took the informal meaning of the abstract idea of elements of knowledge; it was only with seventeenth century mathematicians that a formal meaning could timidly appear, that surprisingly found its greatest confirmation in the nineteenth century with thermodynamics, a branch of physics that particularly studied large dynamical systems. Information could thus be formalized as the opposite of the measurable concept of entropy. The information we have irreversibly decreases as we look forward or backward in time, beyond the limits of our knowledge, on this side of these limits being present. That is, information is a timely notion, valid only in dynamical systems. And such is Life, a dynamical system.

As for Utility before, there needs not be a universal total ordering on Information; what we most often have is partial orderings, and each of us has to try arbitrarily choose finer orderings when basing a decision upon equivocal information. For information is also an moral concept, though it is not until late twentieth century, with cybernetics, that the deep relationship between information and morals explicitly appeared. Few people remember cybernetics as something else than a crazy word associated to the appearance of information technology, but we invite the reader to consult the original works of Norbert Wiener on the subject [7]. However, this relationship had been implicitly discovered by liberal economists of the eighteenth and nineteenth centuries, then rediscovered by biologists studying evolution, and surely, many have always intuititively felt this relationship. What allowed to make it explicit might be the relativization of ethics as something that was not to be taken as known and granted, but first as unknown and more recently as incomplete.

Moral judgments depend on the information we have, so that in order to make a better judgement, we must gather more information. Of course, even though we might have rough ways to quantify information, this doesn't make elements of information of same quantity interchangeable; What information is interesting depends on the information we already have, and on the information we can expect to have. Now, gathering information itself has a cost, that physicists may associate to free energy, which is never zero, and must be taken into account when gathering information.

Because the total information that we can handle is limited, any inadequate actual information that be gathered would be to the prejudice of more adequate potential information. Such inadequate information is then called noise; noise is worse than lack of information, because it costs resources that won't be available for adequate information. Thus, in our dynamic world, the quest of information itself is subject to criteria of utility, and the utility of information is its pertinency, its propensity to favorably influence moral judgements. As an example, the exact quantization of information, when it is possible, itself requires so much information, that it is seldom worth to be sought. Of course, pertinency in particular is not more an absolute concept than utility in general. When a criteria for pertinency is implicitly available, we might use the term ``Information'' for raw information, and ``Knowledge'' for pertinent information.

So to gather information in better ways, one must scan the widest possible space of elements of knowledge, which is the essence of Liberty; but the width of this knowledge must be measured not in terms of its cost or of its interest in case it was true, but in terms of its pertinency and of its solidity, which is the essence of Security.

These are dual, inseparable aspects of Knowledge, that get their meaning from each other. Any attempt to priviledge one upon the other is pointless, and in the past and present, such attempts have led to many a disaster: trying to promote some liberty without corresponding security leads to chaos, whereas promoting security without associated liberty leads to totalitarianism.

Reality and potentiality, finiteness of knowledge, world as a dynamic system, relation between information and decision, duality of liberty and security, all these are parts of a consistent (we hope) approach of the world, that we will admit in the rest of this paper, at least on the considered subjects. A more detailed study of these moral issues per se would certainly be quite interesting, but the authors feel that such study ought to be postponed to another paper, and invite readers to refer to the bibliography (and contribute to it), so as to focus on the goal of this article, discussion about Computer Systems, whereas these moral concepts are a means.

2.3  Computers

The highest goal of computer science is to automate that which can be automated.

-- Derek L. VerLee
Computers are machines that handle quickly large amounts of exact discrete information, and interact with the external world, according to a set of exact discrete directives called ``programs''. This makes them most suited to apply concepts from the above-mentioned information theory; everywhere else in life, information is approximate continuous, and difficult to quantize. Actually, the histories of information theory and of computers, that are information technology, are deeply interrelated; but these histories escape the subject of this article. Just note that being a computer is an abstract concept independent from the actual implementation of a computer: if most current computers are made of silicon transistors, their ancestors were made of metallic gears, and no-one knows what their remote successors will be made of.

Computers are built and programmed by men and for men, with earthly materials and purposes. Hence the utility of computers, among other characteristics, is thus to be measured like the utility of any object and project in the human-reachable world, relatively to men. And, because what computers deal with is information, their utility lies in what will allow humans to access more information in quicker and safer ways, that is to communicate better through them computers with other humans, with nature, with the universe.

Again, Utility criteria should not only compare the visible value of objects, but also their cost, often invisible, in terms of what objects where discarded for it. Cost of computer information includes the time and effort spent at manufacturing or earning money to buy computer hardware and software, but also the time and effort spent before the computer to explain it the work you want to be done, and the time and effort spent verifying, correcting, trying again the obtained computer programs, or just worrying about the programmed computer crashing, preparing for possible or eventual crashes, and recovering from these. All this valuable free energy might have been spent much more profitably at doing other things, and is part of the actual cost of computerware, even when not taken into account by explicit financial contracts. We will stress on this point later.

So to see if computers in general are a useful tool, we can take the lack of computer as the implicit reference for computer utility, and see how computers benefit or not to mankind, comparing the result and cost. Once properly programmed, computers can do quickly and cheaply large amounts of simple calculations that would have required a large number of expensive human beings to manage (which is called ``number crunching''); and they can repeat relentlessly their calculations without committing any of those mistakes that humans would undoubtly have made. When connected to ``robot'' devices, those calculations can replace the automatic parts of work, notably in the industry, and relieve humans from the degrading tasks of chain work, but also control machines that work in environments where no human would survive, and do all that much more regularly and reliably than humans would do. Only computers made possible the current state of industry and technology, with automated high-precision mass production, science of the very small, the very large, and the very complex, that no human senses or intelligence could ever have approached otherwise.

Thus, computers save a great amount of human work, and allow things that no amount of human work could ever bring without them; not only are they useful, but they are necessary to the current state of human civilization. We let the reader meditate on the impact of technology on her everyday life, and compare it to what was her grandmother's life. That this technology may be sometimes misused, and that the savings and benefits of this technology be possibly misdistributed, is a completely independent topic, which may hold for quite any technology, and which will not be otherwise commented in this article.

2.4  Limits of Computers

Some only see in computer's utility a matter of raw performance, a quantitative progress, but not a qualitative one, at least, nothing qualitatively better than what other tools bring about. However we already saw that beyond their performance, beyond the volume of information handled and the speed at which it is handled, which already suffice to make computers a highly desirable tool, computers bring something fundamentally more important than raw information or raw energy, something that is seldom explicitly acknowledged: a new kind of reliability that no human effort can achieve.

Not only can computers perform tasks that would require enormous amounts of human work without them, and do things with more precision than humans, but they do it with reliability that no human can provide. This may not appear as very important, not even as obvious, when the tasks undertaken are independent one from the other, when erroneous results can be discarded or will be compensated somehow by the mass of good results, or when on the contrary the task is unique and completely controlled by one man. But when the failure of just one operation involves the failure of the whole effort, when a single man cannot warranty the validity of the task, then computers prove inestimable tools by their reliability.

Of course, computers are always subject to failures of some kinds, to catastrophes and accidents; but computers are not worse than anything else with respect to such events, and can be arbitrarily enhanced in this respect, because their technology is completely controlled. However, not only is it not a problem particular to computers, but computers are most suited to fight this problem: unpredictable failures are the doom of the world as we live, where we always know a tiny finite piece of information, so even if we can sometimes be fairly sure of many things, and can never be completely sure about anything, as we can never totally discard the event of some unexpected external force significantly perturbating our experiments. The phenomenon is the most pronounced with humans, where every individual is such a complex system by himself, that one can never control all the parameters that affect him, can never perfectly reproduce them; so there are always difficulties in trusting a man's work, even when his sincerity is not in doubt. On the contrary, by their very mechanical nature of their implementation, by the exactitude of their computations, which derives from their very abstract design principle, computing is both a predictable and a reproducible experiment; it can be both mathematically formalized, and studied with the tools of the physicists and engineers; computer behavior is both producible and reproducible at will; and this founds computer reliability: you can always check and counter check a computer's calculations, experiment with them under any condition one requires before one will trust them.

We see that computers allow to accumulate reliability like nothing else in the human-reachable world, though this reliability must be earned in the hard way, by ever-repeated proofs, checks, and tests. In fact, this reliability is one of the two faces of information, which is what information technology is all about, of which computers as we know them are the current cutting edge.

The problem with computers, the absolute limit to their utility, is that by the same mechanical virtues that make us trust their answers as the result of understandable and double-checkable formal computations, they somehow can't create information that isn't formally derivable from their input, and in as much as we introduce randomness and heuristics in their input to simulate more creative behavior, we are not able to trust the answers anymore. That is, computers may reveal reveal potential trust in existing information; they may build trustable information from previous trustable information; they may generate untrustable information at random; but they cannot generate new trustable information about the external world, least it be tautological. Any new trustable information that lies in a computer must derive through natural laws of logic from the work of men who built and programmed the computers, and from the external world with which the computer interacts by means of sensors and various devices.

Hence the limits of computers are men: what they can program in a computer, what the devices they hook into computers produce, what they teach the computer to do with all the input. If a man misdesigns or misprograms a computer, if he feeds it with improper data, if he puts it in an environment not suitable for correct computer behavior, then the computer cannot be expected to yield any correct result. One can fully trust everything he sees and tests about a computer, but as computers grow in utility and complexity, there are more and more things one cannot personally see and test about them, so one must rely on one's fellow human beings to have checked them. Again, this is not worse than anything else in the human world; but for computers as well as for anything else, these are hard limits of which we should all be conscious.

2.5  Computing as a Project

Man is surely a limit to the power of computers, in that computers are made by man, and can be no better than man makes them. But this is not to be understood individually, as computers are not each the work of one man, but are collectively the work of mankind. Computing is a global project.

Like any product of civilization, computers depend on a very rich technological, economical, and social context, before they can even exist, not to talk about their being useful. They are not the work of a single man, who would be born naked in a desert world, and would build every bit of them from scratch. Instead, they are the fruit of the slow accumulation of human work, of which the foundations of civilization participate at least as much as the discoveries of modern scientists. The context is so necessary, that most often it is implicit; but one shouldn't be mistaken by this implicitness and forget or deny the necessity of the context. Actually, this very context, result of this accumulation process, is what Civilization is.

But again, the characteristic of information technology, is that the information you manage to put in it can be made to decay extremely slowly, as compared to objects of same energy: we can expect data entered today in a computer, that is interesting enough to be copied once every ten years at least, to last as long as information technology will exist, that is, as long as human civilization persists. Of course, huge monuments like the egyptian pyramids are work of men that decay slowlier, need less care, and resist to harsher environments, so may last longer; but their informative yield is very weak, as compared to their enormous cost. If only slowness to decay was meant and not informational yield, then nuclear wastes would be the greatest human achievement!

Now computing has the particularity, among the many human collective projects, and as part of mankind being its own collective project, that it can be contributed to in a cumulated way for years. For this reason, we can have the greatest hope in it, as a work of the human race, as a tool to make masterpieces last longer, or as a masterpiece of its own. Computing has already gained its position among the great inventions of Man, together with electricity, writing, and currency.

This whole paper tackles the problems of software as an evolving domain. If ever software settles and stabilizes, or comes to a very slow evolution, then the phenomena described in this paper may cease to be dominant in the considered domain. However, because life is movement, as long as there will be life, there will be a domain where these phenomena are of importance. Besides, the authors are confident that computer software, whatever it will be like, will be a lively domain until it possibly reaches AI.

2.6  Computing versus Artificial Intelligence

Alan Turing thought about criteria to settle the question of whether machines can think, a question of which we now know that it is about as relevant as the question of whether submarines can swim.

-- E.W. Dijkstra
Let us justify the persistence of Computing as a Project, even when faced with this alleged doom of it: Artificial Intelligence.

Many dream, hope, worry, predict or otherwise expect that some day, the cumulated work invested in computing will allow humans to create some computer-based being, which they call ``artificial intelligence'', or more simply, AI. Such AIs would rival with their human creators as for ``intelligence'', that is, their creativity, their ability to undertake independently and voluntarily useful projects; they dream (or some of them have the nightmare) that mankind engenders a next step in evolution by non-genetical means. According to some people, such AI would be the End of Computing as a Project, since humans wouldn't need to program anymore, leaving the task to AIs.

Now, should this dream come true (the eventuality of which won't be discussed in this article), by Information Theory's version of Cantor's diagonal argument, the workings of AIs must globally surpass the understanding of AIs themselves, and hence of humans, if the AIs are similarly endowed as humans. This holds even though the general principles behind the functioniong of AIs might be understood: as with physics, the knowledge of elementary laws doesn't imply understanding of whole phenomena, for the formidable context involved in anything but the simplest applications (and the most useless, as far as ``intelligence'' is meant) would make it impossible for the most developed human or artificial brain to apprehend.

The latter argument does not question the possibility of AI as an eventual human work: there is plenty of evidence that systems governed by a few human-understandable, human-enforceable rules can generate ununderstandable chaotic behavior2. Rather, the argument means that if we replace in all the current discussion ``human'' by ``sentient'', with AIs being a new kind of different (superior or not) sentient beings, the situation of computing would remain essentially the same.

Indeed, Computing is an activity characterized by exact formalizability and as complete understanding as desired of running programs, with the choice and evolution of the programs being directed by human (sentient) beings.

AI, if it ever appears, will not quite be computing as we know it anymore, yet will need Computing even more than we do now.

Maybe this AI will use a computer as an underlying structure, and will need most advanced computing techniques to be deployed; but the AI itself will not be a computer as we defined it, and querying the AI will not be computing anymore, though some may think that the ultimate goal of computing be to transcend computing in such way.

Anyway, current design of computing systems, as we will show, greatly limits the potential of computer software into what a few programmers can fully understand; hence, until this design is replaced, AI will stay a remote dream. And even when and if this dream comes true, the problems we describe may be food for thought for the AIs that would replace current human readers. Computing is will always be a Project for sentient beings, be them AIs instead of humans.

2.7  Computing Systems

Computer Science is no more about computers than astronomy is about telescopes.

-- E. W. Dijkstra
We herein call Computing System any dynamic system where what interests us is the exact information contained by part of it. Note that a computing system is not quite the same as a computer system. In a computer system, the computer is a static tool used in the project, but not part of it. In a computing system, the computer (or most probably only its program) is the very dynamic project being considered. Computer systems have been the subject of study of many very proficient people, who have published a great number of most interesting books on it. Computing systems are the subject of this article, upon which we'll try to bring new lights.

As an example, a given modern washing machine is often a very useful computer system, where a static program manages the operations; but its utility lies entirely in the washing of clothes, so that as a computing system, it is not excessively thrilling. The development of washing machines, on the other hand, contains a computing subsystem of its own, which is the development of better washing programs; this computing system might not be the most exciting one, but it is nevertheless an interesting one.

Similarly, a desktop computer alone might be a perfect computer system, it won't be a very interesting computing system until you consider a human, perhaps one among many, sitting in front of it and using it. And conversely, a man alone without computer might have lots of ideas, he won't constitute a very effective computing system until you give him the ability to express it into computer hardware or software. Note that desktop publishing in a business office is considered as being some kind of software, but that, as long as this information is not spread, copied and manipulated much by computers, as long as the writing is very redundant but not automated, it is not a very interesting computing system. Developing tools to automate desktop publishing, on the other hand, is an interesting computing system; even desktop publishing, if it allowed to take any tiny active part in the development of such tools, would be an interesting computing system; unhappily, there is a quasi-monopoly of large corporations on such development, that greatly restricts the amount of computing in that system, which we'll investigate in following chapters.

A most interesting Computing System, which particularly interests us, is made of all interacting men, computers, and particles in the Universe, where the information being considered is all that encoded by all known computers; we may call it the Universal Computing System (UCS). Actually, as the only computers we know in the Universe are on Earth, or not far from it in space, it is the same as what we might call the Global Computing System (GCS); however the two might diverge from each other in some future, so let's keep them separate.

Now, the question that this article tries to answer is ``how to maximize the utility of the Universal Computing System ?''. That is, we take the current utility of computers for granted, and ask not how they can be useful, but how their utility can be improved, maximized. We already saw that this utility depends on the amount of pertinent information such systems yield as well as the free energy they cost. But to answer this question more precisely requires at the same time a general study of Computing Systems in general, of the way in which they are or should be organized, and a particular study of current, past, and expected future computing systems, that is, where the Universal Computing System is going if we're not doing anything.

2.8  Subsystems

When studying a dynamic system, one must always place oneself in an external, ``meta'' system, and choose some ``representation'' of the studied system. What kind of meta-system(s) and representation(s) to choose is a difficult question; again, the representations are better that allow to extract more information from the study of the system, which needs not be a total ordering among representations.

Particularly, one could try to formalize the UCS with the set of the physical equations of its constituting particles. While such thing might be ``theoretically possible'', the complexity of the obtained equations would such that any direct treatment of them would be impossible, while the exact knowledge of these equations, and of the parameters that appear in it, is altogether unreachable. Thus, this formalization is not very good according to the above criterion.

A fundamental tool in the study of any system, dynamic or not, called analysis, consists into dividing the system into individual subsystems, such that those subsystems, and the interactions between those subsystems be as a whole as simple as possible to formalize. Note that these subsystems need not (and often should not) form an homogeneous mass of (quasi-)isomorphic systems; on the contrary, the richness of information in the total system will depend on the fact that every subsystem be specialized in its way, and doesn't waste its resources by merely being redundant with its neighbours.

For computing systems, the basic, obvious though not sole possible analysis is to consider computers and their human users as the individual subsystems. Because information flows quickly and broadly inside each of these subsystems, but comparatively slowly and tightly between them, they can be considered as decision centers, each of which takes actions depending mostly on its internal information, and slowly interacting with each other ``on purpose'' (because according to these internal informations).

Humans interact with other humans and computers; computers interact with other computers and humans. But while the stable, exact, objectized information lies in the computers, the dynamic nature of the project can be traced down to the humans; thus, even though only the computerized information might be ultimately valuable to the computing system, the information flow among humans, is a non-negligible aspect of the computing system as a project.

Surely, this is not the only possible way to analyze computing systems; but it is a very informative one, and any ``better'' analysis should take all of this into account. For instance, one relevant approach is to refine the subdivision of computer activities according not just to corresponding individual human computer users of these activities, but according to division of trust between these humans under the various roles that they assume: the same person may assume several roles during his computer life, and the trust one places in various programs (including those developed by oneself while assuming another role) varies according to these roles.

Anyway, the point is that what counts when analyzing a system is the ability of the analysis to yield relevant information at a competitive cost. A ``canonical representation'' in terms of atoms and waves, while possibly being a valid analysis of a system, needs not be the most interesting one. Computers may be made, from the hardware, physical point of view, of electronic semiconductor circuitry and other substratum; from the information point of view, this is just transient technological data; tomorrow's computers may be made of a completely different technology, they will still be computers. Similarly, living creatures, among which humans, are, as far as we know, made of organic molecules; but perhaps on other places in the universe, or in other times, things can live that are not made of the same chemical agents (actually, there is genetic variation in the molecular composition of even known living creatures).

What makes creature living is not the matter of which it is made (or else, the soup you obtain after reducing a man to bits would be as living as the man). What makes the living creature is the structure of internal and external interaction that the layout of matter implements. A chair is not a chair because it's made of wood or plastic, but because it has such a shape that a human can sit on it. What makes the thing what you think it is, are abstract patterns that make you recognize it as such, that constitute the idea of the thing. And as for computing systems, the idea lies in the flow of information, not the media on which the information flows or is stored.

2.9  Operating Systems

Often in a discussion, I will ask the other person to define some term. It is not that I believe that terms are absolute, and want to test whether the person knows its One True Meaning. On the contrary, words are conventions, and it is necessary to negociate a common meaning so a sane discussion be possible. For a constructive discussion is a negociation.

-- Faré
Now, we can define what an Operating System is (for which we use the acronym OS), that the project of this article is all about.

Given a collection of subsystems of a cybernetical systems, we call ``Common Background'' the information that we can expect every of these subsystems to have. For instance, if we can expect most Europeans to wear socks, then this expectation is part of the Common Background of Europeans. If we can expect all the computers we consider to use binary logic, then this fact is part of the Common Background for those computers. This Common Background can thus contain both established facts and probabilistic expectations. The Common Background for a collection of human beings is called their collective culture, or even their Civilization, if a large, (mostly) independent collection of human beings is considered. The common background for a collection of computers is called their Operating System.

The concept of Common Background appears in any cybernetical system where a large enough number of similar subsystems exist. Common Backgrounds grow in complexity only if those subsystems do get more complex too, and the large number of such systems means that these should be self-replicating, or more precisely correlated to self quasi-replication. To sum it up, an interesting concept of Common Background is most likely to appear only when some kind of ``life'' has developed in the cybernetical system, or when we're examining a large number of specifically considered similar systems.

Note that the ``similarity'' between the subsystems tightly corresponds to the existence of information common to the subsystems, that constitute the Common Background. In no way does this similarity necessarily correspond to any kind of ``equality'', among the subsystems: how could two subsystems be exactly the same, when they were specifically considered as disjoint subsystems, made of different atoms ? The similarity is an abstract, moral, concept, which must be relative to the frame of comparison that makes the considered information pertinent; a moral frame of Utility can do, but actually, any moral system in the widest acception can, not only those where an order of ``Good'' was distinguished. On the other hand, finding a lot of similarities in somehow (or completely) impertinent subjects (such as gory ``implementation details'') doesn't imply an interesting common background; finding a few similarities on pertinent subjects might not be sufficient to imply an interesting common background either. (technical remark: given a digital encoding of things, quantifying the level of interest of a common background might be expressed in terms of conditional Kolmogorov complexity.)

If we consider humans in the World, can we find cells that are ``exactly the same'' on distinct humans ? No, and even if we could find exactly the same cell on two humans, it wouldn't be meaningful, just boring. Yet you can nonetheless say that those two humans share the same ideas, the same languages and idioms or colloquialisms, the same manners, the same Cultural Background. And this is meaningful, because these are used to communicate, and greatly affect the flow of information, etc. Genetical strangers who were bred together share more background as regards society than genetical clones (twins) who were separated after their being born.

It's the same with computers: computers of the same hardware model, having large portions of common implementation code, but running completely different ``applications'' that have nothing conceptually common to the human user, might be considered as sharing little common information; on the contrary, even though computers may be of completely different models, of completely different hardware and software technologies, thus sharing no actual hardware or software implementation, they may still share a common background, that enables them to communicate and understand each other, and react similarly to similar environments, so that to the human users, they behave similarly, manipulate the same abstraction. That we called the Operating System.

2.10  Controversy about the Definition for an OS

When words are unfit, speech is unadapted and actions are unsuccessful

-- Confucius
There have always been many lengthy arguments everytime someone proposed any definition for what an Operating System is. Many will object to the above definition of an OS, because it doesn't fit the idea they believe they had of what an OS is. Now, let's see the requirement for such a definition: as a definition, it should statically reference a consistent concept, independently enough from space, time, and current state of society and technology, so as to enable discourse about OSes in general; as applying to an existing term, it should formalize the intuitive idea generally vehiculated by this term, and as much as possible coincide with its common usage, while staying consistent (of course, where common usage is inconsistent, the definition cannot stick to the whole of it).

The definition the from previous chapter does fulfill these requirements, and it is the only one known to date by the author that fulfills them. This definition correctly identifies all the programs and user interface of Unix, DOS, Windows*, or Macintosh machines to be their respective OS, the class of similar machines being considered at each time, because they are what the user/programmer can expect to have when encountering such machines. It does support both the points of view that such software or feature, is an OS or part of the OS, or that it is not, depending on the set of machines being considered.

By ``Operating System'', people intuitively mean the ``basic'' software available on a computer, upon which the rest is built.

The first naive definition for an OS would thus be to define it by ``whatever software is available with the computer when you purchase it''. Now, while this sure unambiguously defines an OS, the according pertinency is very poor, because, by being purely factual, the definition induces no possible moral statement upon OSes: anything that's delivered is an OS, whatever it is. You could equivalently write some very large and sophisticated software that works, or some tiny bit of software that doesn't, still it'd be OS, by the mere fact it is sold with the computer; one could buy a computer, remove whatever was given with it, or bundle completely different packages to it, then resell it, and whatever he resells it with would be an OS. This definition, while it embodies some wisdom about the fact that the concept of OS should capture the features of actually deployed software, is so poor as to be unusable, because it isn't based on a relevant notion of deployment.

Then, one could decide that because this question of knowing what an OS is is so difficult, it should be let to the high-priests of OSdom, and that whatever is labelled ``OS'' by their acknowledged authority should be accepted as such, while what isn't should be deemed with the utmost defiance. While this puts the problem back, this is still basically the same attitude of accepting fact for reason, with the little enhancement that the rule of force applies to settle the fact, instead of raw facts being blindly accepted. This is abdicating reason in favor of religion. Now, the high-priests of computing that are to give a definition for an OS are not more endowed than the common computer user to give a good definition. Either they only abuse their authority to give unbacked arbitrary definitions, or they have some reasonable argument to back their definition. Since we're studying computer science, not computer religion, we can but contemptuously ignore them in the first case, and focus on their arguments in the second case. In any case, such definition by authority is useless to us.

Those who escaped the above traps, or the high-priests of the second trap, will need other criteria to define an OS. They might most obviously try to define an OS as a piece of software that does provide such and such services, to the exclusion of any other services, each taking the list of provided services from their favorite OS or OS-to-be. Unhappily, because different people and groups of people have different needs and history, they would favor differently featured OSes. Hence, they would all define an OS differently, and every such definition would disqualify every past, present and future systems, but the few ones considered from being ``OSes''. Hence, this conception leads to endless fights about what should or not be included in a piece of software for it to be an OS. When human civilization rather than just computer background was concerned, these would be wars and killings, crusades, colonizations and missions, in the hope to settle the one civilization over barbarism. Even without fights, we see that completely different sets of services equally qualify as OSes, much like completely different civilizations like the ancient Greek and ancient Chinese civilizations, while being completely different, both qualify as civilizations, not talking about other more or less primitive or sophisticated civilizations. Such a definition for an OS cannot be universal in time and space, and only the use force can have one prevail, so it becomes a new religion. Again, this is a poor definition for an OS.

The final step, as presented in the preceding chapter, is to define an OS as the container, instead of defining it as the contents, of the commonly available computer services; in other words, we give an intentional definition for an OS, instead of looking for an extensional definition. We saw that OS was to Computing Systems what Civilization was to Mankind; actually Computing Systems being a part of the Human system, their OSes are the mark of Human Civilization upon Computers. The language, habits, customs, scriptures, of some people, eating with one's bare hands, a fork and knife, or chopsticks, don't define whether these people have a civilization or not; they define what their civilization is. Similarly the services uniformly provided by a collection of computers, the fact that a mouse or a microphone be used as an input device, that a video screen or a braille table be used as an output device, that there be a built-in real-time clock or not, those features don't define whether those computers have an OS or not, but rather they define what is this OS they have3.

Our definition allows us to acquire knowledge, while refusing to endorse any dogma about what we can't know; this is the very principle of information against noise, of science against metaphysics. It separates the contingencies of life from the universal concept of an OS. An OS is the common background between the computers of a considered collection. This moves the question of knowing what should or not be in an OS from a brute fight between OS religions, from the mutual destruction of dogmas, to a moral competition between OSes, to the collective construction of information. That's why we claim that our definition is more pertinent than the other ones, hence more useful, by an argument previously explained.

2.11  Operating System Utility

In an external environment which constantly changes and in which consequently some individuals will always be discovering new facts, and where we want them to make use of this new knowledge, it is clearly impossible to protect all expectations. It would decrease rather than increase certainty if the individuals were prevented from adjusting their plans of action to the new facts whenever they became known to them. In fact, many of our expectations can be fulfilled only because others constantly alter their plans in the light of new knowledge. If all our expectations concerning the actions of particular other persons were protected, all those adjustments to which we owe it that in constantly changing circumstances someboy can provide for us what we expect would be prevented. Which expectations ought to be protected must therefore depend on how we can maximize the fulfilment of expectations as a whole.

-- F.A. Hayek, Law, Legislation and Liberty, I.4.e [4]
Let it be clear that the concept of Operating System does not apply pertinently to machines that do not evolve, that do not communicate with other machines, that do not interact with humans.

Such machines need complete, perfect, highly-optimized stand-alone software, adapted just to the specific task they are meant to accomplish. Whatever can be found in common among many such machines isn't meaningful to running those machines, as this does not influence the way information flows in the system.

However, as soon as we consider further possible versions of a ``same'' piece of software, as soon as we consider its incomplete development and maintenance process, the way it interacts with other pieces of software, whether in a direct or remote fashion, as soon as it has any influence on other software, be it through the medium of humans who are examining it before to build the other pieces software (or while building these), then we are indeed talking about flow of information, and the concept of OS does become meaningful.

See that communication between machines does not always mean that some kind of cable or radio waves be used to transmit exact messages; rather, the most used medium for machines to communicate pertinent have always been humans, those same humans who talk to each other, read each other's books, articles, and messages, then try to express some of their resulting ideas on machines.

Particularly in the case above of lots of similar perfect machines, the concept of an OS on those machines might have been meaningless, or strictly limited to a vague or limited common interface that they may offer to customers; but the concept of an OS was quite meaningful on the development platforms for these, where a lot of common information is potentially shared by many developers working more or less independently.

As we saw that the pertinency of a concept is related to the utility of the described object, we find the the utility of an OS lies in its dynamic aspects. An obvious dynamic aspect of the OS is how it itself evolves; but from the point of view of arbitrary user subsystems, the fundamental dynamic aspect of the OS, that dictates its Utility, is its propensity to ease communication of knowledge between the considered subsystems. Of course, these two aspects of course interact with each other.

An OS eases communication of knowledge in that it will allow to pass more Information, by providing fast broad communication lanes and information stores, but also in that it gives pertinency to this Information, thus transforming it into Knowledge, by providing a context in which to interpret received information as unambiguously as possible, and in which to synthetize new information that represent as accurately as possible the ideas that are originally meant. Note that both Quantity and Quality of Information are being considered here, and that interaction goes in both ways.

An OS will usefully evolve when modifications to a same OS project will allow improvements in the above communication of knowledge. For obvious reasons of information stability, the OS, can only evolve slowlier than its user base, and its design, which is the essence of the OS, and what manages the pertinency of Information, must change slowlier than its implementation (that drives raw performance).

2.12  Operating System Expressiveness

An Operating System is the common context in which information is passed across the Computing System. It is the one reference used for arbitrary subsystems to communicate information.

Hence, the OS dictates not so much the amount of information that can be passed, which is mostly limited by the laws of physics and technological hardware achievements, as it dictates the kind of information that can be passed, which is a question of OS design proper.

All OSes are more or less equal before technology, which is an external limitation; not all are equal before design, which is a internal limitation.

For instance, given equivalent post office administrations, two countries can ensure similarly fast and reliable shipping of goods. However, the actual use of the post office for exchanging goods will greatly depend on what warranties the state will give to both people who send and people who receive goods: how well identified are the parties, how agreements happen, how contracts are signed, how signed contracts bind the contractors, how payment happens, how disagreements are settled, how well the sent goods are guaranteed to match the advertisements, how much information people have on competing solutions, how likely a failure is likely to be, what support is available in case of failure, what recourse have parties against breach of contract by the other party, etc.

Depending on the rules followed by the system, which are part of the OS design (according to our definition of an OS), the same underlying hardware can be either an efficient way to market goods, or an inefficient risky gadget.

The Internet is a perfect example of a media with a great hardware potential for information passing, but a (currently) poor software infrastructure, that needs lots of enhancements before it can safely be used for large-scale everyday transactions.

This will surely happen, but if things go as can be predicted, there is a wide margin for improvements.

The key concept here is the expressiveness of the OS, which decides what kind of information is expressible by the OS.

The common misconception about expressiveness is that Turing-equivalence be all there is to it. The theory says that ``all (good enough) computing systems are Turing-equivalent'', in that a good enough system can simulate any other system through an simulating interpreter or simulator, so it suffices to provide a Turing-equivalent system to be able to simulate any other system. But a simulation of something is not the original thing. Just like the idea of money is not actual money4. The mere idea that someone may have signed a contract is not a binding contract in itself. Even the fact of actually signing a contract is not binding, in absence of any (explicit or implicit) legal context. If the system won't enforce your contracts, no one will. In absence of system support, the only enforceable contracts you can build are those where it suffices to dynamically check compliance from cooperative third-parties, and it is always legit for a party to fail. The catch is that a simulator gives no warranty: the meaningfulness of the result depend on the objects being manipulated respecting conventions for the validity of simulated representations. If the associated warranties can be interned by the very original system, then indeed that system can express rather than merely simulate the other system. If these warranties cannot be interned, then an external agent (most likely, the programmer) will have to enforce them, and you have to trust him not to fail, without recourse. Arguably, being satisfied with entering a simulation to enforce the warranties that one requires from the system is not using the original system, but building a new system above the first one, and then limiting interactions with other subsystems within that new more expressive system, while praying helplessly that that no agent in the original system should break the rules of the new system. The keyword here being ``helplessly''.

Some will suggest paranoidly testing for dynamic compliance of every single operation for which contracts were passed; but such an approach not only is very expensive when even feasible but is not a solution (though it might be better than nothing): run-time checking can detect failure to comply but it cannot enforce compliance. In everyday life, it might mean that whenever you provide a service to a stranger, this stranger may run away and not pay you back, and you have strictly no recourse, no possibility to sue or anything. At times, run-time checking may allow to take appropriate counter-measures, but it might be too late. In the case of a spacerocket (e.g. Ariane V), a runtime failure means billions of dollars that explode. In the case of a runtime failure in control software for a nuclear device (civilian reactor or military missile), I just don't dare imagine what it might mean! In any case, having some paranoid test code that will terminate the program with message ``ERROR 10043: the nuclear plant is just going to unexpectedly disintegrate.'' won't quite help. Finally, the ability to (counter-)strike, in absence of any system control, brings new dangers that in turn meet lack of solution, as malevolent agents may strike at will.

All in all, the expressiveness of an operating system is its ability to require and provide trust, to enable exchange of trusted services, above that which can be built from zero by iterative interaction between agents. Of course, ultimately, this trust will have to rely on external, human processes. The question is how much the system relieves us

EVERYTHING BELOW IS A DRAFT, AND MUST BE COMPLETED OR REWRITTEN.....

2.13  Computing System Structure

Up to now, we've seen and discussed the external constraints of an OS, what is its goal, its why, in the implicit larger Computing System. Now that this goal is clarified, and keeping it in mind, it's time to focus on the internal constraints of an OS, its structure, its how.

The structure of an OS is the data of its characteristic components, their interrelationships, and their relationships with the rest of the computing system. We must thus study once again the structure of the whole Computing System, of which the OS is but an aspect. For this, we will once again find inspiration in considering cybernetical systems in general, and in comparing the situation with that of another kind of well-known cybernetical systems, human societies. The latter analogy is more than a mere metaphor, since one aspect of computing systems is as actual human societies, with users and programmers being the humans, and the running programs being activities of these humans. Indeed, until AIs come into existence, all programs are human activities (and if AIs ever exist, they won't change much of the current discourse, if we understand ``human'' as ``sentient being'').

However, the analogy is certainly not an exact correspondance (an ``isomorphism''), and the way it can validly bring insight into the domain of computer systems is often more subtle than may appear at first. Most importantly, it breaks down (as far as go specific properties not true of any cybernetical system) when we consider the computerized part of computing systems, that is, programs. Indeed, computing systems comprise as basic identifiable agents not only complex unformalizable humans, but also running programs, that are quite different, simple and formalizable, and are the center of interest and of information processing in the system.

There is still some relevance to the division of computer activities depending on the human persons who run these activities, provide them with input and use their output; issues of trust between humans under the multiple roles they assume are essential in the structure of systems: when two humans or roles do not trust each other, they must rely on some kind of physical or logical separation enforced by a trusted combination of hardware, software and wetware. The ability to express and correctly implement such separation in a way that users can trust is an essential feature of an OS; When such concerns are not satisfyingly tackled by the software part of an OS, they will be tackled by the hardware part, which means buying, deploying and configuring more computers, one per user or assumed role, or by the wetware part, by having it the human users' responsibility to never do anything wrong with the capabilities with which the software entrusts them whereas it shouldn't.

But while this trust aspect covers any activity involving dynamic interaction with the external world in any cybernetical system, there is a peculiarity of computing systems that OS design can and must take advantage of: the actual data and programs that are stored in a computer are purely extensional entities; that is, their digital description suffice to deduce all there is to them.

extensional vs intentional aspects of programming. to take advantage of it, must respect the expected intentional modifications. Managing the coherency between diverging intentions.

Cybernetical systems

of which computing systems are a projection. Human societies are made of lots of people, each with its own needs and capabilities, desires and will. Computer societies are similarly made of these same people, considered through the limited scope of the way they interact with computers, through computers, about computers, and of the computers themselves.

People communicate with each other, and are dynamically organized in families, friendships, associations, companies, countries, confederations; every group is more or less stable;

User services vs kernel services. Privatization vs nationalization of services. Rule of Law vs State Management.

A computing system IS a human society! The programmers are the humans; the programs are their extensions.

2.14  Users are Programmers

To program: to influence the future behavior of the system.

Intentional vs extensional definitions.

Continuum between ``Beginner'' programmer vs ``Advanced programmer'' vs ``Programmer demi-god''. Some will never program. Some will stay rookies forever. Some will develop good programming skills in very specific domains. Etc.

2.15  The Long Reach of the Programmer

Two scales in a computing system. Macro-scale: human minds; heuristic, evolutive. Micro-scale: automated computer programs; algorithmic, constructive.

eager stratification

Artificial barriers due to proprietary software. See other article MPFAS.

Historical barriers due to low resource availability at the time systems were designed: low-level systems.

universal system vs glue languages

managing complexity vs multiplying services

more than one way to do things? ultimately the same

2.16  Authority

Most complex enough systems are structured around a kernel, with ``system services'' on the one hand, and ``user applications'' on the other. This centralized structuration must thus be some kind of a natural concept. But why? And what are the natural attributes of a kernel? What can or cannot, must or must not, be performed by users or by the kernel ?

The principal characteristic of kernels is authority. The authority to take effective decisions that affect unwilling actors. A system programmed by a single man, by a tight team, or more generally by a one coordinated entity, doesn't need a separation of computing systems between system and user spaces; it can be just a project for a conceptually ``monolithic'' computer system. The necessity of a well-separated ``kernel'' appears as multiple people, who are not otherwise much coordinated, need to cooperate.

Monitor, Runtime, Compiler, Verifier, Trust Broker.

3  Languages and Expressiveness

3.1  Computer Languages

Firstly, let's settle what we call a "computer language".

A language is just any means by which humans, computers, or any active member of a dynamical system, can communicate information. Computer languages are languages used to vehiculate information about what the computer should do; any media for exchanging information is a language.

Now, this makes a language even out of point-and-click-on-window-system, or out of a bitstream protocol.

So what? Why has a language got to use ASCII symbols or a written alphabet at all? People use sounds, the deaf use their hands, various animals use a lot of different ways to communicate, computers use electrical signals. What makes the language is the structure of the information communicated, not the media used for this communication to happen.

Written or spoken english, though they have differences, are both english, and recognizable as such; what makes english is its structures, its patterns, not the media used to communicate those patterns. These patterns might be represented by things as physically foreign to each other as vibrations of the air (when one talks), or digital electrical signals on a silicon chip (when your computer text such as this very article you're reading).

Of course, symbol-based languages are simpler to implement on today's computers, but that's only a historical dependency, that may evolve and eventually disappear.

And of course not all languages are equivalent. Surely the language used to communicate with a washing machine is much more limited than what we use to talk to humans. Still, there is no reason why not to call it a language.

As with Operating Systems, the problem is not to define the concept of a computer language, but to identify what characteristics it should have to maximize its utility.

So what kind of structure shall a computer language have? What makes a language structure better or more powerful than another? That's what we'll have to inspect.

3.2  Goal of a computer language

[Rename that to "Computer Language Utility"?]

It should stressed that computer languages have nothing to do with finished, static "perfect" computer programs: those can have been written in any language, preferably a portable one (for instance, any ANSI supported language, i.e. most probably the largely supported "C", even if I'd then personally prefer FORTH or Scheme). If all interesting things already had been said and understood, and all ever needed programs already run satisfactorily on current machines, there would be no more need for a language; but there are infinitely many interesting things, and only finitely many things said and understood, so a language will always be needed, and no finite language (a grammarless dictionary) will ever be enough.

Much like an operating system, being useful not as a static library, but as a frame for dynamic computing, computer languages have to do with programming, with modifyings programs, creating new programs, not just watching existing ones; that is, computer languages are for communicating, be it with other people or a further self. That is languages are protocols to store and retrieve documents in such a way that the meaning of a document, its dynamical properties, its propension towards evolution and modification, etc, be preserved.

Thus, the qualities of a (programming) language do not lie only in what can eventually be done as a static program with the language; or more precisely, assuming we have all the needed "library" routines to access the hardware we need, all Turing-equivalent languages are equally able to describe any static program. These qualities do not lie in the efficiency of a straightforward implementation either, as a good "optimizing" compiler can always be achieved later, and speed critical routines can be included in libraries (i.e. if you really need a language, then you won't be a beginner for a long time at this language).

The qualities of a language lie in the easiness to express new concepts, and to modify existing routines.

With this in mind, a programming language is better than another if it is easier for a human to write a new program or to modify an existing program, or of course to reuse existing code (which is some extension to modifying code); a language is better, if sentences of equal meaning are shorter, or if just if better accuracy is reachable.

3.3  Reuse versus Rewrite

We evaluated a computing system's utility by the actual time saved by using them on the long run, as compared to using other tools instead, or not using any. Now, personal expediency suggests that people keep using the same tools as they always did, however bad they may be, and add functionalities as they are needed, because learning and installing new tools is costly. But this leads to obsolete tools grown with bogus bulging features, that provide tremendous debugging and maintenance costs. It results in completely insecure software, so no one trusts any one else's software, and no one wants to reuse other people's software, all the more if one has to pay.

For the problem is that, with existing tools, 99.99% of programming time throughout the world is spent doing again and again the same basic things that have been done hundreds of times before or elsewhere. It is common to hear (or read) that most programmers spend their time reinventing the wheel, or desesperately trying to adapt existing wheels to their gear. Of course, you can't escape asking students and newbies to repeat and learn what their elders did, so they can understand it and interiorize the constraints of computing. The problem is that today's crippled tools and closed development strategies make learning difficult and reuse even more difficult, secure reuse being just impossible. Thus people spend most of their time writing again and again new versions of earlier works, nothing really worth the time they spend, nothing original, only so they can be sure they know what it does, and it provides correctly the particular feature they need that couldn't be done before, or at least not exactly. Even then, they seldom manage to have it do what they want.

Now, after all, you may argue that such a situation creates jobs, so is desirable; so why bother ?

First of all, there is plenty of useful work to do on Earth, so time and money saved by not repeating things while programming can be spent on many many other activities (if you really can't find any, call me, I'll show you). Physical resources are globally limited, so wasting them at doing redundant work is unacceptably harmful.

Paying people to dig holes and fill them back just to create jobs, as suggested by despicable economists like J.M. Keynes, is of utmost stupidity. Else, we might encourage random killing, as it decreases unemployment among potential victims, and increases employment among morticians, cops, and journalists. If Maynard Keynes' argument holds, I particularly recommend suicide to its proponents for the beneficial effect it has on society. See Bastiat's works [1] for a refutation of this myth, more than a hundred years before stupid socialist politicians apply it: maybe spending money to do useless things might have some beneficial aspects, as for example stimulating employment; but their global effect is very harmful, as the money and energy spent by central organs to the limited benefit of a few could have been spent much more usefully for everyone (not forcibly by a central organ at all), as there are so many useful things to be done, be it only to prepare against natural catastrophes, not to talk about human curses. That useless work policy is taking a lot from everyone to give little to a few.

Now, rewriting is a serious problem for everyone. To begin with, rewriting is a loss of time, that make programming delays quite longer, thus is very costly. More costly even is the fact that rewriting is an error prone operation and anytime during a rewrite, one may introduce errors very difficult to trace and remove (if need be, one may recall the consequences of computer failures in space ships, phone nets, planes). Reuse of existing data accross software rewrites, and communication of data between different software proves being of exorbitant cost. The most costly aspect of rewriting may also be the fact that any work has a short lifespan, and will have to be rewritten entirely from scratch whenever a new problem arises; thus programming investment cost is high, and software maintenance is of high cost and low quality. And it is to be considered that rewriting is an ungrateful work that disheartens programmers, which has an immeasurably negative effect on programmer productivity and work quality, while wasting their (programming or other) talents. Last but not least, having to rewrite from scratch creates an limit to software quality, that is, no software can be better than what one man can program during one life.

Rewrite is waste of shared resources by lack of communication. And all the argument is about that: not communicating is harmful; any good the system should encourage communication. Now, even when current operating systems greatly limit communication of computer code, they happily do not prevent humans to communicate informal ideas of computer code. This is how we could get where we are.

Therefore, it will now be assumed as proven that code rewriting is a really bad thing, and that we thus want the opposite: software reuse, software sharing.

We could have arrived at the same conclusion just with this simple argument: if some software is really useful (considering the general interest), then it must be used many, many times, by many different people, unless it is some kind of computation with a definitive answer that concerns everybody (which is difficult to conceive: some software that would solve a metaphysical or historical problem!). Thus, useful software, least it be some kind of very unique code, is to be reused countless times. That's why to be useful, code must be very easy to reuse.

It will be showed that such reuse is what the "Object-Orientation" slogan is all about, and what it really means when it means anything. But reuse itself introduces new problems that have to be solved before reuse can actually be possible, problems as we already saw, of trust: how can one trust software from someone else? How can one reuse software without spreading errors from reused software, without introducing errors due to misunderstanding or misadaptation of old code, and without having software obsolescence? We'll see what are possible reuse techniques, and how they cope with these problems.

3.4  Copying Code

The first and the simplest way to reuse code is just the "copy-paste" method: the human user just copies some piece of code, and pastes it in a new context, then modifies it to fit a new particular purpose.

This is really like copying whole chapters of a book, and changing a names to have it fit a new context; this method has got many flaws and lacks, and we can both moral and economically object to it.

First of all, copying is a tedious and thus error-prone method: if you have to copy and modify the same piece of code thousands of times, it can prove a long and difficult work, and nothing will prevent you from doing as many mistakes while copying or modifying.

As for the moral or economical objection, it is sometimes considered bad manners to copy other people's code, especially when copyright issues are involved; sometimes code is protected in such a way that one cannot copy it easily (or would be sued for doing that); thus this copy-paste method won't even be legally of humanly possible everytime.

Then, assuming that the previous problems could be solved (which is not obvious at all), there would still be a big problem about code copying: uncontrolled propagation of bugs and lacks of feature accross the system. And this is quite a serious threat to anything like code maintenance; actually, copying code means that any misfeature in the code is copied altogether with intended code. So the paradox of code copying is that bad copying introduces new errors, while good copying spreads existing errors; in any case code copying is an error prone method. Error correction itself is made very difficult, because every copy of the code must be corrected according to its own particular context, while tracking down all existing copies is especially difficult as code will have been modified (else the copy would have been made useless by any macro-defining preprocessor or procedure call in any language). Moreover, if another programmer (or the same programmer some time later) ever wants to modify the code, he may be unable to find all the modified copies.

To conclude, software creation and maintenance is made very difficult, and even impossible, when using copy-paste; thus, this method is definitely bad for anything but exceptional reuse of a small number of mostly identical code in a context where expediency is much more important than long-term utility. That is, copy-paste is good for "hacking" small programs for immediate use; but it's definitely not a method to program code meant to last or to be widely used.

3.5  Having an Extended Vocabulary...

The second easiest, and most common way to reuse code, is to rely on standard libraries. Computer libraries are more like dictionaries and technical references than libraries, but the name stuck. So places where one can find lots of such "libraries" are called repositories.

Using a standard library is easy: look for what you need in the standard library's index, carefully read the manual for the standard code you use, and be sure to follow the instructions.

Unhappily, not everything one needs will be part of a standard library, for standard library include only things that have been established as needed by a large number of persons. Patiently waiting for the functionality one needs to be included in a next version of standard libraries is not a solution, either, because what makes some work useful is precisely what hasn't been done before, so that even if by chance the functionality gets added, it would mean someone else did the useful work in one's place,

..... not everything there are good reasons why before a standard library is available You wait for the function you need to be included in the standard library, and then use it as the manual describes it when it is finally provided.

standards are long to come, and are even longer to be implemented the way they are documented. By that time, you will have needed new not-yet-standard features, and will have had to implement them or to use non-standard dictionaries; when the standard eventually includes your feature, you'll finally have to choose between keeping a non-standard program, that won't be able to communicate with newer packages, or rewriting your program to conform to the standard.

Moreover, this reuse method relies heavily on a central agency for editing revised versions of the standard library. And how could a centralized agency do all the work for everyone to be happy ? Trying to impose reliance on a sole central agency that is communism. Relying only on multiple concurrent hierarchically organized agencies is feudalism. Oneself is the only thing one can ultimately rely upon; and liberalism tells us that only by having the freeer the information interchange between people, the better the system.

It's like vocabulary, culture: you always need people to write dictionaries, encyclopaedias, and reference textbooks; but these people just won't ever provide new knowledge and techniques, they rather settle what everyone already know, thus facilitating communication where people had to translate between several existing ones more easily. You still need other people to create new things: you just can't wait for what you need to be included in the next revision of such reference book; it won't ever be if no one does settle it clearly before it may be considered by a standardization commitee.

Now, these standard dictionaries have a technical problem: the more useful they strive to be, the larger they grow, but the larger they grow, the more difficult it gets to retrieve the right word from its meaning, which is what you want when you're writing. That's why we need some means to retrieve words from their subject, their relationship with other words; thus we need a language to talk about properties of words (perhaps the same), about how words are created, what words are or not in the standard dictionary and will or will not be. And this language will have to evolve too, so a "meta"-library will not be enough.

When vocabularies grow too large, there appear "needle in haystack" problems: though it exists, you can't locate the word you're looking for, because there's no better way to look for it than to cautiously read the entire dictionary until you come to it...

3.6  ... or a Better Grammar

Furthermore, how is a dictionary to be used ? A dictionary does not deal with new words; only old ones. To express non-trivial things, one must do more than just pronounce a one magic word; one must combine words into meaningful sentences. And this is a matter of grammar - the structure of the language - not vocabulary. We could have seen that immediately: standard libraries do not deal with writing new software, but with sharing old software, which is also useful, but comes second, as there must be software before there can be old software. Computer software was not created, but develops from a long tradition. So a library is great for reuse, but actually, a good grammar is essential to use itself, and reuse in particular.

That is, the right thing is not statically having a extended vocabulary, but dynamically having an extended vocabulary; however statically extended, the vocabulary will never be large enough. Thus we need good dynamical way to define new vocabulary. Again, it's a matter of dynamism versus statism. Current OSes suck because of their statism. Dynamically having an extended vocabulary means having dynamic ways to extend the vocabulary, which is a matter of grammar, not dictionary.

Now what does reuse mean for the language grammar ? It means that you can define new words from existing ones, thus creating new contexts, in which you can talk more easily about your particular problems. That is, you must be able to add new words and provide new, extended, dictionaries. To allow the most powerful communication, the language should provide all meaningful means to create new words. To allow multiple people whose vocabularies evolve independently to communicate their ideas, it should allow easy abstraction and manipulation of the context, so that people with different context backgrounds can understand exactly each other's ideas.

Thus we have two basic constructions, that shall be universally available: extracting an object's value in a context (commonly called beta-reduction), and abstracting the context of an object (commonly called lambda-abstraction). A context is made of variables. When you reduce an object, you replace occurences of the variable by its bound value; when abstracting the context, you create an object with occurences of an unbound variable inside, that you may reduce later after having bound the variable. We thus have a third operation, namely function evaluation, that binds an object to a free variable in a context.

For the grammar to allow maximal reuse, just any object shall be abstractible. But what are those objects ?

3.7  Abstraction

.....

The theory of abstractions is called lambda-calculus. There are infinitely many different lambda-calculi, each having its own properties.

Basically, you start with a universe of base objects. ....... Base objects, or zero-order objects... first order ... second order ... nth order ... higher order ... reflectivity ... beware of reflectivity of a sub-language, not the language itself ... syntax control ... .......

.....

(genericity ?)

.....

3.8  Metaprogramming

.....

3.9  Reflection

.....

3.10  Security

We already saw how the one big problem about reusing software is it that when you share the software, you share its good features, but you also share its bugs.

Reuse is good when it saves work, but you can't call that saving work when it makes you spend so much more time tracking bugs, avoiding them, fearing them, trying to prevent their effects, that you would have been better rewriting the software from scratch so you could trust it.

That's why sharable software is useless if it is not also trustworthy software.

Firstly, we must note that this worry about security does not come from software sharing; it is only multiplicated and propagated by software sharing. Even when you "share" code only with your past and future selves, the need arises. The problem is you're never sure that a module you use does what you expect it to. Moreover, to be sure you agree with the module, you must have some means to know what you want, and what the author intended. And this won't warranty that the module works as intended by the author. ......

The first idea that arises is then "programming by contract", that is, every time some piece of code is called, it will first check all the assumptions made on the parameters, and when it returns, the caller will check that the result does fill all the requirements. This may seem simple, but implementing such technique is quite tricky: it means that checking the parameters and results is easy to do, and that you trust the checking code anyway; it also implies that all the necessary information for proper checking is computed, which is loss of space, and that all kind of checking will take place, which is loss of time. The method is thus very costly, and what does it bring ? Well, the program will just detect failure and abort ! Sometimes aborting is ok, when you have time (and money) to call some maintenance service, but sometimes it is not: a plane, a train, a boat, or a spacecraft whose software fail will crash, collide, sink, explode, be lost, or whatever, and won't be able to wait for repairs before it's too late. And even when lives or billion dollars are not involved, any failure can be very costly, at least for the victim, who may be unable to work. That's why security is something important that any operating system should offer support for. Why integrate such support in the OS itself, and not on "higher layers" ? For the very same reasons that reuse had to be integrated to the OS: because else, you would have to use not the system, but a system built on top of it, with all the related problems, and you would have to rely on the double (or bigger multiple, in case of multiple intermediate layers) implementations, that each introduce unsecurity (perhaps even bugs), unadapted semantics, big loss in performance.

......

3.11  Trusting programs

So we just saw techniques to design trustworthy software. Now, how could you be sure they were well used (if at all), unless you did participate to the design using them ? These techniques can only enforce trust to the technician people who have access to the internals of the software. What kind of trust can the user expect from some software s/he purchased ?

Some companies sell support for software, so they shall repair or replace computer systems in case the customer may have problems. Support is fine indeed; support is even needed by anyone seriously using a computer (now which kind of support, it depends on what the customer needs, and what he can afford). But support won't ever replace reliable software. You never can repair all the harm that may result from misdesigned software when used in critical environment: exploding spacecrafts, shutdown phone networks, missed surgical operation, miscomputed bank accounts, blocked factories, all these cost so much that no one can ever pay back. Thus, however important, the computer support one gets is independent from the trustworth of the software one uses.

The computer industry offers no guarantee to its software's reliability. You have to trust them, to trust their programmers and their sellers. But you shouldn't, as their interest is to spend as few money as possible in making their software reliable, as long as you buy it. They may have some ethics that will bind them to design software as reliable as they can; but don't count on ethics to last indefinitely, when there is. The only way to make sure they strive is to have some pressure on them, so that in case they would cheat you, you threaten software vendors to sue them (and long when even possible), or to lead a campaign against buying their products.

The former very hard, when possible at all, and last for years during the which you must feed lawyers, be worried, without being sure to win. The latter means there is fair competition, so you can choose a product that will replace the one that fails; it also means that competing software allow to recover your data from the flawed system, and run on your former hardware. So even competition isn't enough if it's wild and uncontrolled, and vendors can create de facto monopolies on software or hardware compatibility (which they do).

The only reason why you should trust software is that everyone can, and many do, examine, use and test freely the software and its actual or potential competitors, and still keep using it. We shall insist on there being potential competitors, to which you may compare only if the software sources and internal documentation is freely available, which is open development, as compared to development with non-disclosure agreements. This is the one true heart of liberalism.

Now, what if the software you use is too specific to be used and tested by many ? What if there's no way (at reasonable price) to get feedback from the other actual and potential users of the software ? What if you don't have time to choose before you can get enough feedback to make some worthwhile opinion ? In those cases, the liberal theory above won't apply anymore.

3.12  Program proof

As the need of security in computer systems grows, one can't satisfy himself with trusting all the modules one uses, just because other people were (alledgedly) happy with them, or the authors of the modules have a good reputation, or other people bought it but there's no way to get feedback, or (silly idea) one paid a lot for it, or have been promised an "equal" replacement (but no money back for the other loss) in case it fails.

However, trusting a computer system is foremost when lives (or their contents) are involved by the correct behavior of a module.

Thus, providers of computer system modules will have to provide some reliable warranty that their modules cause no harm. They may offer to pay back any harm that may result from bugs (but such harm is seldom measurable). Or they may offer a proof of the correctness of their program.

Test suites are pretty, but not very significant. What are tests in a million cases, when there are multi-zillions of them, or even infinitely many ? Test suites are due to fail.

Computers were born from mathematicians and their theory is largely developped. If computer systems are designed from mathematically simple elements, that have well-known semantics, it may be actually possible to prove that the computer system actually does what it is meant to do.

The advantage of a mathematical proof is that, when done according to the very strict rules of logic, it is as accurate as a comprehensive test, even though such test may be impossible because the number of cases so wondrous (when not infinite) that it would take far longer than the age of the universe to check each one even at the speed of light.

Now, proving a program's correctness is a difficult task, whose complexity grows uncontrollably with the size of the program to prove. This is why the need to use computer systems arises quickly for such proof. Thus, to trust the proof, you must also trust the computer proofchecking program. But this program can be very short and easy to understand; it can also be made publicly available, and be examined, used, tested, by all the computer users and hackers throughout the world, as explained previously, because it is useful to everyone indeed. If those requirements are fulfilled, such program may be really much more reliable than the most reknowned human doing the same job.

Anyway, the simplest are the specifications and proofs, the most reliable they are too. Therefore, programmers ought to use the programming concepts that allow the easiest proofs, such as pure lambda-calculus, as used in a language like like ML. Any kind of thing like side-effects and shared (global) variables should be avoided whenever possible. The language syntax should remain always clear and as localized as possible. As for the efficiency hungry, we recall that however fast to execute, an unreliable program is worthless, while today's compiler technology is ready to translate mathematical abstractions into code that is almost as fast as the unreliable software obtained by the so-called "optimizing" compilers for unsafe languages.

Of course, having program proofs does not mean we should be less careful. If you misspecify what a program must do, and prove the program fulfills the bogus specification, you may have a bogus program; so you must be careful to undertand well what the program is meant to do, and how to express it to the proofchecker. Also, proofs are always founded on assumptions. With wrong assumptions, you can prove anything. So program proofs mean we should always be careful, but we may at last concentrate on the critical parts, and not lose our time verifying details, which computers do much better than us.

Actually, that's what machines, including computers, are all about: having the human concentrate on the essential, and letting the machines do repetitive tasks.
A programming language is low level when its programs require attention to the irrelevant.

-- Alan Perlis

4  No Computer is an Iland

5  Conclusion

The ideas exposed in this article are not new. Since the seventeenth century, political thinkers, economists, physicists, biologists, have discovered them, which led to theories of democracy, liberalism, thermodynamics, darwinism. The unification of these into a same set of principles, under a more general theory of information, is not foreign to the appearance of computer technology, from the early essays of Leibniz on automatas, to Wiener's Cybernetics.

The point of the Tunes project is not to claim to have invented any of these, neither is it to claim to realize anything technologically original. The claim of this article is to consistently acknowledge the validity of these principles in the computer world that is so well suited to experiment them, by its very principle of manipulating information exactly.

The Tunes project will try to provide an initial software frame for reliable distributed information to exist, that is all the more needed that the necessary hardware is already available and underexploited by people following the transient external aspects of tradition instead of its stable roots.

A  Draft

Nota Bene: This section contains many ideas to insert in the text as it is rewritten. The ideas are in no particular order (not even order of chronological appearance), having been put at random places in the file as they came, or were moved from the written text, since late january 1995 when redacting this article began.

A.1  About the whole article

Some of this draft should definitely be moved to other Tunes documentation files, or expanded into independent articles.

A.2  Part I

Part I would:
  1. Show that OS utility lies in its influence on dynamic CS behavior
  2. The OS is not as much the software as the protocols
  3. Show that this influence is in the way the common background allows to increase signal/noise ratio, that is to give meaning to observable data, to provide expressive languages using the obsersable world as substratum
  4. The role of the "kernel" is to provide some central authority as a ultimate resource to arbitrate conflicts and guarantee consistency.
  5. Constraints of an Operating System:
    1. it may contains only a tiny fraction of the total information in the CS, as its information is bounded by what one computer can know, whereas the system is bounded by what N computers can know.
    2. evolves slowly, in a conservative way so that dataflow can rely on it.


  6. (old stuff)
    1. computing is a recent art whose evolution is well-known

    2. multimedia is the latest OS slogan; when we see through this veil of illusion, we find


    3. the trend is toward adding new functions to the OS. and the trend in which they evolve


    4. show that they fail
      1. [u vs p] see what is their approach,
      2. see why it fails


      3. The essence of an OS is no more in a kernel that would supervise all forms of communication between objects, than the essence of civilization lies in a central administration that would supervise all forms of communication between humans. The essence of an OS is in the abstract property of allowing objects to communicate, through any possible decentralized means; it is in its utility as a general context for communication, much as civilization is an intangible set of said or unsaid traditions and rules, that allow humans to rely on each other.

    6. focus on what they should do, not on what they do (what defines a place setting is not its having the shape of a fork or that of a spoon, but its ability to ease lunch activity, that is, its function, not its implementation). (xref to PartII: centralize)
  1. Part I:
    1. (I.10 ?)

      utility -- correlation to static ou dynamic features

      [current OSes] informational basis that gives meaning to the flux of raw information; dynamical structure

    2. (I.11 ?) kernel, centralism, authority

    3. (I.12 ?) The ultimate source of meta(n)-information: Man


  2. Security is being able to devise arbitrary contracts, and have the guarantee that if agreed upon, the contract will be fulfilled.

    Systems that don't allow you to express the contract you want are stupid unsecure systems.

    Systems that do allow you to express the contract you want, but have no way to enforce it (e.g. literate programming) are ineffective unsecure systems.

    Systems that enforce contracts that you don't want are fascist unfree systems.



    1. and only such information can eventually and enrich the whole system. basis of any reliable information upon which new information can be built that will enrich the whole system; when this information eventually settles, it enriches in turn the OS, and can serve as a universal basis for even further enhancements. That is the utility of Operating Systems.

      That's why the power and long-term utility of an OS mustn't be measured according to what the OS does currently allow to do, but according to how easily it can be extended so that more and more people share more and more complex software. That is, the power of an OS is not expressed in terms of services it statically provide, but in terms of services it can dynamically manage; intelligence is expressed not in terms of knowledge, but in terms of evolutivity toward more knowledge. A culture with a deep knowledge but that would prevent or considerably slowdown further innovations, like the ancient chinese civilization, would indeed be quite harmful. An OS providing lots of services, but not allowing its user to evolve would likewise be harmful.

      Utility lies in new, original information; a large body of acquired information is a sign of past utility, but quite independent from current utility.

      Again, we find the obvious analogy with human culture for which the same stands; the analogy is not fallacious at all, as the primary goal of an operating system is allowing humans to communicate with computers more easily to achieve better software. So an operating system is a part of human culture, though a part that involves computers.

      Multiplying the actual services provided by an operating system may be an expedient way to solve computer problems, in the same way that multiplying welfare institutions may be an expedient way to solve the everyday problems of a human system; the progress of the system ultimately means that those services will actually be multiplied in the long run. However, from the point of view of utility, what counts is not any the objective state of the system at any given moment, and its ephemeral advantages, but the dynamic project of the system across time, and its smaller, but growing, long-standing advantages.

      the information in an OS is virtually (not forcibly physically) duplicated at each node. Hence growing the OS for ever more feature is harmful, as it would involve an ever increased waste of resources duplicated at each node, instead of letting each node develop original information in a way adapted to its immediate environment.

      A.3  Users are Programmers

      The only source of information in the UCS that we can directly act upon, hence what counts with respect to utility, is the Humans. Therefore, Operating Systems should structure the Computing System so that the fullest possible human creativity is promoted.

      .....

      The deepest flaw in computer design is this idea that there is a fundamental difference between system programming and usual programming, between usual programming and "mere" using. The previous point shows how false is this conception.

      The truth is any computer user, whether a programming guru or a novice user, is somehow trying to communicate with the machine. The easier the communication, the quicker better larger the work is getting done.

      Of course, there are different kinds of use; actually, there are infinitely many. You can often say that such kind of computer use is much more advanced and technical than such other; but you can never find a clear limit, and that's the important point (in mathematics, we'd say the space of kinds of computing is connected).

      Of course also, any given computer object has been created by some user(s), who programmed it above a given system, and is being used by other (or the same) user(s), who program using it, above the thus enriched system. That is, there are computer object providers and consumers. But anyone can provide some objects and consume other objects; providing objects without using some is unimaginable, while using objects without providing any is pure useless waste. The global opposition between users and programmers that roots the computer industry is thus inadequate; instead, there is a local complementarity between providers and consumers of every kind of objects.

      Some say that common users are too stupid to program; that's only despising them; most of them don't have time and mind to learn all the subtleties of advanced programming; Most of the time, such subtleties shouldn't be really needed, and learning them is thus a waste of time but they often do manually emulate macros, and if shown once how to do it, are very eager to use or even write their own macros or aliases.

      Others fear that encouraging people to use a powerful programming language is the door open to piracy and system crash, and argue that programming languages are too complicated anyway. Well, if the language library has such security holes and cryptic syntax, then it is clearly misdesigned; and if the language doesn't allow the design of a secure, understandable library, then the language itself is misdesigned (e.g. "C"). Whatever was misdesigned, it should be redesigned, amended or replaced (as should be "C"). If you don't want people to cross an invisible line, just do not draw roads that cross the line, write understandable warning signs, then hire an army of guards to shoot at people trying to trespass or walk out of the road. If you're really paranoid, then just don't let people near the line: don't have them use your computer. But if they have to use your computer, then make the line appear, and abandon these ill-traced roads and fascist behavior.

      So as for those who despise higher-order and user-customizability, I shall repeat that there is NO frontier between using and programming. Programming is using the computer while using a computer is programming it. Which does not mean there is no difference between various users-programmers; but creating an arbitrary division in software between "languages" for "programmers" and "interfaces" for mere "users" is asking reality to comply to one's sentences instead of having one's sentences reflect reality: one ends with plenty of unadapted, inefficient, unpowerful tools, stupefies all computer users with a lot of unuseful ill-conceived, similar but different languages, and wastes a considerable lot of human and computer resources, writing the same elementary software again and again.

      A.4  Operating System Kernel

      In traditional OS design, the kernel is some central piece of software through which any communication between first-class system objects is done...

      But this accounts only for centralized design; it appears that what system acknowledge as first-class objects are actually very coarse-grained information concepts, and that a meaningful study of information flow should take into account much finer-grained information, that such system just do no consider at all, hence being unadapted to the actual use that is done of them.

      How does this design generalize to arbitrary OSes? What do OS kernels provide that is essential to all OSes, and what do they do that is costly noise?

      To answer such questions, we must depart from the traditional OS point of view that we know is flawed, and see how are OSes doing, that we recognized as such, that traditional design refuses to consider this way, and what the analogy to human systems lead to.

      Thus, we see that of course, centralization of the information flow through the kernel is not needed: hence, information most often is much more efficiently passed directly from object to object without any intermediate. Also,

      To conclude, we'll say that the kernel is the central authority used to coordinate software components, and solve conflicts, in a computer system.

      A.5  Current state of System software

      It is remarkable that while since their origins, computer hardware have grown in power and speed at a constant exponential rate, system software only slowly evolved in comparison. It does not offer any new tools to master the increasing power of hardware, but only enhancements of obsolete tools, and new "device drivers" to access new kinds of hardware as they appear. System software becomes fatware (a.k.a. hugeware), as it tries to cope differently with all the different users' different but similar problems.

      It is also remarkable that while new standard libraries arise, they do not lead to reduced code size for programs of same functionality, but to enhanced code size for them, so that they take into account all the newly added capabilities.

      As a blatant example of the lack of evolution of system software quality is the fact that the most popular system software in the world (MS-DOS) is a fifteen-year old thing that does not allow the user to do either simple tasks, or complicated ones, thus being a no-operating system, and forces programmers to rewrite low-level tasks everytime they develop any non-trivial program, while not even providing trivial programs.

      This industry-standard has always been designed as a least sub-system possible for the Unix system, which itself is a least subsystem of Multics made of features assembled in undue ways on top of only two basic abstractions, the raw sequence of bytes ("files"), and the ASCII character string.

      As these abstractions proved not enough to express adequately the semantics of new hardware and software that appeared, Unix has had a huge number of ad-hoc "system calls" added, to extend the operating system in special ways. Hence, what was an OS meant to fit the tiny memory of then available computers, has grown into a tentaculous monster with ever growing pseudopods, that wastes without counting the resources of the most powerful workstations. And this, renamed as POSIX, is the new industry standard OS to come, whose promoters crown as the traditional, if not natural, way to organize computations.

      Following the same tendency, widespread OSes are found upon a large number of human interface services, video and sound. This is known as the "multi-media" revolution, which basically just means that your computer produces high-quality graphics and sound. All that is fine: it means that your system software grants you access to your actual hardware, which is the least it can do!

      But software design, a.k.a. programming, is not made simpler for that; it is even made quite harder: while a lot of new primitives are made available, no new combinatorials are provided that could ease their manipulation; worse, even the old reliable software is made obsolete by the new interface conventions. Thus you have computers with beautiful interfaces that waste lots of resources, but that cannot do anything new; to actually do interesting things, you must constantly rewrite everything from almost scratch, which leads to very expensive low-quality slowly-evolving software.

      A.6  An Ancien Régime

      [= most of the energy is wasted in a fight for supremacy between monopolies]

      The current computing world is anything but a failure. So many things are now done by computers that relieve people from stupid repetitive work, and so many things are done that just could not be done without computers, that nobody can deny the utility of today's computers relatively to the implicit reference being the absence of computers.

      But somehow, programming techniques are finding their limits as programs reach the size beyond which no human can fully understand the whole of one. And the current OS trend, by generating code bloat, makes those limits reached much faster than they should, while wasting lots of human resources. It is thus necessary to see why current programming techniques lead to code bloat, and how this trend can be slowed down, set back, or reversed.

      Of course, we easily can diagnose about the "multimedia revolution" that it stems from the cult of external look, of the container, to the detriment of the internal being, the contents; such cult is inevitable whenever non-technical people have to choose without any objective guide among technical products, so that the most seductive wins. So this general phenomenon, which goes beyond the scope of this paper, though it does harm to the computing world, and must be fought there as well as elsewhere, is a sign that computing spreads and benefits to a large public; by its very nature, it may waste a lot of resources, but it won't compromise the general utility of operating systems. Hence, if there is some flaw to find in current OS design, it must be looked for deeper.

      Computing is a recent art, and somehow, it left its Antiquity for its Ancien Régime. Its world is dominated by a few powerful companies, that wage a perpetual war to each other, where At the same time, there are heavens where computists can grow in art while freely benefitting ..... isn't the deeply rooted .....

      Actually, the ..... the informational status of the computer world is quite remindful of the political status of .....

      A.7  Computists

      A.8  Contents of an Operating System

      What are the characteristic components of an operating system ?

      Well, firstly, we may like to find some underlying structure of mind in terms of which everything else would be expressed, and that we would call "kernel". Most existing OSes, at least, all those software that claim to be an OS, are conceived this way. Then, over this "kernel" that statically provides most basic services, "standard libraries" and "standard programs" are provided that should be able to do all that is needed in the system, that would contain all the system knowledge, while standard "device drivers" would provide complementary access to the external world.

      We already see why such a conception may fail: it could perhaps be perfect for a finite unextensible static system, but we feel it may not be able to express a dynamically evolving system. However, a solid argument why it shouldn't be able to do so is not so obvious at first sight. The key is that like any complex enough systems, like human beings, computer have some self-knowledge. The fact becomes obvious when you see a computer being used as a development system for programs that will run on the same computer. And indeed the exceptions to that "kernel" concept are those kind of dynamic languages and systems that we call "reflective", that is, that allow dynamical manipulation of the language constructs themselves: FORTH and LISP (or Scheme) development systems, which can be at the same time editors, interpreters, debuggers and compilers, even if those functionalities are available separately, are such reflective systems. so there is no "kernel" design, but rather an integrated OS.

      And then, we see that if the system is powerful enough (that is, reflective), any knowledge in the system can be applied to the system itself; any knowledge is also self-knowledge; so it can express system structure. As you discover more knowledge, you also discover more system structure, perhaps better structure than before, and certainly structure that is more efficiently represented directly than through stubborn translation to those static kernel constructs. So you can never statically settle once and for all the structure of the system without ampering the system's ability to evolve toward a better state; any structure that cannot adapt, even those you trust the most, may eventually (though slowly) become a burden as new meta-knowledge is available. Even if it actually won't, you can never be sure of it, and can expect only refutation, never confirmation of any such assumption.

      The conclusion to this is that you cannot truly separate a "kernel" from a "standard library" or from "device drivers"; in a system that works properly, all have to be integrated into the single concept, the system itself as a whole. Any clear cut distinction inside the system is purely arbitrary, and harmful if not done due to strong reasons of necessity.

      A.9  Toward a Unified System

      From what was previously said, what can we deduce about how an OS should be behaved for real utility ?

      Well, we have seen that an OS' utility is not defined in terms of static behavior, or standard library functionality; that it should be optimally designed for dynamic extensibility, that it shall provide a unified interface to all users, without enforcing arbitrary layers (or anything arbitrary at all). That is, an OS should be primarily open and rational.

      But then, what kind of characteristics are these ? They are features of a computing language. We defined an OS by its observational semantics, and thus logically ended into a good OS being defined by a good way to communicate with it and have it react.

      People often boast about their OS being "language independent", but what does it actually mean ? Any powerful-enough (mathematicians say universal/Turing-equivalent) computing system is able to emulate any language, so this is no valid argument. Most of the time, this brag only means that they followed no structured plan as for their OS semantics, which will lead to some horrible inconsistent interface, or voluntarily limited their software to interface with the least powerful language.

      So before we can say how an OS should be, we must study computer languages, what they are meant to, how to compare them, how they should be or not.Comparing computers and cars:
      1. people say that computers, like cars, should have everything done by the machine, with the user never having to modify anything.
      2. but cars are rarely creative objects Most people use cars to move from some place to another, which they don't consider as a piece of art, as a work they produce. They rather feel it's some inevitable noise, that should be reduced as much as possible.
      3. cars are merely tools to relieve people from the burden of displacement, and even then, we don't forbid people from repairing their car themselves, or adding something to it, or making it. Of course, there are laws about how cars should or should not be done, that these persons should follow like all manufacturers, for security reasons.
      4. Thus, in so far as computers are tools that people are not developing, everything should be made to relieve people from the hassle of using the computer, to hide all the nasty details, to provide everything possible to make their daily computer usage easy and secure, fool-proof, etc, to the detriment of raw performance, and even of some "liberties" that bring only chaos (like the liberty to drive on either side of the road would be).
      5. This is a sign that Computing as a project evolves, and the obtained computerware are objects that this project leaves behind it; the more advanced the project, the more elaborate these objects indeed.
      6. Now, information technology, under its particular form of computers as well as all of its forms, is precisely not a complete project, but a project in continuous development.
      7. Surely, people should not have to worry about c