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完成翻译：20181014 How Lisp Became God-s Own Programming Language
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How Lisp Became God's Own Programming Language
======
When programmers discuss the relative merits of different programming languages, they often talk about them in prosaic terms as if they were so many tools in a tool belt—one might be more appropriate for systems programming, another might be more appropriate for gluing together other programs to accomplish some ad hoc task. This is as it should be. Languages have different strengths and claiming that a language is better than other languages without reference to a specific use case only invites an unproductive and vitriolic debate.
But there is one language that seems to inspire a peculiar universal reverence: Lisp. Keyboard crusaders that would otherwise pounce on anyone daring to suggest that some language is better than any other will concede that Lisp is on another level. Lisp transcends the utilitarian criteria used to judge other languages, because the median programmer has never used Lisp to build anything practical and probably never will, yet the reverence for Lisp runs so deep that Lisp is often ascribed mystical properties. Everyone’s favorite webcomic, xkcd, has depicted Lisp this way at least twice: In [one comic][1], a character reaches some sort of Lisp enlightenment, which appears to allow him to comprehend the fundamental structure of the universe. In [another comic][2], a robed, senescent programmer hands a stack of parentheses to his padawan, saying that the parentheses are “elegant weapons for a more civilized age,” suggesting that Lisp has all the occult power of the Force.
Another great example is Bob Kanefsky’s parody of a song called “God Lives on Terra.” His parody, written in the mid-1990s and called “Eternal Flame”, describes how God must have created the world using Lisp. The following is an excerpt, but the full set of lyrics can be found in the [GNU Humor Collection][3]:
> For God wrote in Lisp code
> When he filled the leaves with green.
> The fractal flowers and recursive roots:
> The most lovely hack I’ve seen.
> And when I ponder snowflakes,
> never finding two the same,
> I know God likes a language
> with its own four-letter name.
I can only speak for myself, I suppose, but I think this “Lisp Is Arcane Magic” cultural meme is the most bizarre and fascinating thing ever. Lisp was concocted in the ivory tower as a tool for artificial intelligence research, so it was always going to be unfamiliar and maybe even a bit mysterious to the programming laity. But programmers now [urge each other to “try Lisp before you die”][4] as if it were some kind of mind-expanding psychedelic. They do this even though Lisp is now the second-oldest programming language in widespread use, younger only than Fortran, and even then by just one year. Imagine if your job were to promote some new programming language on behalf of the organization or team that created it. Wouldn’t it be great if you could convince everyone that your new language had divine powers? But how would you even do that? How does a programming language come to be known as a font of hidden knowledge?
How did Lisp get to be this way?
![Byte Magazine Cover, August, 1979.][5]
The cover of Byte Magazine, August, 1979.
### Theory A: The Axiomatic Language
John McCarthy, Lisp’s creator, did not originally intend for Lisp to be an elegant distillation of the principles of computation. But, after one or two fortunate insights and a series of refinements, that’s what Lisp became. Paul Graham—we will talk about him some more later—has written that, with Lisp, McCarthy “did for programming something like what Euclid did for geometry.” People might see a deeper meaning in Lisp because McCarthy built Lisp out of parts so fundamental that it is hard to say whether he invented it or discovered it.
McCarthy began thinking about creating a language during the 1956 Darthmouth Summer Research Project on Artificial Intelligence. The Summer Research Project was in effect an ongoing, multi-week academic conference, the very first in the field of artificial intelligence. McCarthy, then an assistant professor of Mathematics at Dartmouth, had actually coined the term “artificial intelligence” when he proposed the event. About ten or so people attended the conference for its entire duration. Among them were Allen Newell and Herbert Simon, two researchers affiliated with the RAND Corporation and Carnegie Mellon that had just designed a language called IPL.
Newell and Simon had been trying to build a system capable of generating proofs in propositional calculus. They realized that it would be hard to do this while working at the level of the computer’s native instruction set, so they decided to create a language—or, as they called it, a “pseudo-code”—that would help them more naturally express the workings of their “Logic Theory Machine.” Their language, called IPL for “Information Processing Language”, was more of a high-level assembly dialect then a programming language in the sense we mean today. Newell and Simon, perhaps referring to Fortran, noted that other “pseudo-codes” then in development were “preoccupied” with representing equations in standard mathematical notation. Their language focused instead on representing sentences in propositional calculus as lists of symbolic expressions. Programs in IPL would basically leverage a series of assembly-language macros to manipulate and evaluate expressions within one or more of these lists.
McCarthy thought that having algebraic expressions in a language, Fortran-style, would be useful. So he didn’t like IPL very much. But he thought that symbolic lists were a good way to model problems in artificial intelligence, particularly problems involving deduction. This was the germ of McCarthy’s desire to create an algebraic list processing language, a language that would resemble Fortran but also be able to process symbolic lists like IPL.
Of course, Lisp today does not resemble Fortran. Over the next few years, McCarthy’s ideas about what an ideal list processing language should look like evolved. His ideas began to change in 1957, when he started writing routines for a chess-playing program in Fortran. The prolonged exposure to Fortran convinced McCarthy that there were several infelicities in its design, chief among them the awkward `IF` statement. McCarthy invented an alternative, the “true” conditional expression, which returns sub-expression A if the supplied test succeeds and sub-expression B if the supplied test fails and which also only evaluates the sub-expression that actually gets returned. During the summer of 1958, when McCarthy worked to design a program that could perform differentiation, he realized that his “true” conditional expression made writing recursive functions easier and more natural. The differentiation problem also prompted McCarthy to devise the maplist function, which takes another function as an argument and applies it to all the elements in a list. This was useful for differentiating sums of arbitrarily many terms.
None of these things could be expressed in Fortran, so, in the fall of 1958, McCarthy set some students to work implementing Lisp. Since McCarthy was now an assistant professor at MIT, these were all MIT students. As McCarthy and his students translated his ideas into running code, they made changes that further simplified the language. The biggest change involved Lisp’s syntax. McCarthy had originally intended for the language to include something called “M-expressions,” which would be a layer of syntactic sugar that made Lisp’s syntax resemble Fortran’s. Though M-expressions could be translated to S-expressions—the basic lists enclosed by parentheses that Lisp is known for— S-expressions were really a low-level representation meant for the machine. The only problem was that McCarthy had been denoting M-expressions using square brackets, and the IBM 026 keypunch that McCarthy’s team used at MIT did not have any square bracket keys on its keyboard. So the Lisp team stuck with S-expressions, using them to represent not just lists of data but function applications too. McCarthy and his students also made a few other simplifications, including a switch to prefix notation and a memory model change that meant the language only had one real type.
In 1960, McCarthy published his famous paper on Lisp called “Recursive Functions of Symbolic Expressions and Their Computation by Machine.” By that time, the language had been pared down to such a degree that McCarthy realized he had the makings of “an elegant mathematical system” and not just another programming language. He later wrote that the many simplifications that had been made to Lisp turned it “into a way of describing computable functions much neater than the Turing machines or the general recursive definitions used in recursive function theory.” In his paper, he therefore presented Lisp both as a working programming language and as a formalism for studying the behavior of recursive functions.
McCarthy explained Lisp to his readers by building it up out of only a very small collection of rules. Paul Graham later retraced McCarthy’s steps, using more readable language, in his essay [“The Roots of Lisp”][6]. Graham is able to explain Lisp using only seven primitive operators, two different notations for functions, and a half-dozen higher-level functions defined in terms of the primitive operators. That Lisp can be specified by such a small sequence of basic rules no doubt contributes to its mystique. Graham has called McCarthy’s paper an attempt to “axiomatize computation.” I think that is a great way to think about Lisp’s appeal. Whereas other languages have clearly artificial constructs denoted by reserved words like `while` or `typedef` or `public static void`, Lisp’s design almost seems entailed by the very logic of computing. This quality and Lisp’s original connection to a field as esoteric as “recursive function theory” should make it no surprise that Lisp has so much prestige today.
### Theory B: Machine of the Future
Two decades after its creation, Lisp had become, according to the famous [Hacker’s Dictionary][7], the “mother tongue” of artificial intelligence research. Early on, Lisp spread quickly, probably because its regular syntax made implementing it on new machines relatively straightforward. Later, researchers would keep using it because of how well it handled symbolic expressions, important in an era when so much of artificial intelligence was symbolic. Lisp was used in seminal artificial intelligence projects like the [SHRDLU natural language program][8], the [Macsyma algebra system][9], and the [ACL2 logic system][10].
By the mid-1970s, though, artificial intelligence researchers were running out of computer power. The PDP-10, in particular—everyone’s favorite machine for artificial intelligence work—had an 18-bit address space that increasingly was insufficient for Lisp AI programs. Many AI programs were also supposed to be interactive, and making a demanding interactive program perform well on a time-sharing system was challenging. The solution, originally proposed by Peter Deutsch at MIT, was to engineer a computer specifically designed to run Lisp programs. These Lisp machines, as I described in [my last post on Chaosnet][11], would give each user a dedicated processor optimized for Lisp. They would also eventually come with development environments written entirely in Lisp for hardcore Lisp programmers. Lisp machines, devised in an awkward moment at the tail of the minicomputer era but before the full flowering of the microcomputer revolution, were high-performance personal computers for the programming elite.
For a while, it seemed as if Lisp machines would be the wave of the future. Several companies sprang into existence and raced to commercialize the technology. The most successful of these companies was called Symbolics, founded by veterans of the MIT AI Lab. Throughout the 1980s, Symbolics produced a line of computers known as the 3600 series, which were popular in the AI field and in industries requiring high-powered computing. The 3600 series computers featured large screens, bit-mapped graphics, a mouse interface, and [powerful graphics and animation software][12]. These were impressive machines that enabled impressive programs. For example, Bob Culley, who worked in robotics research and contacted me via Twitter, was able to implement and visualize a path-finding algorithm on a Symbolics 3650 in 1985. He explained to me that bit-mapped graphics and object-oriented programming (available on Lisp machines via [the Flavors extension][13]) were very new in the 1980s. Symbolics was the cutting edge.
![Bob Culley's path-finding program.][14] Bob Culley’s path-finding program.
As a result, Symbolics machines were outrageously expensive. The Symbolics 3600 cost $110,000 in 1983. So most people could only marvel at the power of Lisp machines and the wizardry of their Lisp-writing operators from afar. But marvel they did. Byte Magazine featured Lisp and Lisp machines several times from 1979 through to the end of the 1980s. In the August, 1979 issue, a special on Lisp, the magazine’s editor raved about the new machines being developed at MIT with “gobs of memory” and “an advanced operating system.” He thought they sounded so promising that they would make the two prior years—which saw the launch of the Apple II, the Commodore PET, and the TRS-80—look boring by comparison. A half decade later, in 1985, a Byte Magazine contributor described writing Lisp programs for the “sophisticated, superpowerful Symbolics 3670” and urged his audience to learn Lisp, claiming it was both “the language of choice for most people working in AI” and soon to be a general-purpose programming language as well.
I asked Paul McJones, who has done lots of Lisp [preservation work][15] for the Computer History Museum in Mountain View, about when people first began talking about Lisp as if it were a gift from higher-dimensional beings. He said that the inherent properties of the language no doubt had a lot to do with it, but he also said that the close association between Lisp and the powerful artificial intelligence applications of the 1960s and 1970s probably contributed too. When Lisp machines became available for purchase in the 1980s, a few more people outside of places like MIT and Stanford were exposed to Lisp’s power and the legend grew. Today, Lisp machines and Symbolics are little remembered, but they helped keep the mystique of Lisp alive through to the late 1980s.
### Theory C: Learn to Program
In 1985, MIT professors Harold Abelson and Gerald Sussman, along with Sussman’s wife, Julie Sussman, published a textbook called Structure and Interpretation of Computer Programs. The textbook introduced readers to programming using the language Scheme, a dialect of Lisp. It was used to teach MIT’s introductory programming class for two decades. My hunch is that SICP (as the title is commonly abbreviated) about doubled Lisp’s “mystique factor.” SICP took Lisp and showed how it could be used to illustrate deep, almost philosophical concepts in the art of computer programming. Those concepts were general enough that any language could have been used, but SICP’s authors chose Lisp. As a result, Lisp’s reputation was augmented by the notoriety of this bizarre and brilliant book, which has intrigued generations of programmers (and also become [a very strange meme][16]). Lisp had always been “McCarthy’s elegant formalism”; now it was also “that language that teaches you the hidden secrets of programming.”
It’s worth dwelling for a while on how weird SICP really is, because I think the book’s weirdness and Lisp’s weirdness get conflated today. The weirdness starts with the book’s cover. It depicts a wizard or alchemist approaching a table, prepared to perform some sort of sorcery. In one hand he holds a set of calipers or a compass, in the other he holds a globe inscribed with the words “eval” and “apply.” A woman opposite him gestures at the table; in the background, the Greek letter lambda floats in mid-air, radiating light.
![The cover art for SICP.][17] The cover art for SICP.
Honestly, what is going on here? Why does the table have animal feet? Why is the woman gesturing at the table? What is the significance of the inkwell? Are we supposed to conclude that the wizard has unlocked the hidden mysteries of the universe, and that those mysteries consist of the “eval/apply” loop and the Lambda Calculus? It would seem so. This image alone must have done an enormous amount to shape how people talk about Lisp today.
But the text of the book itself is often just as weird. SICP is unlike most other computer science textbooks that you have ever read. Its authors explain in the foreword to the book that the book is not merely about how to program in Lisp—it is instead about “three foci of phenomena: the human mind, collections of computer programs, and the computer.” Later, they elaborate, describing their conviction that programming shouldn’t be considered a discipline of computer science but instead should be considered a new notation for “procedural epistemology.” Programs are a new way of structuring thought that only incidentally get fed into computers. The first chapter of the book gives a brief tour of Lisp, but most of the book after that point is about much more abstract concepts. There is a discussion of different programming paradigms, a discussion of the nature of “time” and “identity” in object-oriented systems, and at one point a discussion of how synchronization problems may arise because of fundamental constraints on communication that play a role akin to the fixed speed of light in the theory of relativity. It’s heady stuff.
All this isn’t to say that the book is bad. It’s a wonderful book. It discusses important programming concepts at a higher level than anything else I have read, concepts that I had long wondered about but didn’t quite have the language to describe. It’s impressive that an introductory programming textbook can move so quickly to describing the fundamental shortfalls of object-oriented programming and the benefits of functional languages that minimize mutable state. It’s mind-blowing that this then turns into a discussion of how a stream paradigm, perhaps something like today’s [RxJS][18], can give you the best of both worlds. SICP distills the essence of high-level program design in a way reminiscent of McCarthy’s original Lisp paper. The first thing you want to do after reading it is get your programmer friends to read it; if they look it up, see the cover, but then don’t read it, all they take away is that some mysterious, fundamental “eval/apply” thing gives magicians special powers over tables with animal feet. I would be deeply impressed in their shoes too.
But maybe SICP’s most important contribution was to elevate Lisp from curious oddity to pedagogical must-have. Well before SICP, people told each other to learn Lisp as a way of getting better at programming. The 1979 Lisp issue of Byte Magazine is testament to that fact. The same editor that raved about MIT’s new Lisp machines also explained that the language was worth learning because it “represents a different point of view from which to analyze problems.” But SICP presented Lisp as more than just a foil for other languages; SICP used Lisp as an introductory language, implicitly making the argument that Lisp is the best language in which to grasp the fundamentals of computer programming. When programmers today tell each other to try Lisp before they die, they arguably do so in large part because of SICP. After all, the language [Brainfuck][19] presumably offers “a different point of view from which to analyze problems.” But people learn Lisp instead because they know that, for twenty years or so, the Lisp point of view was thought to be so useful that MIT taught Lisp to undergraduates before anything else.
### Lisp Comes Back
The same year that SICP was released, Bjarne Stroustrup published the first edition of The C++ Programming Language, which brought object-oriented programming to the masses. A few years later, the market for Lisp machines collapsed and the AI winter began. For the next decade and change, C++ and then Java would be the languages of the future and Lisp would be left out in the cold.
It is of course impossible to pinpoint when people started getting excited about Lisp again. But that may have happened after Paul Graham, Y-Combinator co-founder and Hacker News creator, published a series of influential essays pushing Lisp as the best language for startups. In his essay [“Beating the Averages,”][20] for example, Graham argued that Lisp macros simply made Lisp more powerful than other languages. He claimed that using Lisp at his own startup, Viaweb, helped him develop features faster than his competitors were able to. [Some programmers at least][21] were persuaded. But the vast majority of programmers did not switch to Lisp.
What happened instead is that more and more Lisp-y features have been incorporated into everyone’s favorite programming languages. Python got list comprehensions. C# got Linq. Ruby got… well, Ruby [is a Lisp][22]. As Graham noted even back in 2001, “the default language, embodied in a succession of popular languages, has gradually evolved toward Lisp.” Though other languages are gradually becoming like Lisp, Lisp itself somehow manages to retain its special reputation as that mysterious language that few people understand but everybody should learn. In 1980, on the occasion of Lisp’s 20th anniversary, McCarthy wrote that Lisp had survived as long as it had because it occupied “some kind of approximate local optimum in the space of programming languages.” That understates Lisp’s real influence. Lisp hasn’t survived for over half a century because programmers have begrudgingly conceded that it is the best tool for the job decade after decade; in fact, it has survived even though most programmers do not use it at all. Thanks to its origins and use in artificial intelligence research and perhaps also the legacy of SICP, Lisp continues to fascinate people. Until we can imagine God creating the world with some newer language, Lisp isn’t going anywhere.
If you enjoyed this post, more like it come out every two weeks! Follow [@TwoBitHistory][23] on Twitter or subscribe to the [RSS feed][24] to make sure you know when a new post is out.
Previously on TwoBitHistory…
> This week's post: A look at Chaosnet, the network that gave us the "CH" DNS class.<https://t.co/dC7xqPYzi5>
>
> — TwoBitHistory (@TwoBitHistory) [September 30, 2018][25]
--------------------------------------------------------------------------------
via: https://twobithistory.org/2018/10/14/lisp.html
作者：[Two-Bit History][a]
选题：[lujun9972][b]
译者：[译者ID](https://github.com/译者ID)
校对：[校对者ID](https://github.com/校对者ID)
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
[a]: https://twobithistory.org
[b]: https://github.com/lujun9972
[1]: https://xkcd.com/224/
[2]: https://xkcd.com/297/
[3]: https://www.gnu.org/fun/jokes/eternal-flame.en.html
[4]: https://www.reddit.com/r/ProgrammerHumor/comments/5c14o6/xkcd_lisp/d9szjnc/
[5]: https://twobithistory.org/images/byte_lisp.jpg
[6]: http://languagelog.ldc.upenn.edu/myl/llog/jmc.pdf
[7]: https://en.wikipedia.org/wiki/Jargon_File
[8]: https://hci.stanford.edu/winograd/shrdlu/
[9]: https://en.wikipedia.org/wiki/Macsyma
[10]: https://en.wikipedia.org/wiki/ACL2
[11]: https://twobithistory.org/2018/09/30/chaosnet.html
[12]: https://youtu.be/gV5obrYaogU?t=201
[13]: https://en.wikipedia.org/wiki/Flavors_(programming_language)
[14]: https://twobithistory.org/images/symbolics.jpg
[15]: http://www.softwarepreservation.org/projects/LISP/
[16]: https://knowyourmeme.com/forums/meme-research/topics/47038-structure-and-interpretation-of-computer-programs-hugeass-image-dump-for-evidence
[17]: https://twobithistory.org/images/sicp.jpg
[18]: https://rxjs-dev.firebaseapp.com/
[19]: https://en.wikipedia.org/wiki/Brainfuck
[20]: http://www.paulgraham.com/avg.html
[21]: https://web.archive.org/web/20061004035628/http://wiki.alu.org/Chris-Perkins
[22]: http://www.randomhacks.net/2005/12/03/why-ruby-is-an-acceptable-lisp/
[23]: https://twitter.com/TwoBitHistory
[24]: https://twobithistory.org/feed.xml
[25]: https://twitter.com/TwoBitHistory/status/1046437600658169856?ref_src=twsrc%5Etfw

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Lisp 是怎么成为上帝的编程语言的
======
当程序员们谈论各类编程语言的相对优势时，他们通常会采用相当平淡的词措，就好像这些语言是一条工具带上的各种工具似的——有适合写操作系统的，也有适合把其它程序黏在一起来完成特殊工作的。这种讨论方式非常合理；不同语言的能力不同。不声明特定用途就声称某门语言比其他语言更优秀只能导致侮辱性的无用争论。
但有一门语言似乎受到和用途无关的特殊尊敬：那就是 Lisp。即使是恨不得给每个说出形如“某某语言比其他所有语言都好”这类话的人都来一拳的键盘远征军们，也会承认Lisp处于另一个层次。 Lisp 超越了用于评判其他语言的实用主义标准，因为普通程序员并不使用 Lisp 编写实用的程序 —— 而且，多半他们永远也不会这么做。然而，人们对 Lisp 的敬意是如此深厚，甚至于到了这门语言会时而被加上神话属性的程度。大家都喜欢的网络漫画合集 xkcd 就至少在两组漫画中如此描绘过 Lisp：[其中一组漫画][1]中，一个人物得到了某种 Lisp 启示，而这好像使他理解了宇宙的基本构架。在[另一组漫画][2]中，一个穿着长袍的老程序员给他的徒弟递了一沓圆括号，说这是“文明时代的优雅武器”，暗示着 Lisp 就像原力那样拥有各式各样的神秘力量。
另一个绝佳例子是 Bob Kanefsky 的滑稽剧插曲，《上帝就在人间》。这部剧叫做《永恒之火》，编写于 1990 年代中期；剧中描述了上帝必然是使用 Lisp 创造世界的种种原因。完整的歌词可以在 [GNU 幽默合集][3]中找到，如下是一段摘抄：
> 因为上帝用祂的 Lisp 代码
> 让树叶充满绿意。
> 分形的花儿和递归的根：
> 我见过的奇技淫巧（hack）之中没什么比这更可爱。
> 当我对着雪花深思时，
> 从未见过两片相同的，
> 我知道，上帝偏爱那一门
> 名字是四个字母的语言。
以下这句话我实在不好在人前说；不过，我还是觉得，这样一种“ Lisp 是奥术魔法”的文化模因实在是有史以来最奇异、最迷人的东西。 Lisp 是象牙塔的产物，是人工智能研究的工具；因此，它对于编程界的俗人而言总是陌生的，甚至是带有神秘色彩的。然而，当今的程序员们开始怂恿彼此，[“在你死掉之前至少试一试 Lisp ”][4]，就像这是一种令人恍惚入迷的致幻剂似的。尽管 Lisp 是广泛使用的编程语言中第二古老的（只比 Fortran 年轻一岁），程序员们也仍旧在互相怂恿。想象一下，如果你的工作是为某种组织或者团队推广一门新的编程语言的话，忽悠大家让他们相信你的新语言拥有神力难道不是绝佳的策略吗？——但你如何能够做到这一点呢？或者，换句话说，一门编程语言究竟是如何变成人们口中“隐晦知识的载体”的呢？
Lisp 究竟是怎么成为这样的？
![Byte 杂志封面,1979年八月。][5] Byte 杂志封面，1979年八月。
### 理论 A ：公理般的语言
Lisp 的创造者 John McCarthy 最初并没有想过把 Lisp 做成优雅、精炼的计算法则结晶。然而，在一两次运气使然的深谋远虑和一系列优化之后， Lisp 的确变成了那样的东西。 Paul Graham —— 我们一会儿之后才会聊到他 —— 曾经这么写，说， McCarthy 通过 Lisp “为编程作出的贡献就像是欧几里得对几何学所做的贡献一般”。人们可能会在 Lisp 中看出更加隐晦的含义——因为 McCarthy 创造 Lisp 时使用的要素实在是过于基础，基础到连弄明白他到底是创造了这门语言、还是发现了这门语言，都是一件难事。
最初， McCarthy 产生要造一门语言的想法，是在 1956 年的达特茅斯人工智能夏季研究项目（Darthmouth Summer Research Project on Artificial Intelligence）上。夏季研究项目是个持续数周的学术会议，直到现在也仍旧在举行；它是此类会议之中最早开始举办的会议之一。 McCarthy 当初还是个达特茅斯的数学助教，而“人工智能”这个词事实上就是他建议举办会议时发明的。在整个会议期间大概有十人参加。他们之中包括了 Allen Newell 和 Herbert Simon ，两名隶属于兰德公司和卡内基梅隆大学的学者。这两人不久之前设计了一门语言，叫做IPL。
当时，Newell 和 Simon 正试图制作一套能够在命题演算中生成证明的系统。两人意识到，用电脑的原生指令集编写这套系统会非常困难；于是他们决定创造一门语言——原话是“伪代码”，这样，他们就能更加轻松自然地表达这台“逻辑理论机器”的底层逻辑了。这门语言叫做IPL，即“信息处理语言” (Information Processing Language) ；比起我们现在认知中的编程语言，它更像是一种汇编语言的方言。 Newell 和 Simon 提到，当时人们开发的其它“伪代码”都抓着标准数学符号不放——也许他们指的是 Fortran；与此不同的是，他们的语言使用成组的符号方程来表示命题演算中的语句。通常，用 IPL 写出来的程序会调用一系列的汇编语言宏，以此在这些符号方程列表中对表达式进行变换和求值。
McCarthy 认为，一门实用的编程语言应该像 Fortran 那样使用代数表达式；因此，他并不怎么喜欢 IPL 。然而，他也认为，在给人工智能领域的一些问题建模时，符号列表会是非常好用的工具——而且在那些涉及演绎的问题上尤其有用。 McCarthy 的渴望最终被诉诸行动；他要创造一门代数的列表处理语言——这门语言会像 Fortran 一样使用代数表达式，但拥有和 IPL 一样的符号列表处理能力。
当然，今日的 Lisp 可不像 Fortran。在会议之后的几年中， McCarthy 关于“理想的列表处理语言”的见解似乎在逐渐演化。到 1957 年，他的想法发生了改变。他那时候正在用 Fortran 编写一个能下象棋的程序；越是长时间地使用 Fortran ， McCarthy 就越确信其设计中存在不当之处，而最大的问题就是尴尬的“ IF ”声明。为此，他发明了一个替代品，即条件表达式“ true ”；这个表达式会在给定的测试通过时返回子表达式 A ，而在测试未通过时返回子表达式 B ，而且，它只会对返回的子表达式进行求值。在 1958 年夏天，当 McCarthy 设计一个能够求导的程序时，他意识到，他发明的“true”表达式让编写递归函数这件事变得更加简单自然了。也是这个求导问题让 McCarthy 创造了 maplist 函数；这个函数会将其它函数作为参数并将之作用于指定列表的所有元素。在给项数多得叫人抓狂的多项式求导时，它尤其有用。
然而，以上的所有这些，在 Fortran 中都是没有的；因此，在1958年的秋天，McCarthy 请来了一群学生来实现 Lisp。因为他那时已经成了一名麻省理工助教，所以，这些学生可都是麻省理工的学生。当 McCarthy 和学生们最终将他的主意变为能运行的代码时，这门语言得到了进一步的简化。这之中最大的改变涉及了 Lisp 的语法本身。最初，McCarthy 在设计语言时，曾经试图加入所谓的“M 表达式”；这是一层语法糖，能让 Lisp 的语法变得类似于 Fortran。虽然 M 表达式可以被翻译为 S 表达式 —— 基础的、“用圆括号括起来的列表”，也就是 Lisp 最著名的特征 —— 但 S 表达式事实上是一种给机器看的低阶表达方法。唯一的问题是，McCarthy 用方括号标记 M 表达式，但他的团队在麻省理工使用的 IBM 026 键盘打孔机的键盘上根本没有方括号。于是 Lisp 团队坚定不移地使用着 S 表达式，不仅用它们表示数据列表，也拿它们来表达函数的应用。McCarthy 和他的学生们还作了另外几样改进，包括将数学符号前置；他们也修改了内存模型，这样 Lisp 实质上就只有一种数据类型了。
到 1960 年，McCarthy 发表了他关于 Lisp 的著名论文，《用符号方程表示的递归函数及它们的机器计算》。那时候，Lisp 已经被极大地精简，而这让 McCarthy 意识到，他的作品其实是“一套优雅的数学系统”，而非普通的编程语言。他之后这么写道，对 Lisp 的许多简化使其“成了一种描述可计算函数的方式，而且它比图灵机或者一般情况下用于递归函数理论的递归定义更加简洁”。在他的论文中，他不仅使用 Lisp 作为编程语言，也将它当作一套用于研究递归函数行为方式的表达方法。
通过“从一小撮规则中逐步实现出 Lisp”的方式，McCarthy 将这门语言介绍给了他的读者。不久之后，Paul Graham 换用更加易读的写法，在短文[《Lisp 之根》][6]（The Roots of Lisp）中再次进行了介绍。在 Graham 的介绍中，他只用了七种基本的运算符、两种函数写法，和几个稍微高级一点的函数（也都使用基本运算符进行定义）。毫无疑问，Lisp 的这种只需使用极少量的基本规则就能完整说明的特点加深了其神秘色彩。Graham 称 McCarthy 的论文为“使计算公理化”的一种尝试。我认为，在思考 Lisp 的魅力从何而来时，这是一个极好的切入点。其它编程语言都有明显的人工构造痕迹，表现为“While”，“typedef”，“public static void”这样的关键词；而 Lisp 的设计却简直像是纯粹计算逻辑的鬼斧神工。Lisp 的这一性质，以及它和晦涩难懂的“递归函数理论”的密切关系，使它具备了获得如今声望的充分理由。
### 理论 B：属于未来的机器
Lisp 诞生二十年后，它成了著名的《黑客词典》中所说的，人工智能研究的“母语”。Lisp 在此之前传播迅速，多半是托了语法规律的福 —— 不管在怎么样的电脑上，实现 Lisp 都是一件相对简单直白的事。而学者们之后坚持使用它乃是因为 Lisp 在处理符号表达式这方面有巨大的优势；在那个时代，人工智能很大程度上就意味着符号，于是这一点就显得十分重要。在许多重要的人工智能项目中都能见到 Lisp 的身影。这些项目包括了 [SHRDLU 自然语言程序][8]（the SHRDLU natural language program），[Macsyma 代数系统][9]（the Macsyma algebra system），和 [ACL2 逻辑系统][10]（the ACL2 logic system）。
然而，在 1970 年代中期，人工智能研究者们的电脑算力开始不够用了。PDP-10 就是一个典型。这个型号在人工智能学界曾经极受欢迎；但面对这些用 Lisp 写的 AI 程序，它的 18 位内存空间一天比一天显得吃紧。许多的 AI 程序在设计上可以与人互动。要让这些既极度要求硬件性能、又有互动功能的程序在分时系统上优秀发挥，是很有挑战性的。麻省理工的 Peter Deutsch 给出了解决方案：那就是针对 Lisp 程序来特别设计电脑。就像是我那[关于 Chaosnet 的上一篇文章][11]所说的那样，这些 Lisp 计算机（Lisp machines)会给每个用户都专门分配一个为 Lisp 特别优化的处理器。到后来，考虑到硬核 Lisp 程序员的需求，这些计算机甚至还配备上了完全由 Lisp 编写的开发环境。在当时那样一个小型机时代已至尾声而微型机的繁盛尚未完全到来的尴尬时期，Lisp 计算机就是编程精英们的“高性能个人电脑”。
有那么一会儿，Lisp 计算机被当成是未来趋势。好几家公司无中生有地出现，追着赶着要把这项技术商业化。其中最成功的一家叫做 Symbolics，由麻省理工 AI 实验室的前成员创立。上世纪八十年代，这家公司生产了所谓的 3600 系列计算机，它们当时在 AI 领域和需要高性能计算的产业中应用极广。3600 系列配备了大屏幕、位图显示、鼠标接口，以及[强大的图形与动画软件][12]。它们都是惊人的机器，能让惊人的程序运行起来。例如，之前在推特上跟我聊过的机器人研究者 Bob Culley，就能用一台 1985 年生产的 Symbolics 3650 写出带有图形演示的寻路算法。他向我解释说，在 1980 年代，位图显示和面向对象编程（能够通过 [Flavors 扩展][13]在 Lisp 计算机上使用）都刚刚出现。Symbolics 站在时代的最前沿。
![Bob Culley 的寻路程序。][14] Bob Culley 的寻路程序。
而以上这一切导致 Symbolics 的计算机奇贵无比。在 1983 年，一台 Symbolics 3600 能卖 111,000 美金。所以，绝大部分人只可能远远地赞叹 Lisp 计算机的威力，和操作员们用 Lisp 编写程序的奇妙技术 —— 但他们的确发出了赞叹。从 1979 年到 1980 年代末，Byte 杂志曾经多次提到过 Lisp 和 Lisp 计算机。在 1979 年八月发行的、关于 Lisp 的一期特别杂志中，杂志编辑激情洋溢地写道，麻省理工正在开发的计算机配备了“大坨大坨的内存”和“先进的操作系统”；他觉得，这些 Lisp 计算机的前途是如此光明，以至于它们的面世会让 1978 和 1977 年 —— 诞生了 Apple II, Commodore PET，和TRS-80 的两年 —— 显得黯淡无光。五年之后，在1985年，一名 Byte 杂志撰稿人描述了为“复杂精巧、性能强悍的 Symbolics 3670”编写 Lisp 程序的体验，并力劝读者学习 Lisp，称其为“绝大数人工智能工作者的语言选择”，和将来的通用编程语言。
我问过 Paul McJones [他在山景（Mountain View）的计算机历史博物馆做了许多 Lisp 的[保存工作][15]]，人们是什么时候开始将 Lisp 当作高维生物的赠礼一样谈论的呢？他说，这门语言自有的性质毋庸置疑地促进了这种现象的产生；然而，他也说，Lisp 上世纪六七十年代在人工智能领域得到的广泛应用，很有可能也起到了作用。当 1980 年代到来、Lisp 计算机进入市场时，象牙塔外的某些人由此接触到了 Lisp 的能力，于是传说开始滋生。时至今日，很少有人还记得 Lisp 计算机和 Symbolics 公司；但 Lisp 得以在八十年代一直保持神秘，很大程度上要归功于它们。
### 理论 C：学习编程
1985 年，两位麻省理工的教授，Harold Abelson 和 Gerald Sussman，外加 Sussman 的妻子，出版了一本叫做《计算机程序的构造和解释》（Structure and Interpretation of Computer Programs）的教科书。这本书用 Scheme（一种 Lisp 方言）向读者们示范如何编程。它被用于教授麻省理工入门编程课程长达二十年之久。出于直觉，我认为 SICP（这是通常而言的标题缩写）倍增了 Lisp 的“神秘要素”。SICP 使用 Lisp 描绘了深邃得几乎可以称之为哲学的编程理念。这些理念非常普适，可以用任意一种编程语言展现；但 SICP 的作者们选择了 Lisp。结果，这本阴阳怪气、卓越不凡、吸引了好几代程序员（还成了一种[奇特的模因][16]）的著作臭名远扬之后，Lisp 的声望也顺带被提升了。Lisp 已不仅仅是一如既往的“McCarthy 的优雅表达方式”；它现在还成了“向你传授编程的不传之秘的语言”。
SICP 究竟有多奇怪这一点值得好好说；因为我认为，时至今日，这本书的古怪之处和 Lisp 的古怪之处是相辅相成的。书的封面就透着一股古怪。那上面画着一位朝着桌子走去，准备要施法的巫师或者炼金术士。他的一只手里抓着一副测径仪 —— 或者圆规，另一只手上拿着个球，上书“eval”和“apply”。他对面的女人指着桌子；在背景中，希腊字母λ漂浮在半空，释放出光芒。
![SICP 封面上的画作][17] SICP 封面上的画作。
说真的，这上面画的究竟是怎么一回事？为什么桌子会长着动物的腿？为什么这个女人指着桌子？墨水瓶又是干什么用的？我们是不是该说，这位巫师已经破译了宇宙的隐藏奥秘，而所有这些奥秘就蕴含在 eval/apply 循环和 Lambda 微积分之中？看似就是如此。单单是这张图片，就一定对人们如今谈论 Lisp 的方式产生了难以计量的影响。
然而，这本书的内容通常并不比封面正常多少。SICP 跟你读过的所有计算机科学教科书都不同。在引言中，作者们表示，这本书不只教你怎么用 Lisp 编程 —— 它是关于“现象的三个焦点：人的心智，复数的计算机程序，和计算机”的作品。在之后，他们对此进行了解释，描述了他们对如下观点的坚信：编程不该被当作是一种计算机科学的训练，而应该是“程序性认识论”的一种新表达方式。程序是将那些偶然被送入计算机的思想组织起来的全新方法。这本书的第一章简明地介绍了 Lisp，但是之后的绝大部分都在讲述更加抽象的概念。其中包括了对不同编程范式的讨论，对于面向对象系统中“时间”和“一致性”的讨论；在书中的某一处，还有关于通信的基本限制可能会如何带来同步问题的讨论 —— 而这些基本限制在通信中就像是光速不变在相对中一样关键。都是些高深难懂的东西。
以上这些并不是说这是本糟糕的书；这本书其实棒极了。在我读过的所有作品中，这本书对于重要的编程理念的讨论是最为深刻的；那些理念我琢磨了很久，却一直无力用文字去表达。一本入门编程教科书能如此迅速地开始描述面向对象编程的根本缺陷，和函数式语言“将可变状态降到最少”的优点，实在是一件让人印象深刻的事。而这种描述之后变为了另一种震撼人心的讨论：某种（可能类似于今日的 [RxJS][18] 的）流范式能如何同时具备两者的优秀特性。SICP 用和当初 McCarthy 的 Lisp 论文相似的方式提纯出了高级程序设计的精华。你读完这本书之后，会立即想要将它推荐给你的程序员朋友们；如果他们找到这本书，看到了封面，但最终没有阅读的话，他们就只会记住长着动物腿的桌子上方那神秘的、根本的、给予魔法师特殊能力的、写着 eval/apply 的东西。话说回来，书上这两人的鞋子也让我印象颇深。
然而，SICP 最重要的影响恐怕是，它将 Lisp 由一门怪语言提升成了必要教学工具。在 SICP 面世之前，人们互相推荐 Lisp，以学习这门语言为提升编程技巧的途径。1979 年的 Byte 杂志 Lisp 特刊印证了这一事实。之前提到的那位编辑不仅就麻省理工的新计算机大书特书，还说，Lisp 这门语言值得一学，因为它“代表了分析问题的另一种视角”。但 SICP 并未只把 Lisp 作为其它语言的陪衬来使用；SICP 将其作为入门语言。这就暗含了一种论点，那就是，Lisp 是最能把握计算机编程基础的语言。可以认为，如今的程序员们彼此怂恿“在死掉之前至少试试 Lisp”的时候，他们很大程度上是因为 SICP 才这么说的。毕竟，编程语言 [Brainfuck][19] 想必同样也提供了“分析问题的另一种视角”；但人们学习 Lisp 而非学习 Brainfuck，那是因为他们知道，前者的那种视角在二十年中都被看作是极其有用的，有用到麻省理工在给他们的本科生教其它语言之前，必然会先教 Lisp。
### Lisp 的回归
在 SICP 出版的同一年，Bjarne Stroustrup 公布了 C++ 语言的首个版本，它将面向对象编程带到了大众面前。几年之后，Lisp 计算机市场崩盘，AI 寒冬开始了。在下一个十年的变革中， C++ 和后来的 Java 成了前途无量的语言，而 Lisp 被冷落，无人问津。
理所当然地，确定人们对 Lisp 重新燃起热情的具体时间并不可能；但这多半是 Paul Graham 发表他那几篇声称 Lisp 是首选入门语言的短文之后的事了。Paul Graham 是 Y-Combinator 的联合创始人和《黑客新闻》(Hacker News)的创始者，他这几篇短文有很大的影响力。例如，在短文[《胜于平庸》][20]（Beating the Averages）中，他声称 Lisp 宏使 Lisp 比其它语言更强。他说，因为他在自己创办的公司 Viaweb 中使用 Lisp，他得以比竞争对手更快地推出新功能。至少，[一部分程序员][21]被说服了。然而，庞大的主流程序员群体并未换用 Lisp。
实际上出现的情况是，Lisp 并未流行，但越来越多 Lisp 式的特性被加入到广受欢迎的语言中。Python 有了列表理解。C# 有了 Linq。Ruby……嗯，[Ruby 是 Lisp 的一种][22]。就如 Graham 在2002年提到的那样，“在一系列常用语言中所体现出的‘默认语言’正越发朝着 Lisp 的方向演化”。尽管其它语言变得越来越像 Lisp，Lisp 本身仍然保留了其作为“很少人了解但是大家都该学的神秘语言”的特殊声望。在 1980 年，Lisp 的诞生二十周年纪念日上，McCarthy写道，Lisp 之所以能够存活这么久，是因为它具备“编程语言领域中的某种近似局部最优”。这句话并未充分地表明 Lisp 的真正影响力。Lisp 能够存活超过半个世纪之久，并非因为程序员们一年年地勉强承认它就是最好的编程工具；事实上，即使绝大多数程序员根本不用它，它还是存活了下来。多亏了它的起源和它的人工智能研究用途，说不定还要多亏 SICP 的遗产，Lisp 一直都那么让人着迷。在我们能够想象上帝用其它新的编程语言创造世界之前，Lisp 都不会走下神坛。
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via: https://twobithistory.org/2018/10/14/lisp.html
作者：[Two-Bit History][a]
选题：[lujun9972][b]
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[a]: https://twobithistory.org
[b]: https://github.com/lujun9972
[1]: https://xkcd.com/224/
[2]: https://xkcd.com/297/
[3]: https://www.gnu.org/fun/jokes/eternal-flame.en.html
[4]: https://www.reddit.com/r/ProgrammerHumor/comments/5c14o6/xkcd_lisp/d9szjnc/
[5]: https://twobithistory.org/images/byte_lisp.jpg
[6]: http://languagelog.ldc.upenn.edu/myl/llog/jmc.pdf
[7]: https://en.wikipedia.org/wiki/Jargon_File
[8]: https://hci.stanford.edu/winograd/shrdlu/
[9]: https://en.wikipedia.org/wiki/Macsyma
[10]: https://en.wikipedia.org/wiki/ACL2
[11]: https://twobithistory.org/2018/09/30/chaosnet.html
[12]: https://youtu.be/gV5obrYaogU?t=201
[13]: https://en.wikipedia.org/wiki/Flavors_(programming_language)
[14]: https://twobithistory.org/images/symbolics.jpg
[15]: http://www.softwarepreservation.org/projects/LISP/
[16]: https://knowyourmeme.com/forums/meme-research/topics/47038-structure-and-interpretation-of-computer-programs-hugeass-image-dump-for-evidence
[17]: https://twobithistory.org/images/sicp.jpg
[18]: https://rxjs-dev.firebaseapp.com/
[19]: https://en.wikipedia.org/wiki/Brainfuck
[20]: http://www.paulgraham.com/avg.html
[21]: https://web.archive.org/web/20061004035628/http://wiki.alu.org/Chris-Perkins
[22]: http://www.randomhacks.net/2005/12/03/why-ruby-is-an-acceptable-lisp/