Richard P. Gabriel
本文章初次發表於 1991 年
Lisp 在過去十年做得還不錯：幾乎完全標準化，建立了商業部分的基礎，達到很高的效率，有好的環境，也可以成功建立應用。可是 Lisp 的社群發展卻沒有這麼的好。在這份文章內我將探討 Lisp 的成功點，失敗點，以及下一步該怎麼做。
Lisp 的環境現在非常好：十年之前 Lisp 還沒有一個標準；最標準的 Lisp 是 InterLisp，可以在 PDP-10 和 Xerox Lisp 機器上運作（有些人說可以在 Vax 上運作，我認為他們有點誇大了）；排名第二標準的是 MacLisp，只能在 PDP-10 機器上運作，但是支援該機器上最多人使用的三種作業系統。排名第三的是 Portable Standard Lisp，可以支援很多種機器，但是很少人願意用。排名第四的是 Scheme，可以在不少機器上運作，但是很少人願意用。
現在我們有 Common Lisp（CL），可以在所有主流機器上運作，支援所有主流作業系統，存在於所有國家。Common Lisp 即將被 ANSI 標準化，有著好的效能，環境也非常好，並且和其他語言與軟體都有很好的整合度。
然而，從商業角度看，Lisp 可以說非常不健康。一直都存在有關 Lisp 在實際應用上被放棄的謠言，而且有時候這些說法是真的。
To some extent the problem is one of perception – there are simply better Lisp delivery solutions than are generally believed to exist and to a disturbing extent the problem is one of unplaced or misplaced resources, of projects not undertaken, and of implementation strategies not activated.
Part of the problem stems from our very dear friends in the artificial intelligence (AI) business. AI has a number of good approaches to formalizing human knowledge and problem solving behavior. However, AI does not provide a panacea in any area of its applicability. Some early promoters of AI to the commercial world raised expectation levels too high. These expectations had to do with the effectiveness and deliverability of expert-system-based applications.
When these expectations were not met, some looked for scapegoats, which frequently were the Lisp companies, particularly when it came to deliverability. Of course, if the AI companies had any notion about what the market would eventually expect from delivered AI software, they never shared it with any Lisp companies I know about. I believe the attitude of the AI companies was that the Lisp companies will do what they need to survive, so why share customer lists and information with them?
Another part of the problem is the relatively bad press Lisp got, sometimes from very respectable publications. I saw an article in Forbes (October 16, 1989) entitled Where Lisp Slipped by Julie Pitta. However, the article was about Symbolics and its fortunes. The largest criticisms of Symbolics in the article are that Symbolics believed AI would take off and that Symbolics mistakenly pushed its view that proprietary hardware was the way to go for AI. There was nothing about Lisp in the article except the statement that it is a somewhat obscure programming language used extensively in artificial intelligence.
It seems a pity for the Lisp business to take a bump partly because Julie thought she could make a cute title for her article out of the name Lisp.
But, there are some real successes for Lisp, some problems, and some ways out of those problems.
1 Lisp 的成功點
如我所說，Lisp 現在的狀態是前所未有的好。我想要回顧一下 Lisp 的成功故事。
A major success is that there is a standard Lisp – Common Lisp. Many observers today wish there were a simpler, smaller, cleaner Lisp that could be standardized, but the Lisp that we have today that is ready for standardization is Common Lisp. This isn’t to say that a better Lisp could not be standardized later, and certainly there should be. Furthermore, like any language, Common Lisp should be improved and changed as needs change.
Common Lisp started as a grassroots effort in 1981 after an ARPA-sponsored meeting held at SRI to determine the future of Lisp. At that time there were a number of Lisps in the US being defined and implemented by former MIT folks: Greenblatt (LMI), Moon and Weinreb (Symbolics), Fahlman and Steele (CMU), White (MIT), and Gabriel and Steele (LLNL). The core of the Common Lisp committee came from this group. That core was Fahlman, Gabriel, Moon, Steele, and Weinreb, and Common Lisp was a coalescence of the Lisps these people cared about.
There were other Lisps that could have blended into Common Lisp, but they were not so clearly in the MacLisp tradition, and their proponents declined to actively participate in the effort because they predicted success for their own dialects over any common lisp that was defined by the grassroots effort. Among these Lisps were Scheme, Interlisp, Franz Lisp, Portable Standard Lisp, and Lisp370.
And outside the US there were major Lisp efforts, including Cambridge Lisp and Le-Lisp. The humble US grassroots effort did not seek membership from outside the US, and one can safely regard that as a mistake. Frankly, it never occurred to the Common Lisp group that this purely American effort would be of interest outside the US, because very few of the group saw a future in AI that would extend the needs for a standard Lisp beyond North America.
Common Lisp was defined and a book published in 1984 called /Common Lisp: the Language/ (CLtL). And several companies sprang up to put Common Lisp on stock hardware to compete against the Lisp machine companies. Within four years, virtually every major computer company had a Common Lisp that it had either implemented itself or private-labeled from a Common Lisp company.
In 1986, X3J13 was formed to produce an ANSI version of Common Lisp. By then it was apparent that there were significant changes required to Common Lisp to clean up ambiguities and omissions, to add a condition system, and to define object-oriented extensions.
After several years it became clear that the process of standardization was not simple, even given a mature language with a good definition. The specification of the Common Lisp Object System (CLOS) alone took nearly two years and seven of the most talented members of X3J13.
It also became apparent that the interest in international Lisp standardization was growing. But there was no heir apparent to Common Lisp. Critics of Common Lisp, especially those outside the US, focused on Common Lisp’s failures as a practical delivery vehicle.
In 1988, an international working group for the standardization of Lisp was formed. That group is called WG16. Two things are absolutely clear: The near-term standard Lisp is Common Lisp; a longer-term standard that goes beyond Common Lisp is desirable.
In 1988, the IEEE Scheme working group was formed to produce an IEEE and possibly an ANSI standard for Scheme. This group completed its work in 1990, and the relatively small and clean Scheme is a standard.
Currently, X3J13 is less than a year away from a draft standard for ANSI Common Lisp; WG16 is stalled because of international bickering; Scheme has been standardized by IEEE, but it is of limited commercial interest.
Common Lisp is in use internationally, and serves at least as a de facto standard until the always contentious Lisp community agrees to work together.
Common Lisp performs well. Most current implementations use modern compiler technology, in contrast to older Lisps, which used very primitive compiler techniques, even for the time. In terms of performance, anyone using a Common Lisp today on almost any computer can expect better performance than could be obtained on single-user PDP-10s or on single-user Lisp machines of mid-1980s vintage. Many Common Lisp implementations have multitasking and non-intrusive garbage collection – both regarded as impossible features on stock hardware ten years ago.
In fact, Common Lisp performs well on benchmarks compared to C. The following table shows the ratio of Lisp time and code size to C time and code size for three benchmarks.
|CPU Time||Code Size|
Tak is a Gabriel benchmark that measures function calling and fixnum arithmetic. Traverse is a Gabriel benchmark that measures structure creation and access. Lexer is the tokenizer of a C compiler and measures dispatching and character manipulation.
These benchmarks were run on a Sun 3 in 1987 using the standard Sun C compiler using full optimization. The Lisp was not running a non-intrusive garbage collector.
It is arguable that modern programming environments come from the Lisp and AI tradition. The first bit-mapped terminals (Stanford/MIT), the mouse pointing device (SRI), full-screen text editors (Stanford/MIT), and windowed environments (Xerox PARC) all came from laboratories engaged in AI research. Even today one can argue that the Symbolics programming environment represents the state of the art.
It is also arguable that the following development environment features originated in the Lisp world:
- Incremental compilation and loading
- Symbolic debuggers
- Data inspectors
- Source code level single stepping
- Help on builtin operators
- Window-based debugging
- Symbolic stack backtraces
- Structure editors
Today’s Lisp environments are equal to the very best Lisp machine environments in the 1970s. Windowing, fancy editing, and good debugging are all commonplace. In some Lisp systems, significant attention has been paid to the software lifecycle through the use of source control facilities, automatic cross-referencing, and automatic testing.
Today Lisp code can coexist with C, Pascal, Fortran, etc. These languages can be invoked from Lisp and in general, these languages can then re-invoke Lisp. Such interfaces allow the programmer to pass Lisp data to foreign code, to pass foreign data to Lisp code, to manipulate foreign data from Lisp code, to manipulate Lisp data from foreign code, to dynamically load foreign programs, and to freely mix foreign and Lisp functions.
The facilities for this functionality are quite extensive and provide a means for mixing several different languages at once.
Lisp has the most powerful, comprehensive, and pervasively object-oriented extensions of any language. CLOS embodies features not found in any other object-oriented language. These include the following:
- Generic functions including multi-methods
- First-class generic functions
- Method combination
- Initialization protocols
- Metaobject protocol
- Integration with Lisp types
看起來 Common Lisp（含 CLOS）會成為第一個標準化的物件導向語言
It is possible to deliver applications written in Lisp. The currently available tools are good but are not yet ideal. These solutions include from removing unused code and data from application, building up applications using only the code and data needed, and producing .o files from Lisp code.
Delivery tools are commercially provided by Lucid, Franz, and Ibuki.
2 Lisp 明顯的失敗點
Too many teardrops for one heart to be crying.
Too many teardrops for one heart to carry on.
You’re way on top now, since you left me,
Always laughing, way down at me.
? & The Mysterians
這個快樂的故事現在卻有著陰鬱的插曲。這個插曲可能源自 AI 竄起的失敗，不過裡面也可能有一些我們該注意的事實。
Common Lisp 和 CLOS 幾乎所有的設計者，包含我，都受到了 MIT／史丹佛風格設計的影響。這個風格的精髓，可以用「做對的事」一句話來概括。對這樣的設計者來說，設計出來的架構一定要同時滿足下面幾點：
- 簡潔 – 設計在實作上和使用介面要簡潔，另外介面簡潔比起實作簡潔更重要一些
- 正確 – 設計在所有考慮到的面向要正確。錯誤的設計是不被允許的
- 一致 – 設計分歧是不被允許的。為了維持設計的一致性，系統架構可以有點不簡潔和有點不完整。一致性和正確性是同等重要的。
- 完整 – 設計應該包含實際上會遇到的各種重要情境。所有合理的情況都應該被考慮到，為了簡潔而犧牲完整度是不被接受的。
我相信多數人會同意這些特點都是好的。這裡我稱呼這種邏輯為 MIT 風格的設計哲學，Common Lisp（含 CLOS）以及 Scheme 的設計與實作可以代表這一種哲學。
- 簡潔 – 設計在實作上和使用介面要簡潔，另外實作簡潔比起使用者介面簡潔要更重要。簡潔是設計中最重要的考量項目。
- 正確 – 設計在所有可觀察到的面向上要正確，不過簡單比起正確要重要一點點。
- 一致 – 設計不能太不一致，不過為了簡潔，可以犧牲掉一部分的一致性。另外為了避免提升實作複雜度或者導致設計不一致，可以放棄處理少見的情況。
- 完整 – 設計應該包含實際上會遇到的各種重要情境。所有合理的情況都應該被考慮到。如果和上述任何特點衝突，可以犧牲設計的完整性。事實上，如果危害到實作的簡潔度，那麼一定要放棄設計的完整性。如果一樣簡潔，那可以為了完整度犧牲一致性，特別是使用介面的一致性。
早期 Unix 和 C 的設計可以代表這一種哲學。這裡我稱呼這種設計方式是紐澤西風格的做法。我刻意用有點諷刺意味的方式形容「壞就是好」的哲學，來說服各位這顯然是一種不好的做法。
不過，我相信即使是這種稻草人版本的說法，「壞就是好」這個哲學還是比起「做對的事」這種哲學有更好的生存特性。紐澤西風格的做法在軟體上是比起 MIT 風格更容易存活的做法。
這裡我重新講一個故事做開頭，這故事顯示 MIT 風格和紐澤西風格的定義是正確的，並且可以看出每個哲學的擁護者都相信自己的哲學是比較好的。
有兩位名人，一個是從 MIT，另一位則是從柏克萊（正在開發 Unix）來的人。兩人正在討論作業系統的問題。MIT 的人很瞭解 ITS（MIT AI 實驗室的作業系統），而且最近正在閱讀 Unix 的程式碼。
他對 Unix 怎麼解決 PC 輸家問題（PC loser-ing problem，或者 Program Counter Lusering problem）很有興趣。PC 輸家問題出現在使用者程式觸發了像是 IO buffers 這類很耗時的系統常駐程式的時候。如果操作過程被中斷了，應該要儲存使用者的程式狀態。
因為系統常駐程式的呼叫通常是單條指令，使用者程式的 PC 沒辦法正確的捕捉程序目前的狀態。系統常駐程式要嘛得退出，要嘛得繼續處理下去。
對的處理方式是退出該程式，並重建使用者程式的 PC 到呼叫系統常駐程式之前，以便在中斷後能重新恢復使用者程序，像是可以重新進入常駐程式，這問題被稱為 PC 輸家問題，因為使用者程式的 PC 被強制進入了「輸家」模式。這裡的輸家是 MIT 的人對使用者的暱稱。
MIT 的人在 Unix 的程式裡沒看到處理這種狀況的部分，所以問紐澤西人這個問題是怎麼處理的。紐澤西人說 Unix 開發者知道這個問題，不過解決方法是系統常駐程式一定會結束，不過當系統常駐程式無法完成動作時，會回傳一個錯誤碼告知呼叫的程式。正確撰寫的使用者程式，必須要檢查常駐程式回傳的錯誤碼，並且決定是否要重新呼叫系統常駐程式。
紐澤西人則說 Unix 的做法是對的，因為 Unix 設計的理念是簡潔，而對的事情則太過複雜了。另外工程師多加一個驗證並重新跑程式並不困難。
MIT 的人點出這樣實作起來確實比較簡單，但是對使用這個系統的工程師來說，介面反而變複雜了。紐澤西人則說這是 Unix 所做出正確的取捨——具體來說，實作的簡潔比起使用者的簡潔要重要得多。
MIT 的人開始嘟囔說需要一個堅強的人才能做出一隻嫩雞（sometimes it takes a tough man to make a tender chicken），不過紐澤西的人沒有理解他的意思（我也不確定我真的理解了）。
現在我想解釋為什麼「壞就是好」比較好了。C 是一個設計來撰寫 Unix 的程式語言，並且其設計邏輯符合紐澤西風格的做法。因此很容易為 C 這個語言撰寫一個堪用的編譯器，然後要求使用 C 開發的工程師撰寫對編譯器容易理解的程式碼。有的人會稱呼 C 只是一個比較華麗的組語而已。
早期的 Unix 和 C 編譯器都有著很簡單的架構，很容易移植，運作起來不太花費效能，而且能提供差不多五成到八成你希望作業系統和程式語言該做到的事情。
有一半的機器效能是低於平均值的（比較小或者比較慢）。Unix 和 C 在這些機器上面運作不會有什麼問題，壞就是好的哲學保證了實作的簡潔是比較重要的，這代表 Unix 和 C 移植到這些機器上時可以運作得很好。使用者也逐漸覺得 Unix 和 C 能滿足五成左右的功能就很不錯了，結果我們就開始到處看到這些系統。現在確實是這樣，不是嗎？
Unix 和 C 是終極的電腦病毒。
用實際案例來解釋，即使 1987 年（四年前）的 Lisp 編譯器已經和現在的 C 編譯器一樣好，想改進 C 編譯器的專家還是遠比想改進 Lisp 編譯器的專家要多。
好消息是 1995 年時，我們會有好的作業系統和程式語言；壞消息是，這些東西會是 Unix 和 C++。
首先，要設計出對的事情，然後花時間設計對的實作方式，最後進行實作。因為這是對的事情， First, the right thing needs to be designed. Then its implementation needs to be designed. Finally it is implemented. Because it is the right thing, it has nearly 100% of desired functionality, and implementation simplicity was never a concern so it takes a long time to implement. It is large and complex. It requires complex tools to use properly. The last 20% takes 80% of the effort, and so the right thing takes a long time to get out, and it only runs satisfactorily on the most sophisticated hardware.
The right thing takes forever to design, but it is quite small at every point along the way. To implement it to run fast is either impossible or beyond the capabilities of most implementors.
上面兩個場景分別對應 Common Lisp 和 Scheme。
The first scenario is also the scenario for classic artificial intelligence software.
The right thing is frequently a monolithic piece of software, but for no reason other than that the right thing is often designed monolithically. That is, this characteristic is a happenstance.
The lesson to be learned from this is that it is often undesirable to go for the right thing first. It is better to get half of the right thing available so that it spreads like a virus. Once people are hooked on it, take the time to improve it to 90% of the right thing.
A wrong lesson is to take the parable literally and to conclude that C is the right vehicle for AI software. The 50% solution has to be basically right, and in this case it isn’t.
But, one can conclude only that the Lisp community needs to seriously rethink its position on Lisp design. I will say more about this later.
2.2 寫好的 Lisp 程式是困難的
Many Lisp enthusiasts believe that Lisp programming is easy. This is true up to a point. When real applications need to be delivered, the code needs to perform well. With C, programming is always difficult because the compiler requires so much description and there are so few data types. In Lisp it is very easy to write programs that perform very poorly; in C it is almost impossible to do that. The following examples of badly performing Lisp programs were all written by competent Lisp programmers while writing real applications that were intended for deployment. I find these quite sad.
This example is a mistake that is easy to make. The programmer here did not declare his arrays as fully as he could have. Therefore, each array access was about as slow as a function call when it should have been a few instructions. The original declaration was as follows:
(proclaim '(type (array fixnum *) *ar1* *ar2* *ar3*))
The three arrays happen to be of fixed size, which is reflected in the following correct declaration:
(proclaim '(type (simple-array fixnum (4)) *ar1*)) (proclaim '(type (simple-array fixnum (4 4)) *ar2*)) (proclaim '(type (simple-array fixnum (4 4 4)) *ar3*))
Altering the faulty declaration improved the performance of the entire system by 20%.
2.2.2 Poor Knowledge of the Implementation The next example is where the implementation has not optimized a particular case of a general facility, and the programmer has used the general facility thinking it will be fast. Here five values are being returned in a situation where the order of side effects is critical:
(multiple-value-prog1 (values (f1 x) (f2 y) (f3 y) (f4 y) (f5 y)) (setf (aref ar1 i1) (f6 y)) (f7 x y))
The implementation happens to optimize multiple-value-prog1 for up to three return values, but the case of five values CONSes. The correct code follows:
(let ((x1 (f1 x)) (x2 (f2 y)) (x3 (f3 y)) (x4 (f4 y)) (x5 (f5 y))) (setf (aref ar1 i1) (f6 y)) (f7 x y) (values x1 x2 x3 x4 x5))
There is no reason that a programmer should know that this rewrite is needed. On the other hand, finding that performance was not as expected should not have led the manager of the programmer in question to conclude, as he did, that Lisp was the wrong language.
2.2.3 FORTRAN 養成的習慣
有些 Common Lisp 編譯器的最佳化和其他編譯器的不同。有時候我們會在程式內看到下面的寫法：
(* -1 <form>)
當然，第一種寫法是從 FORTRAN 的寫法
轉到 Lisp 的結果
Some might find this example hard to believe. This really occurred in some code I’ve seen:
(defun make-matrix (n m) (let ((matrix ())) (dotimes (i n matrix) (push (make-list m) matrix)))) (defun add-matrix (m1 m2) (let ((l1 (length m1)) (l2 (length m2))) (let ((matrix (make-matrix l1 l2))) (dotimes (i l1 matrix) (dotimes (j l2) (setf (nth i (nth j matrix)) (+ (nth i (nth j m1)) (nth i (nth j m2)))))))))
What’s worse is that in the particular application, the matrices were all fixed size, and matrix arithmetic would have been just as fast in Lisp as in FORTRAN.
This example is bitterly sad: The code is absolutely beautiful, but it adds matrices slowly. Therefore it is excellent prototype code and lousy production code. You know, you cannot write production code as bad as this in C.
In the worse-is-better world, integration is linking your .o files together, freely intercalling functions, and using the same basic data representations. You don’t have a foreign loader, you don’t coerce types across function-call boundaries, you don’t make one language dominant, and you don’t make the woes of your implementation technology impact the entire system.
The very best Lisp foreign functionality is simply a joke when faced with the above reality. Every item on the list can be addressed in a Lisp implementation. This is just not the way Lisp implementations have been done in the right thing world.
The virus lives while the complex organism is stillborn. Lisp must adapt, not the other way around. The right thing and 2 shillings will get you a cup of tea.
2.4 非 Lisp 的環境正在迎頭趕上
This is hard to face up to. For example, most C environments – initially imitative of Lisp environments – are now pretty good. Current best C environments have the following:
- Symbolic debuggers
- Data inspectors
- Source code level single stepping
- Help on builtin operators
- Window-based debugging
- Symbolic stack backtraces
- Structure editors
And soon they will have incremental compilation and loading. These environments are easily extendible to other languages, with multi-lingual environments not far behind.
Though still the best, current Lisp environments have several prominent failures. First, they tend to be window-based but not well integrated. That is, related information is not represented so as to convey the relationship. A multitude of windows does not mean integration, and neither does being implemented in the same language and running in the same image. In fact, I believe no currently available Lisp environment has any serious amount of integration.
Second, they are not persistent. They seemed to be defined for a single login session. Files are used to keep persistent data – how 1960s.
Third, they are not multi-lingual even when foreign interfaces are available.
Fourth, they do not address the software lifecycle in any extensive way. Documentation, specifications, maintenance, testing, validation, modification, and customer support are all ignored.
Fifth, information is not brought to bear at the right times. The compiler is able to provide some information, but the environment should be able to generally know what is fully defined and what is partially defined. Performance monitoring should not be a chore.
Sixth, using the environment is difficult. There are too many things to know. It’s just too hard to manage the mechanics.
Seventh, environments are not multi-user when almost all interesting software is now written in groups.
The real problem has been that almost no progress in Lisp environments has been made in the last 10 years.
3 Lisp 可以怎樣大贏
When the sun comes up, I’ll be on top.
You’re right down there looking up.
On my way to come up here,
I’m gonna see you waiting there.
I’m on my way to get next to you.
I know now that I’m gonna get there.
? & The Mysterians
We need to bury our differences at the ISO level and realize that there is a short term need, which must be Common Lisp, and a long term need, which must address all the issues for practical applications.
We’ve seen that the right thing attitude has brought us a very large, complex-to-understand, and complex-to-implement Lisp – Common Lisp that solves way too many problems. We need to move beyond Common Lisp for the future, but that does not imply giving up on Common Lisp now. We’ve seen it is possible to do delivery of applications, and I think it is possible to provide tools that make it easier to write applications for deployment. A lot of work has gone into getting Common Lisp to the point of a right thing in many ways, and there are viable commercial implementations. But we need to solve the delivery and integration problems in spades.
Earlier I characterized the MIT approach as often yielding stillborn results. To stop Common Lisp standardization now is equivalent to abortion, and that is equivalent to the Lisp community giving up on Lisp. If we want to adopt the New Jersey approach, it is wrong to give up on Lisp, because C just isn’t the right language for AI.
It also simply is not possible to dump Common Lisp now, work on a new standard, and then standardize in a timely fashion. Common Lisp is all we have at the moment. No other dialect is ready for standardization.
Scheme is a smaller Lisp, but it also suffers from the MIT approach. It is too tight and not appropriate for large-scale software. At least Common Lisp has some facilities for that.
I think there should be an internationally recognized standard for Common Lisp. I don’t see what is to be gained by aborting the Common Lisp effort today just because it happens to not be the best solution to a commercial problem. For those who believe Lisp is dead or dying, what does killing off Common Lisp achieve but to convince people that the Lisp community kills its own kind? I wish less effort would go into preventing Common Lisp from becoming a standard when it cannot hurt to have several Lisp standards.
On the other hand, there should be a strong effort towards the next generation of Lisp. The worst thing we can do is to stand still as a community, and that is what is happening.
All interested parties must step forward for the longer-term effort.
3.2 Retain the High Ground in Environments
I think there is a mistake in following an environment path that creates monolithic environments. It should be possible to use a variety of tools in an environment, and it should be possible for those who create new tools to be able to integrate them into the environment.
I believe that it is possible to build a tightly integrated environment that is built on an open architecture in which all tools, including language processors, are protocol-driven. I believe it is possible to create an environment that is multi-lingual and addresses the software lifecycle problem without imposing a particular software methodology on its users.
Our environments should not discriminate against non-Lisp programmers the way existing environments do. Lisp is not the center of the world.
Even though Common Lisp is not structured as a kernel plus libraries, it can be implemented that way. The kernel and library routines can be in the form of .o files for easy linking with other, possibly non-Lisp, modules; the implementation must make it possible to write, for example, small utility programs. It is also possible to piggyback on existing compilers, especially those that use common back ends. It is also possible to implement Lisp so that standard debuggers, possibly with extensions, can be made to work on Lisp code.
It might take time for developers of standard tools to agree to extend their tools to Lisp, but it certainly won’t happen until our (exceptional) language is implemented more like ordinary ones.
I believe it is possible to implement a Lisp and surrounding environment which has no discrimination for or against any other language. It is possible using multi-lingual environments, clever representations of Lisp data, conservative garbage collection, and conventional calling protocols to make a completely integrated Lisp that has no demerits.
3.5 Make Lisp the Premier Prototyping Language
Lisp is still the best prototyping language. We need to push this forward. A multi-lingual environment could form the basis or infrastructure for a multi-lingual prototyping system. This means doing more research to find new ways to exploit Lisp’s strengths and to introduce new ones.
Prototyping is the act of producing an initial implementation of a complex system. A prototype can be easily instrumented, monitored, and altered. Prototypes are often built from disparate parts that have been adapted to a new purpose. Descriptions of the construction of a prototype often involve statements about modifying the behavioral characteristics of an existing program. For example, suppose there exists a tree traversal program. The description of a prototype using this program might start out by saying something like
let S1 be the sequence of leaf nodes visited by P on tree T1 and S2 the leaf nodes visited by P on tree T2. Let C be a correspondence between S1 and S2 where f: S1 ! S2 maps elements to corresponding elements.
Subsequent statements might manipulate the correspondence and use f. Once the definition of a leaf node is made explicit, this is a precise enough statement for a system to be able to modify the traversal routine to support the correspondence and f.
A language that describes the modification and control of an existing program can be termed a program language. Program languages be built on one or several underlying programming languages, and in fact can be implemented as part of the functionality of the prototyping environment. This view is built on the insight that an environment is a mechanism to assist a programmer in creating a working program, including preparing the source text. There is no necessary requirement that an environment be limited to working only with raw source text. As another example, some systems comprise several processes communicating through channels. The creation of this part of the system can be visual, with the final result produced by the environment being a set of source code in several languages, build scripts, link directives, and operating system calls. Because no single programming language encompasses the program language, one could call such a language an epi-language.
3.6 下一個 Lisp
I think there will be a next Lisp. This Lisp must be carefully designed, using the principles for success we saw in worse-is-better.
There should be a simple, easily implementable kernel to the Lisp. That kernel should be both more than Scheme – modules and macros – and less than Scheme – continuations remain an ugly stain on the otherwise clean manuscript of Scheme.
The kernel should emphasize implementational simplicity, but not at the expense of interface simplicity. Where one conflicts with the other, the capability should be left out of the kernel. One reason is so that the kernel can serve as an extension language for other systems, much as GNU Emacs uses a version of Lisp for defining Emacs macros.
Some aspects of the extreme dynamism of Common Lisp should be reexamined, or at least the tradeoffs reconsidered. For example, how often does a real program do this?
(defun f ...) (dotimes (...) ... (setf (symbol-function 'f) #'(lambda ...)) ...)
Implementations of the next Lisp should not be influenced by previous implementations to make this operation fast, especially at the expense of poor performance of all other function calls.
The language should be segmented into at least four layers:
The kernel language, which is small and simple to implement. In all cases, the need for dynamic redefinition should be re-examined to determine that support at this level is necessary. I believe nothing in the kernel need be dynamically redefinable. A linguistic layer for fleshing out the language. This layer may have some implementational difficulties, and it will probably have dynamic aspects that are too expensive for the kernel but too important to leave out. A library. Most of what is in Common Lisp would be in this layer. Environmentally provided epilinguistic features. In the first layer I include conditionals, function calling, all primitive data structures, macros, single values, and very basic object-oriented support.
In the second layer I include multiple values and more elaborate object-oriented support. The second layer is for difficult programming constructs that are too important to leave to environments to provide, but which have sufficient semantic consequences to warrant precise definition. Some forms of redefinition capabilities might reside here.
In the third layer I include sequence functions, the elaborate IO functions, and anything else that is simply implemented in the first and possibly the second layers. These functions should be linkable.
In the fourth layer I include those capabilities that an environment can and should provide, but which must be standardized. A typical example is defmethod from CLOS. In CLOS, generic functions are made of methods, each method applicable to certain classes. The first layer has a definition form for a complete generic function – that is, for a generic function along with all of its methods, defined in one place (which is how the layer 1 compiler wants to see it). There will also be means of associating a name with the generic function. However, while developing a system, classes will be defined in various places, and it makes sense to be able to see relevant (applicable) methods adjacent to these classes. defmethod is the construct to define methods, and defmethod forms can be placed anywhere amongst other definitional forms.
But methods are relevant to each class on which the method is specialized, and also to each subclass of those classes. So, where should the unique defmethod form be placed? The environment should allow the programmer to see the method definition in any or all of these places, while the real definition should be in some particular place. That place might as well be in the single generic function definition form, and it is up to the environment to show the defmethod equivalent near relevant classes when required, and to accept as input the source in the form of a defmethod (which it then places in the generic function definition).
We want to standardize the defmethod form, but it is a linguistic feature provided by the environment. Similarly, many uses of elaborate lambda-list syntax, such as keyword arguments, are examples of linguistic support that the environment can provide possibly by using color or other adjuncts to the text.
In fact, the area of function-function interfaces should be re-examined to see what sorts of argument naming schemes are needed and in which layer they need to be placed.
Finally, note that it might be that every layer 2 capability could be provided in a layer 1 implementation by an environment.
3.7 Help Application Writers Win
The Lisp community has too few application writers. The Lisp vendors need to make sure these application writers win. To do this requires that the parties involved be open about their problems and not adversarial. For example, when an expert system shell company finds problems, it should open up its source code to the Lisp vendor so that both can work towards the common goal of making a faster, smaller, more deliverable product. And the Lisp vendors should do the same.
The business leadership of the AI community seems to have adopted the worst caricature-like traits of business practice: secrecy, mistrust, run-up-the-score competitiveness. We are an industry that has enough common competitors without searching for them among our own ranks.
Sometimes the sun also rises.
 ? & the Mysterians, 96 Tears, Pa-go-go Records 1966, re-released on Cameo Records, September 1966.