T

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Subject: T

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Date: Tue, 11 Dec 2001 17:49:02 -0400

In-reply-to: <5.1.0.14.2.20011210152757.0219dd88@pop.sidhe.org> (message fromDan Sugalski on Mon, 10 Dec 2001 15:28:35 -0500)

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I was involved in the T project. I can give you its history, in a rambling, first-person way. Around 1981-1982, the Yale CS dept., which had a strong AI group led by Roger Schank, hired undergraduate Jonathan Rees to implement a new Lisp for their research programming. Jonathan, I and Dan Weld (now a prof. at U Washington) were the three people at Yale that had discovered the early Sussman/Steele "lambda" papers, including Guy's seminal master's thesis on Rabbit, the first Scheme compiler. Dan was a college senior; Jonathan & I were juniors. Alan Perlis, the soul of the department, had just discovered functional programming, and was running a graduate seminar covering early FP languages such as Hope & Miranda & Scheme. The three of us managed to sleaze our way into this grad class, where we met each other. Some context: Common Lisp did not exist (the effort was just getting underway). MIT Scheme did not exist. Scheme was a couple of AI Lab tech reports and a master's thesis. We're talking the tiniest seed crystal imaginable, here. There was immense experience in the lisp community on optimising compiled implementations of dynamically-scoped languages -- this, to such an extent, that it was a widely held opinion at the time that "lexical scope is interesting, *theoretically*, but it's inefficient to implement; dynamic scope is the fast choice." I'm not kidding. To name two examples, I heard this, on different occasions, from Richard Stallman (designer & implementor of emacs lisp) and Richard Fateman (prof. at Berkeley, and the principal force behind franz lisp, undoubtedly the most important lisp implementation built in the early Vax era -- important because it was delivered and it worked). I asked RMS when he was implementing emacs lisp why it was dynamically scoped and his exact reply was that lexical scope was too inefficient. So my point here is that even to people who were experts in the area of lisp implementation, in 1982 (and for years afterward, actually), Scheme was a radical, not-at-all-accepted notion. And *outside* the Lisp/AI community... well, languages with GC were definitely not acceptable. (Contrast with the perl & Java era in which we live. It is no exaggeration, thanks to perl, to say in 2001 that *billions* of dollars of services have been rolled out to the world on top of GC'd languages.) Jonathan had spent the previous year on leave from Yale working at MIT. The important thing that was happening was that 32-bit machines were coming out, with 32-bit address spaces -- *big* address spaces. A lot of the existing language technology in the AI community had been developed for the PDP-11 (16-bit machine) and, more importantly, the workhorse PDP-10 and -20. I loved the "ten," may I add. It had an instruction set that fit onto a single page of large type, and was just cool. That ISA was a hacker's dream; you could play all kinds of fun games with it. For example, there was a famous hack that provided a means of (1) removing a cons cell from a freelist, (2) updating the freelist, and (3) branching if the freelist was exhausted to the GC... in *one instruction*. The PDP-10 was a 36-bit machine, with an 18-bit word-addressed address space. Note what this means: a cons cell fit into a single word. There are many who claim that the -10 was the world's first lisp machine. I agree with them. There were two extremely good, mature, highly optimised lisp implementations for the -10, one "East Coast" (Maclisp, from MIT) and one "West coast" (Interlisp, from Stanford & Xerox PARC). You could also program the -10 in a beautiful, roughly-C-level language from CMU, called Bliss. I see C and I remember Bliss, and I could weep. The problem was the limited, 18-bit address spaces of the -10's. Programmers were blowing them out. When DEC shipped the Vax & Motorola 68000s began to show up in Sun & Apollo workstations, people realised that the 32-bit address space of these architectures was a discontinuous shift in technology, and that language implementation on these machines was going to be similarly discontinuous. For example, with a really big address space, you wanted to fundamentally change your GC technology and data representations. Berkeley was a big player making the Vax happen in universities, by getting the ARPA contract to build Berkeley Unix for the Vax (which effort subsequently spun off into Sun, courtesy Bill Joy). Part of this effort was a lisp for the Vax, franz lisp, built under Fateman's guidance. Franz was a design more in the vein of Maclisp than Interlisp, enough so as to allow the porting of Macsyma (Fateman's interest) to the Vax. Franz also showed fundamental influences from a little-known lisp done at harvard. MIT responded to the Vax by kicking off the NIL project. NIL stood for "New Implementation of Lisp." Jonathan was part of this project during his year away from Yale. It was a really, really good effort, but in the end, was crippled by premature optimisation -- it was very large, very aggressive, very complex. Example: they were allocating people to write carefully hand-tuned assembly code for the bignum package before the general compiler was written. The NIL project was carried out by top people (err... I recall Jonl White & George Carrette being principals). But it never got delivered. It was finished years later than projected, by which time it was mostly irrelevant. (This has happened to me. It's a bitter, bitter experience. I fashionably decried premature optimisation in college without really understanding it until I once committed an act of premature opt so horrific that I can now tell when it is going to rain by the twinges I get in the residual scar tissue. Now I understand premature optimisation.) The genesis & eventual failure of this kind of project is always clearly visible (in hindsight) in the shibboleths of the early discussions. One key tip-off phrase is always something of the form, "We'll throw out all the old cruft, start over fresh, and just Do Things Right." (This, unfortunately, is not a useful observation, because that strategy sometimes does pay off, hugely. It's just very risky.) Jonathan worked on NIL for a year, then came back to Yale for his senior year, where he was hired by the CS dept. to implement a new Lisp. He made a *radical* decision: he was going to do an optimising, native-code *Scheme* system. He chose to name it T. This was a great name for a couple of reasons. It was short & simple, of course. It fit in with Yale CS culture, as there was a history of programs developed there that had single-letter names: e, c, z & u. (These were a locally-grown family of sophisticated screen editors that were rougly comparable to, but quite different from, emacs.) Finally, if you're a lisp hacker, then you know that NIL is the lisp false constant... and T is the canonical true constant. So "T is not NIL." Let me repeat here what a radical decision it was to go and build a Scheme. The *only* Scheme implementation that had *ever* been built at this point was the research prototype Steele had done for his Masters. *All* serious Lisps in production use at that time were dynamically scoped. No one who hadn't carefully read the Rabbit thesis believed lexical scope would fly; even the few people who *had* read it were taking a bit of a leap of faith that this was going to work in serious production use -- the difference between theory & practice is, uh, larger in practice than in theory. (For example, the other big MIT implementation effort, Zetalisp for the Lisp Machine, kept dynamic scoping, but allowed the compiler to sort of break the semantics, and then, in response to Scheme, threw lexical closures into the mix as a fairly kludged-up special form.) (The Europeans working on early systems like ML in Edinburgh probably find all this American early-80's thrashing & confusion over scoping discipline and implementation strategy incredibly clueless. Sorry 'bout that.) Besides Roger Schank, the other person who made the resource committment to hire Jonathan to develop T was John O'Donnell, who later went on to be a principal Multiflow, the company that commercialised VLIW architecture/compiler technology that Josh Fisher spun out of Yale in 1983. I suspect Alan Perlis probably had a hand in the decision, as well, though I don't really know. Committing funds to allow Jonathan to set out to (try to) build a production-quality Scheme implementation was pretty brave, up there with Jonathan's decision to try. Jonathan brought back to Yale from the NIL project a raft of really excellent implementation technology -- primarily the fundamental data representations that were carefully honed for the new-generation machine architectures, using tag bits in the low bits of the datum. E.g., if you made the fixnum tag "000", then you could add & subtract fixnums in a single instruction, with no tag-hacking overhead; you could multiply with a single pre-shift and divide with a single post-shift. This was a big improvement over Maclisp's required boxing of fixnums, and the supporting cruft that made that all work (in my opinion). Also, since the Vax was *byte* addressable, you could strip off the type tag of a cons-cell datum simply by adjusting the constant offset in the addressing mode. I.e., cons cells were represented by the double-word-aligned address of the two-word chunk of memory where the cell's car & cdr fields lived. Double-word-aligning the memory block means the low three bits of its address are always zero, that is, not needed. So the three low bits of the address were used for the type tags. So suppose we use "010" (decimal 2) for the type tag. You could take the cdr of the pair in register r7 with a single instruction: load r8, r7[4-2] where the "4" gets you 1 word (4 bytes) into the pair (the cdr field) and the "-2" corrects for the type tag. I.e., you could strip off the type tag with *zero* run-time penalty. Nice! The representations for closures and stack frames were also very clever. Jonathan had been burned by the NIL project's failure to complete, so he was very careful about avoiding premature optimisation. So he blasted out a quick & dirty prototype implementation just to get something up and running. (I think he wrote this in Maclisp, and as I recall, he called it "cheapy.") After that, all development of future implementations was done in T -- T 2 was implemented with T 1. T 2 was the first really good implementation, with all of the tricks I've described above. It ran on Vaxes & 68000's, which had also just come out. It was solid enough to be a serious system that had real clients who depended on it. About this time, roughly, Sussman's group was starting the development path that eventually led to MIT Scheme, and the (intertwined) pedagogical path that led to Sussman & Abelson's book, *Structure and Interpretation of Computer Programs*. The Lisp Machine effort had also spun out into Symbolics & LMI, causing Maclisp to spawn Zetalisp & Flavors, which in turn had a lot of influence on Common Lisp and Common Lisp's object system, CLOS. But I'm digressing. Back to Yale. T also used a pretty cool GC. Maclisp on the -10 had used a mark&sweep GC (one version of which famously "ran in the register set," though that is another story), encoding type information using a "BIBOP" scheme -- all objects were boxed, and segregated by type into pages. Hence the high bits of the object's address could be used to index into a page table to tell you what kind of thing lived in that page. This was well tuned for tight-memory systems like the -10. With large address spaces, though, you wanted to use stop©, because with stop© you only pay to copy the live data; you don't pay a cost proportional to the amount of garbage. This is well suited to the big heaps you can allocate on a 32-bit machine. Most stop© collectors almost universally implement the the Cheney algorithm, which does a breadth-first search of the heap. But BFS is not so great for memory locality -- it scatters topologically close data structures all over the heap as it copies. Not good. T used a lesser-known (but quite simple -- the research paper describing it is about 2 pages long) algorithm due to Clark that implements *depth*-first traversal. (Just as the Cheney algorithm cleverly uses the existing heap data structures to provide the BFS search queue, Clark's uses the heap to provide the search stack.) Depth-first search means that if you GC a linked list, the GC zips down the spine of the list before turning its attention to the elements of the list, so those "spine" cells wind up laid out sequentially in memory. Your list turns into a vector! (sorta) This *rocks* for locality. However, - T dropped this algorithm in the late 80's for the classic BFS algorithm. David Kranz (who will appear in this tale shortly) told me at that point that he'd made the switch because the copy phase of the BFS algorithm had slightly faster constant factors - That standard religion I just gave you about "stop© only pays for the good stuff, but in mark&sweep you have to pay for the garbage, as well"? It's not true. We all believed it for decades. But Norman Ramsey at harvard has cleverly shown that you can implement mark&sweep with *exactly* the same asymptotic costs as stop©. This is good news especially for tight-memory systems with homogenous heap data. Norman's observation is really obvious and simple; hardly an impressive result when you see it. Except, uh, that it eluded *everyone else* for *decades.* And not because people didn't care; GC has received a lot of attention from researchers. There's a lesson there. I've never seen a depth-first collector anywhere but T. By the way, the T garbage collector was written in T. This is also a slightly amazing feat. It was achieved by virtue of the fact that T was native-code compiled, and the garbage collector was written by the compiler authors. They knew *exactly* how the compiler would handle their source, so they could carefully code the collector so that it would not need to heap allocate while running. (That's not as simple as it sounds. It's not as easy as simply writing your code and never calling malloc() or invoking a "new" method. It's tied up in the treatment of lambda. Good Scheme compilers use a range of implementations for the lambdas in the program, depending upon what they can determine about the lambdas at compile time -- how they're used, to where they are passed, the relationship between the uses and the definition points, etc. Some lambdas just evaporate into nothing. Some lambdas turn into control-flow join points with associated register/variable bindings. Some lambdas turn into stack frames. But some lambdas cause heap allocation to produce general closures. So you have to understand how the compiler is going to handle every lambda you write. And the fundamental skeleton of a Scheme program is built on lambda.) Another implementation feat of T's was that it allowed interrupts between *any* two instructions of user code. This placed a pretty intense burden on the compiler, enough so that, of all the Scheme implementations of which I'm aware, T is *unique* in this respect. To understand why this is hard in the presence of garbage collection, you can read a paper I wrote on the subject ten years later, "Atomic heap transactions and fine-grain interrupts," found at http://www.cc.gatech.edu/~shivers/citations.html#heap (You don't have to be a heavy-duty lambda-calculus wizard to read this paper; it's written to be comprehensible to general hackers.) T also allowed you to write interrupt (Unix signal) handlers in T, which was pretty pleasant. There was more to T than implementation technology; there was also a lot of beautiful language design happening. Jonathan seized the opportunity to make a complete break with backwards compatibility in terms of the runtime library and even the names chosen. Somewhere in the T 2 effort, Kent Pitman, another Lisp wizard, came down to Yale from MIT. He and Jonathan poured an immense amount of design effort into the language, and it was just really, really *clean*. Small (but difficult) things: they chose a standard set of lexemes and a regular way of assembling them into the names of the standard procedures, so that you could easily remember or reconstruct names when you were coding. (I have followed this example in the development of the SRFIs I've done for the Scheme community. It is not an easy task.) Larger, deeper things: they designed a beautiful object system that was integrated into the assignment machinery -- just as Common Lisp's SETF lets you assign using accessors, e.g., in Common Lisp (setf (car x) y) is equivalent to (rplaca x y) in T, (set! (car x) y) was shorthand for ((setter car) x y) Accessor functions like CAR handled "generic functions" or "messages" like SETTER -- CAR returned the SET-CAR! procedure when sent the SETTER message. The compiler was capable of optimising this into the single Vax store instruction that implements the SET-CAR! operation, but the semantic machinery was completely general -- you could define your own accessor procedures, give them SETTER methods, and then use them in SET! forms. (This turned out to be very nice in the actual implementation of the compiler. The AST was a tree of objects, connected together in both directions -- parents knew their children; children also had links to their parents. If the optimiser changed the else-part of an if-node N with something like this (set! (if-node:else n) new-child) which was really ((setter if-node:else) n new-child) the if-node:else's SETTER method did a lot of work for you -- it disconnected the old child, installed NEW-CHILD as N's else field, and set NEW-CHILD's parent field to be N. So you could never forget to keep all the links consistent; it was all handled for you just by the single SET! assignment.) Around the time that Kent went back to MIT, new grad student Norman Adams hooked up w/Jonathan. T 2 and its compiler TC, was produced after about a year of really hard, focussed work on the part of Jonathan, Kent and Norman. I graduated from Yale and went off to CMU to be a grad student in AI. Jonathan started to think about the next compiler. During my first year as a grad student, Jonathan met Forrest Baskett, who was the director of one of the top industrial CS labs, DEC's Western Research Lab, where a lot of the important RISC work was done (e.g., you could argue that David Wall's work on interprocedural register allocation there killed the architectural feature of overlapping register-set stacks that came out of Berkeley and wound up in the SPARC). Forrest liked Jonathan, and invited him to bring a team out to WRL for the summer to implement T for the machine they were building (an amazing-for-the-time RISC called the Titan). Jonathan's team was himself, Norman, Jim Philbin, David Kranz, Richard Kelsey, John Lamping and myself. Lamping was at Stanford, I was at CMU, the rest were grad students at Yale (except Jonathan, who was an employee at Yale). This brings us to the summer of 1984. The mission was to build the world's most highly-optimising Scheme compiler. We wanted to compete with C and Fortran. The new system was T3, and the compiler was to be called Orbit. We all arrived at WRL and split up responsibility for the compiler. Norman was going to do the assembler. Philbin was going to handle the runtime (as I recall). Jonathan was project leader and (I think) wrote the linker. Kranz was to do the back end. Kelsey, the front end. I had passed the previous semester at CMU becoming an expert on data-flow analysis, a topic on which I completely grooved. All hot compilers do DFA. It is necessary for all the really cool optimisations, like loop-invariant hoisting, global register allocation, global common subexpression elimination, copy propagation, induction-variable elimination. I knew that no Scheme or Lisp compiler had ever provided these hot optimisations. I was burning to make it happen. I had been writing 3D graphics code in T, and really wanted my floating-point matrix multiplies to get the full suite of DFA optimisation. Build a DFA module for T, and we would certainly distinguish ourselves from the pack. So when we divided up the compiler, I told everyone else to back off and loudly claimed DFA for my own. Fine, everyone said. You do the DFA module. Lamping signed up to do it with me. Lamping and I spent the rest of the summer failing. Taking trips to the Stanford library to look up papers. Hashing things out on white boards. Staring into space. Writing little bits of experimental code. Failing. Finding out *why* no one had ever provided DFA optimisation for Scheme. In short, the fundamental item the classical data-flow analysis algorithms need to operate is not available in a Scheme program. It was really depressing. I was making more money than I'd ever made in my life ($600/week). I was working with *great* guys on a cool project. I had never been to California before, so I was discovering San Francisco, my favorite city in the US and second-favorite city in the world. Silicon Valley in 1984 was beautiful, not like the crowded strip-mall/highway hell hole it is today. Every day was perfect and beautiful when I biked into work. I got involved with a gorgeous redhead. And every day, I went in to WRL, failed for 8 hours, then went home. It was not a good summer. At the end of the summer, I slunk back to CMU with my tail between my legs, having contributed not one line of code to Orbit. Everyone else, however, completed. The compiler wasn't finished by summer's end, but it was completed the following year at Yale. And it was the world's most highly optimising Scheme compiler (even though it did not do data-flow analysis), a record it held for a *long* time -- perhaps ten years? It was also a massive validation of a thesis Steele had argued for his Master's, which was that CPS was a great intermediate representation for a compiler. Orbit was totally hard-core about this -- the first thing the compiler did was translate the user program into CPS, and that was the standard form on which the compiler operated for the rest of its execution. And it turned out this approach scaled up from Rabbit to a production, native-code compiler very successfully. David Kranz took the work he'd done on the back end, which was a very complex piece of code that did a lot of sophisticated analysis on data representations, register allocation, and, in particular, lambdas, and turned it into his PhD thesis. Orbit produced code that actually beat the Pascal implementation used by Apollo (a Sun-class workstation company) to implement the *operating system* on that workstation; that was a huge coup. David then went to MIT, where he brought his compiler technology to Bert Halstead's parallel lisp project, before hooking up with Steve Ward to do the research project that turned into Curl. When Ward spun Curl out into a company, Halstead & Kranz became the senior technical guys there. Let's call Kranz's dissertation PhD #1. It's title was *An Optimising Compiler for Scheme,* which I took to be an in-reference to William Wulf's seminal Bliss compiler, described in a book (my copy is signed) titled simply *The Design of an Optimising Compiler*. Wulf's Bliss compiler was a model up to which we all looked -- it held the title "world's most highly optimising compiler" for a while. (Remember Bliss? Just to add more cross-links, Wulf had left CMU about then and spun out a company, Tartan Labs, to commercialise this compiler technology for C. He took Guy Steele with him, who had just finished wrapping up leading the Common Lisp definition while on the faculty at CMU. Tartan tanked, Wulf moved on to a senior position at UVa & is now a big wheel at the national science-policy level, e.g. leading National Academy inquiries into counter-terrorism technology. Steele went to Thinking Machines, and then threw his language-development skills behind the Java effort at Sun.) Kranz' diss is a Yale Computer Science Dept. tech report. I would say it is required reading for anyone interested in serious compiler technology for functional programming languages. You could probably order or download one from a web page at a url that I'd bet begins with http://www.cs.yale.edu/. Richard Kelsey took his front end, which was a very aggressive CPS-based optimiser, and extended it all the way down to the ground to produce a complete, second compiler, which he called "TC" for the "Transformational Compiler." His approach was simply to keep transforming the program from one simple, CPS, lambda language to an even simpler one, until the language was so simple it only had 16 variables... r1 through r15, at which time you could just kill the lambdas and call it assembler. It is a beautiful piece of work, and, like Kranz's dissertation, required reading for anyone who wants to do compilers for functional programming languages. It had a big influence on Andrew Appel, at Princeton, who subsequently adopted a lot of the ideas in it when he and Dave MacQueen's group at Bell Labs built the SML/NJ compiler for SML; Andrew described this in the book he subsequently wrote on that compiler, *Compiling With Continuations.* However, unlike the SML/NJ compiler, Kelsey's CPS-based compiler compiled code that used a run-time stack for procedure calls. He actually describes front ends in his diss for standard procedural "non-lambda" languages such as Basic. So the lineage of the CPS-as-compiler-IR thesis goes from Steele's Rabbit compiler through T's Orbit to SML/NJ. At which point Sabry & Felleisen at Rice published a series of very heavy-duty papers dumping on CPS as a representation and proposing an alternate called A-Normal Form. ANF has been the fashionable representation for about ten years now; CPS is out of favor. This thread then sort of jumps tracks over to the CMU ML community, where it picks up the important typed-intermediate-language track and heads to Cornell, and Yale, but I'm not going to follow that now. However, just to tell you where I am on this issue, I think the whole movement from CPS to ANF is a bad idea (though Sabry & Felleisen's technical observations and math are as rock solid as one would expect from people of their caliber). Let's call Kelsey's dissertation PhD #2. Kelsey subsequently spent time as a prof at Northeastern, then left for NEC's prestige lab in Princeton, where he worked on the Kali distributed system. He also got set down precisely on paper something all the CPS people knew at some intuitive level: that the whole "SSA" revolution in the classical compiler community was essentially a rediscovery of CPS. (Harrumph.) NEC Princeton went on to accumulate a very impressive collection of Scheme/ML hackers: Stephen Weeks & Andrew Wright from Rice, Kevin Lang (who built a little known but quite beautiful, elegant, free and portable object-oriented Scheme called Oaklisp), Kelsey, Jim Philbin, Henry Cetjin, and Jeff Siskind. When NEC Princeton became an insane toxic place, Kelsey, like almost everyone else in that previous list, jumped out into startup land, where he did a startup with Rees & an MIT alumn, Patrick Sobalvarro, who achieved some early fame for work on GC. That startup tanked in the dotcom meltdown last year, and Kelsey's now on his second startup. Norman Adams turned his assembler into a master's degree. It also was a cool piece of software. His assembler didn't take a linear text stream; the compiler handed it a *graph structure*. It serialised the graph on its own to minimise the spans of the jump instructions, and had other neat features (e.g., it was actually a portable framework for building assemblers). Then he took his Masters and bailed out to Tektronix, where he developed a very high-performance Scheme implementation for the Motorola 88000 called "screme," and then went to Xerox PARC, where he worked on ubiquitous computing and a Scheme implementation called SchemeXeroX (a joke on "Team Xerox") with Pavel Curtis. He left Xerox at the beginning of the dotcom boom and was early in at the startup company Ariba, which is why (1) Ariba's big product had a configuration system that is a Scheme built in Java and (2) he's a rich dude. Lamping's story is perhaps the strangest. He went back to Stanford, and got involved in a very arcane, theoretical problem called optimal lambda reduction, which he completely solved for his PhD. This is an achievement of considerable note because pointy-headed theoretical semanticists had been struggling to crack this problem for a long time in Europe. They'd been struggling so hard, in fact, that they really seemed... annoyed when this hacker from Stanford just sat down and solved the problem. John seemed to be completely unqualified to solve the problem, bringing nothing to it but, uh, brains. There was, for example, a snooty French paper that sort of dismissed Lamping as an "autodidact," before proceeding to build (with, let me be careful to note, proper credit given to John) on his work. So Lamping has thus been permanently saddled with this hilarious title/term, by those who know & like him. He'll never live it down. John Lamping, autodidact. John subsequently went to Xerox PARC, where he and Gregor Kiczales made a team working on a wide array of interesting programming-language problems, of which "Aspect-Oriented Programming" is the most well known. Again, the story here departs from T, so I won't pursue it. For the same reason, we will not call John's dissertation "PhD #3" -- it wasn't really connected to his work on the T project. About three years after the summer at WRL, I *finally* figured out how to do data-flow analysis for Scheme, which ended a long, pretty unhappy period in my life. I officially switched from being an AI student to being a PL student, picked up Peter Lee as a co-advisor (since my original advisor, Allen Newell, while certainly the greatest scholar I've ever personally known, was not a PL guy), and wrote it all up for *my* dissertation. This we can call PhD #3. By the way, I'll add that the deepest and most powerful part of my diss, in my opinion, is the part (a) about which no one seems to know and (b) which is on the shakiest theoretical ground: environment reflow analysis. I would surely love it if some interested character one day takes that piece of my diss and really takes it someplace. Jim Philbin, like Kelsey, also went to NEC, where he built an operating system tuned for functional programming languages, STING (or perhaps it was spelled "STNG" -- in any event it was pronounced "sting"). He built it in T, of course, and one could see that it had its roots in his work on T3. (Implementing the runtime for a functional language, in some sense, requires you to implement a little virtual OS on top of the real, underlying OS.) Call that PhD #4. Jim subsequently left Scheme, to do parallel processor & systems work with Kai Li at Princeton. Jonathan went to MIT as a graduate student, where he worked with Gerry Sussman and David Gifford. After working on a series of interesting problems, Jonathan also wrote his dissertation on an operating system for functional languages, where you could use language safety as the fundamental protection mechanism. Call that PhD #5. Then he got interested in entomology (bugs, I mean -- real bugs, not computer bugs), did a post-doc in Europe, then came back to the US and has sort of bounced between pursuing research topics that are as radical and unusual as T was in 1982 & startup companies. (Jonathan also wrote his dissertation *in Scheme* as well as *about* Scheme. He built a little word processor for his diss in Scheme called "markup" that allowed you to write standard text, interspersed with commands that were delimited with curly braces. (Hmm. Text and commands in curly braces. Sound familiar?) Commands were defined in Scheme; the markup processor had multiple back-ends, such as HTML & PostScript. Scott Draves later extended markup for *his* dissertation on partial-evaluation and high-performance graphics rendering at CMU.) I think that covers the entire T team. It is interesting to note that *five* dissertation-level chunks of work (and one Master's-level chunk) came out of a single summer project. I've spent a fair amount of time discussing T's implementation technology. However, it is also worth study as a language *design*, and here, Jonathan is the single greatest influence. T was, principally, his baby. It was quite a beautiful design. When the risc revolution happened, Orbit was ported to the late-80's risc processors: MIPS & SPARC. This is when the Clark GC was ripped out and replaced with the Cheney collector. At CMU, I ported Orbit to an IBM precursor of their POWER architecture, called the ROMP or the RT/PC. One of the limiting factors of Orbit was the complexity of the back end. It was documented very well by Kranz' diss, and it was very sophisticated, but it was also a big mess of code. Out of a reaction to this complexity was born Scheme 48 -- when Kelsey came to Northeastern as a prof, Jonathan was still at MIT; he and Jonathan built Scheme 48 together. Its first use was on an autonomous robot system that Jonathan had gotten involved with at Cornell. The name was intended to reflect the idea that the implementation should be so clear and simple that you could believe the system could have been written in 48 hours (or perhaps, when S48 got complex enough, this was altered to "could have been *read* in 48 hours"). Scheme 48 had very little technical overlap w/T3 and Orbit -- no native code compiler, no object system, no CPS IR. Its innovations were its module system, the language in which its VM was defined ("pre-scheme"), and its stack-management technology. These were all interesting technical bits. The stack was managed not by push & pop, but by push & a generational gc. I believe Kelsey wrote a paper on this and its advantages. The module system was somewhat like SML's, but allowed modular macros and had another fairly cool feature: when you defined a module, clauses let you specify which files held the module's source. But *other* clauses let you specify which "reader" procedure to use to translate the character stream in the files to the s-expression tree handed to the compiler. So you could handle files with different concrete syntax -- R5RS syntax, scsh syntax, S48 syntax, PLT Scheme syntax, guile syntax, perhaps an infix syntax (as is so often discussed). That eliminated an annoying, low-level but persistent barrier to sharing code across different implementations of Scheme. Pre-scheme was quite interesting. Kelsey published a paper on it, as well, I believe. It was Scheme in the sense that you could load it into a Scheme system and run the code. But it was restrictive -- it required you to write in a fashion that allowed complete Hindley-Milner static type inference, and all higher-order procedures were beta-substituted away at compile time, meaning you could *straightforwardly* translate a prescheme program into "natural" C code with C-level effiency. That is, you could view prescheme as a really pleasant alternative to C for low-level code. And you could debug your prescheme programs in the interactive Scheme development environment of your choice, before flipping a switch and translating to C code, because prescheme was just a restricted Scheme. The Scheme 48 byte-code interpreter was written in prescheme. Prescheme sort of died -- beyond the academic paper he wrote, Kelsey never quite had the time to document it and turn it into a standalone tool that other people could use (Ian Horswill's group at Northwestern is an exception to that claim -- they have used prescheme for interesting work). There are ideas there to be had, however. I subsequently picked up Scheme 48 around 1992 to build scsh, but we're beginning to wander from T, so I'll leave that thread. The tapestry of advanced language implementation work is a very rich and interconnected one, the weaving of which is is an incredibly interesting task that can keep you happily occupied for a lifetime. I've only traced out one selected thread in that tapestry with this rambling post; there are many other important ones. But that, to the best of my knowledge, is the story of T. A cautionary note: the danger of writing history when all of the principals are still alive is that there are people around to catch you out in your errors. I'm sure there *are* errors in my recollection, but I'm also reasonably sure I've got the broad strokes roughly correct. Someone like Jonathan could certainly give a much more authoritative account. -Olin ------------------------------------------------------------------------------- Here are some references to papers I've mentioned. This is the first paper published on T, based on T2 \Bibitem[Rees\etal 82]{T} Jonathan A.~Rees and Norman I.~Adams {\sc iv}. \\ T: A dialect of Lisp or, Lambda: The ultimate software tool. \\ In {\em Conference Record of the 1982 ACM Symposium on LISP and Functional Programming,} pages 114--122, August 1982. This is a general overview of T3's Orbit: ORBIT: An optimizing compiler for Scheme. \\ In {\em Proceedings of the SIGPLAN '86 Symposium on Compiler Construction,} published as {\em SIGPLAN Notices\/} 21(7), pages 219--233. Association for Computing Machinery, July 1986. There is a later, third paper, written by Jonathan & Norman, on object systems in general and T's in particular. I do not have a reference. The reference manual for T is also interesting reading, for information on the features of the language. Here is a citation: \Bibitem[Rees\etal 84]{TMan} Jonathan A.~Rees, Norman I.~Adams {\sc iv} and James R.~Meehan. \\ {\em The T Manual.} \\ 4th edition, Yale University, Department of Computer Science, January 1984. I also could probably post PostScript source for it, if people care. Kelsey's diss: {\em Compilation by Program Transformation.} \\ Ph.D.~dissertation, Yale University, May 1989. Research Report 702, Department of Computer Science. \\ A conference-length version of this dissertation appears in {\em POPL 89}. Kranz's diss: \Bibitem[Kranz 88]{KranzPhD} David Kranz. \\ {\em ORBIT: An Optimizing Compiler for Scheme.} \\ Ph.D.~dissertation, Yale University, February 1988. Research Report 632, Department of Computer Science. \\ I don't have references for Rees', Philbin's or Lamping's dissertations. They shouldn't be hard to dig up if you care.