Great Works in Programming Languages (2004) | Hacker News Reader

Great Works in Programming Languages (2004)

cis.upenn.edu

212 pointsadamnemecek37 comments

The most recent paper mentioned here is from 2000. The most recent 'greatest of the great' is from 1978.

Is it simply that it takes a long time for us to decide what constitutes a significant advancement, or is something else going on?

The most recent paper mentioned here is from 2000.

Realize that the list was proposed in 2004.

Is it simply that it takes a long time for us to decide what constitutes a significant advancement, or is something else going on?

Seminal work is recognized by its influence, and influence becomes more apparent as impact accumulates over time.

The point that this was published in 2004 is certainly well taken.

I'm not sure anything interesting happened in the PL world since 2004 besides PEGs. Please feel free to correct me if I'm wrong, I always prefer to be among the first to jump on a new bandwagon in the language design trends.

A few:

* Fault Location via Dynamic Slicing

* Interprocedural Analysis and the Verification of Concurrent Programs

* Logics and Algorithms for Software Model Checking

* Verifying Low-Level Programs via Liquid Type Inference

Moreover:

* Agda

* LLVM

Thanks! Interesting. I'll try to dig out the recent papers. Although I have a feeling that most of this is not that new. LLVM is just a very basic SSA, which is early 90s. Agda builds on similar grounds as things like Coq, Minlog, even ACL2 and Isabelle, which are very old. There've been a lot of buzz in the concurrent code verification ever since the early pi-calculus papers by R. Milner.

But the liquid type inference seems to be a genuinely new thing, and apparently I totally missed it somehow. It even seems like I unknowingly reinvented something similar, by using arbitrary Prolog code as type attributes on top of a basic Hindley-Milner.

Agda builds on similar grounds as things like Coq, Minlog, even ACL2 and Isabelle, which are very old.

… Coq, Minlog, even ACL2 and Isabelle build on similar grounds as Chrysippus’ in the 3rd century BC …

i.e. there’s nothing new under the sun.

HoTT?

Dependent types, gradual typing, HoTT

The ones I've been paying attention to are data parallel programming systems and type inference algorithms (simpler ones than MLF).

What are good examples of things in the bucket of type inference algorithms that are simpler than MLF? You must be looking for ones which infer sophisticated logics, still, otherwise that bucket will always be dominated by HM, no?

Boxy types, HMF, and bidirectional (older but more recently applied to parametric polymorphism) all leverage partial annotations to handle a more flexible parametric polymorphism than HM itself allows.

Gradual and optional typing have become a pretty big idea over the last 6-7 years, as language designers have tried to retrofit type systems onto languages that weren't designed with them.

This idea has been showing up in industry (whether the designers call it "gradual typing" or not) with at least Hack, Flow, TypeScript, and Dart (which has optional type annotations).

You can find lots of references for useful underlying theory and research applications (the first paper that mentions "gradual typing" was Siek and Taha in 2006) at https://github.com/samth/gradual-typing-bib.

Typed Racket (http://docs.racket-lang.org/ts-guide/) is probably the best-engineered exemplar of many of these ideas, especially 1. installing run-time checks at boundaries between typed and untyped code, and 2. tackling problems of typing previously untyped code that uses rich class and interface patterns.

Thanks, that's fairly new.

Even in the parser corner, the parser combinator / graph-structured stack / GLL algorithm is both new and exciting. GLL was published in 2010: http://dotat.at/tmp/gll.pdf

That's very cool, thanks for posting it. I enjoyed Daniel Spiewak's paper on parser combinators for GLL too: http://www.cs.uwm.edu/~dspiewak/papers/generalized-parser-co... (scala code here: https://github.com/djspiewak/gll-combinators)

PEGs date from 2002 :-)

Another brilliant recent discovery (2001, so still more than a decade ago I am afraid) is the algebraic connection between differentiation and zippers. See Conor McBride's paper "The Derivative of a Regular Type is its Type of One-Hole Contex"

"influence becomes more apparent as impact accumulates over time."

Its interesting to try to re-prioritize the papers given a decade of impact (or lack thereof) since the list was published. I have no useful results but it was good mental exercise.

A clearly practical and influential advance from the last 10 years is the application of tracing JITs to high level languages (as in TraceMonkey and LuaJIT 2).

Interesting that a lot of this is about "What stands the test of time?" Papers from 1994 to 2004 perhaps didn't have enough time to work their way through the system.

What I find interesting is the gap of time between papers for the authors with multiple listings. A casual look suggests no more than 12 years between papers. This could be because it's a young field, but I found that worth noting.

p.s. To be pedantic, we should put 2004 in the title.

Codd, E. F. (1970). "A relational model of data for large shared data banks". Communications of the ACM 13 (6): 377. doi:10.1145/362384.362685.

http://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf

The lambda papers http://library.readscheme.org/page1.html

Previously discussed here

`https://news.ycombinator.com/item?id=5872043'.

And links to the `greatest of the great' papers;

`https://news.ycombinator.com/item?id=5872310'.

Why "Go to statement considered harmful" is considered a great work ?

Edsger W. Dijkstra made that statement in the context of an argument with Donald Knuth. Knuth won: (http://pplab.snu.ac.kr/courses/adv_pl05/papers/p261-knuth.pd...) http://web.archive.org/web/20070927094626/http://pplab.snu.a...

This article has been the bible of many "code nazis" who have caused a lot of pain to many programmers. Please, forgot this article.

Their metric of what a great work is seems to be entirely based on how many papers cite it.

This is akin to the Waterfall method being touted as the dumb way that people used to say to write software. When the entire point of the paper that introduced it by that name did so as a straw man.

Also, do be fair. If "Knuth won" the argument, he still ultimately condemned goto statements. To quote: "I personally wouldn't mind having goto in the highest level, just in case I really need it; but I probably would never use it" Further, that paper is on the list.

And, I do highly recommend people reading the paper. It is, as usual for Knuth, a very thorough exploration of the topic.

Yes, all the articles of Knuth are always insightfull. The problem of the article about goto is not its content but how it has been used since its publication to hurt the whole profession. This article is more harmfull than the occasional presence of a goto.

How so?

Great list, I'm downloading many of them now!

pdfs, or at least as many as one guy could find: http://www.reddit.com/r/compsci/comments/2nuz75/great_works_...

Surprised SICP isn't mentioned.

SICP isn't a research publication—it's a pedagogical work. It's been very valuable as a textbook for CS students, but I don't think it contributed any significant ideas to the field of PL.

Most of the papers listed on the page are PL theory papers, PL is a much bigger discipline than just theory. Some of the papers at the end are more design and/or implementation papers (e.g. the Self paper).

I was hoping this would be about the equivalent to the great works of the ancient and modern worlds, the pyramids, the manhattan project...Disappointed...

I was hoping this would be great works in various programming languages, rather than about. A list of classics like the Architecture of Open Source Applications project http://aosabook.org/en/index.html to accompany the short stories in https://github.com/aosabook/500lines

What a fool! I expected from "great works" some algorithms or pieces of code, not papers... Interesting anyway.

Plenty of them do give algorithms/code.

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