Lambda the Ultimate

An amusing historical analysis of the origin of zero based array indexing (hint: C wasn't the first). There's a twist to the story which I won't reveal, so as not to spoil the story for you. All in all, it's a nice anecdote, but it seems to me that many of the objections raised in the comments are valid.

This summer, spend some quality time with your favorite technology in our 2013 summer programming contest!

The Lisp community is awarding prizes for demonstrating interesting and useful programs, technologies and art using any LISP-based technology.

Lisp, prizes, what's not to like?

I was surprised to see that DYNAMO hasn't been mentioned here in the past. DYNAMO (DYNAmic MOdels) was the simulation language used to code the simulations that led to the famous 1972 book The Limits to Growth from The Club of Rome. The language was designed in the late 1950s. It is clear that the language was used in several other places and evolved through several iterations, though I am not sure how extensively it was used. When Stafford Beer was creating Cybersyn for Salvador Allende he used DYNAMO to save time suggesting it was somewhat of a standard tool (this is described in Andrew Pickering's important book The Cybernetic Brain).

The language itself is essentially what you'd expect. It is declarative, programs consisting of a set of equations. The equations are zero and first-order difference equations of two kinds: level equations (accumulations) and rate equations (flows). Computation is integration over time. Levels can depend on rates and vice versa with the language automatically handling dependencies and circularities. Code looks like code looked those days: fixed columns, all caps, eight characters identifiers.

Here are a few links:

• Section 3.7 of this history of discrete event simulation languages is a succinct description of the history of the language and its main features.
• A more leisurely description of the language and the Limits to Growth model can be found in this article. Ironically, the author of the article reimplemented the model in Javascript (run it!). What was originally written in a DSL is now implemented in a general purpose language, with all the niceties handled manually.
• Finally, a nice piece on Jay Forrester who prompted the creation of SIMPLE and DYNAMO, its offspring.

A fun thread at stackexhange.

Oleg Kiselyov, Simon Peyton-Jones and Amr Sabry: Simple Generators:

Incremental stream processing, pervasive in practice, makes the best case for lazy evaluation. Lazy evaluation promotes modularity, letting us glue together separately developed stream producers, consumers and transformers. Lazy list processing has become a cardinal feature of Haskell. It also brings the worst in lazy evaluation: its incompatibility with effects and unpredictable and often extraordinary use of memory. Much of the Haskell programming lore are the ways to get around lazy evaluation.

We propose a programming style for incremental stream processing based on typed simple generators. It promotes modularity and decoupling of producers and consumers just like lazy evaluation. Simple generators, however, expose the implicit suspension and resumption inherent in lazy evaluation as computational effects, and hence are robust in the presence of other effects. Simple generators let us accurately reason about memory consumption and latency. The remarkable implementation simplicity and efficiency of simple generators strongly motivates investigating and pushing the limits of their expressiveness.

To substantiate our claims we give a new solution to the notorious pretty-printing problem. Like earlier solutions, it is linear, backtracking-free and with bounded latency. It is also modular, structured as a cascade of separately developed stream transducers, which makes it simpler to write, test and to precisely analyze latency, time and space consumption. It is compatible with effects including IO, letting us read the source document from a file, and format it as we read.

This is fascinating work that shows how to gain the benefits of lazy evaluation - decoupling of producers, transformers, and consumers of data, and producing only as much data as needed - in a strict, effectful setting that works well with resources that need to be disposed of once computation is done, e.g. file handles.

The basic idea is that of Common Lisp signal handling: use a hierarchical, dynamically-scoped chain of handler procedures, which get called - on the stack, without unwinding it - to parameterize code. In this case, the producer code (which e.g. reads a file character by character) is the parameterized code: every time data (a character) is produced, it calls the dynamically innermost handler procedure with the data (it yields the data to the handler). This handler is the data consumer (it could e.g. print the received character to the console). Through dynamic scoping, each handler may also have a super-handler, to which it may yield data. In this way, data flows containing multiple transformers can be composed.

I especially like the OCaml version of the code, which is just a page of code, implementing a dynamically-scoped chain of handlers. After that we can already write map and fold in this framework (fold using a loop and a state cell, notably.) There's more sample code.

This also ties in with mainstream yield.

Tiny Transactions on Computer Science (TinyToCS) is the premier venue for computer science research of 140 characters or less.

This is an interesting idea: CS papers whose body fits in 140 characters - the abstract may be longer, watering the concept down a bit.

Interactive Tutorial of the Sequent Calculus by Edward Z. Yang.

This interactive tutorial will teach you how to use the sequent calculus, a simple set of rules with which you can use to show the truth of statements in first order logic. It is geared towards anyone with some background in writing software for computers, with knowledge of basic boolean logic. ...

Proving theorems is not for the mathematicians anymore: with theorem provers, it's now a job for the hacker. — Martin Rinard ...

A common complaint with a formal systems like the sequent calculus is the "I clicked around and managed to prove this, but I'm not really sure what happened!" This is what Martin means by the hacker mentality: it is now possible for people to prove things, even when they don't know what they're doing. The computer will ensure that, in the end, they will have gotten it right.

The tool behind this nice tutorial is Logitext.

Here's a fun challenge for LtU. The team at Securelist is analyzing a worm called Duqu and found a few interesting things. One of them is that they can't figure out the source language for the core framework.

After having performed countless hours of analysis, we are 100% confident that the Duqu Framework was not programmed with Visual C++. It is possible that its authors used an in-house framework to generate intermediary C code, or they used another completely different programming language.

We would like to make an appeal to the programming community and ask anyone who recognizes the framework, toolkit or the programming language that can generate similar code constructions, to contact us or drop us a comment in this blogpost. We are confident that with your help we can solve this deep mystery in the Duqu story.

I'm not clear on how much knowing the source language helps with the security analysis, but what else were you doing with your time? All the details and clues in the object file can be found on their blog.

Nick Benton and Neel Krishnaswami, ICFP'11, A Semantic Model for Graphical User Interfaces:

We give a denotational model for graphical user interface (GUI) programming using the Cartesian closed category of ultrametric spaces. [..] We capture the arbitrariness of user input [..] [by a nondeterminism] “powerspace” monad.

Algebras for the powerspace monad yield a model of intuitionistic linear logic, which we exploit in the definition of a mixed linear/non-linear domain-specific language for writing GUI programs. The non-linear part of the language is used for writing reactive stream-processing functions whilst the linear sublanguage naturally captures the generativity and usage constraints on the various linear objects in GUIs, such as the elements of a DOM or scene graph.

We have implemented this DSL as an extension to OCaml, and give examples demonstrating that programs in this style can be short and readable.

This is an application of their (more squiggly) LICS'11 submission, Ultrametric Semantics of Reactive Programs. In both these cases, I find appealing the fact the semantic model led to a type system and a language that was tricky to find.

Programming and Scaling, a one-hour lecture by Alan Kay at his finest (and that's saying something!)

Some of my favorite quotes:

• "The biggest problem we have as human beings is that we confuse our beliefs with reality."
• "We could imagine taking the internet as a model for doing software modules. Why don't people do it?" (~00:17)
• "One of the mistakes that we made years ago is that we made objects too small." (~00:26)
• "Knowledge in many cases trumps IQ. [Henry] Ford was powerful because Isaac Newton changed the way we think." (~00:28)
• "Knowledge is silver. Outlook is gold. IQ is a lead weight." (~00:30)
• "Whatever we [in computing] do is more like what the Egyptians did. Building pyramids, piling things on top of each other."
• "The ability to make science and engineering harmonize with each other - there's no greater music." (~00:47)

And there are some other nice ideas in there: "Model-T-Shirt Programming" - software the definition of which fits on a T-shirt. And imagining source code sizes in terms of books: 20,000 LOC = a 400-page book. A million LOC = a stack of books one meter high. (Windows Vista: a 140m stack of books.)

Note: this a Flash video, other formats are available.