Lambda the Ultimate

Ongoing discussion that you can follow on William Cook's blog.

I am not going to take sides (or keep points). I know everyone here has an opinion on the issue, and many of the arguments were discussed here over the years. I still think LtU-ers will want to follow this.

Given the nature of the topic, I remind everyone to review our policies before posting here on the issue.

The event is held at the Microsoft Campus on Apr 2-4 with talks, panels and discussions from 9-5 every day. Attendance is free, and includes lunch. Details here.

While ethics aren't normal LtU fare, it's sometimes interesting to see how our technical discussions fit into a larger picture.

In When Formal Systems Kill: Computer Ethics and Formal Methods February, 2012, Darren Abramson and Lee Pike make the case that the ubiquity of computing in safety critical systems and systems that can create real economic harm means that formal methods should not just be technical and economic discussions but ethical ones as well.

Computers are different from all other artifacts in that they are automatic formal systems. Since computers are automatic formal systems,techniques called formal methods can be used to help ensure their safety. First, we call upon practitioners of computer ethics to deliberate over when the application of formal methods to computing systems is a moral obligation. To support this deliberation, we provide a primer of the subfield of computer science called formal methods for non-specialists. Second, we give a few arguments in favor of bringing discussions of formal methods into the fold of computer ethics.

They also spend a good amount of time giving a lay overview of the practical, economic challenges faced by formal methods.

Julia is a new programming language by Viral Shah, Jeff Bezanson, Stefan Karpinski, and Alan Edelman.

From the blog post Why We Created Julia:

We are greedy: we want more.

We want a language that’s open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that’s homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled.

(Did we mention it should be as fast as C?)

While we’re being demanding, we want something that provides the distributed power of Hadoop — without the kilobytes of boilerplate Java and XML; without being forced to sift through gigabytes of log files on hundreds of machines to find our bugs. We want the power without the layers of impenetrable complexity. We want to write simple scalar loops that compile down to tight machine code using just the registers on a single CPU. We want to write A*B and launch a thousand computations on a thousand machines, calculating a vast matrix product together.

We never want to mention types when we don’t feel like it. But when we need polymorphic functions, we want to use generic programming to write an algorithm just once and apply it to an infinite lattices of types; we want to use multiple dispatch to efficiently pick the best method for all of a function’s arguments, from dozens of method definitions, providing common functionality across drastically different types. Despite all this power, we want the language to be simple and clean.

Looking at the excellent Julia manual, it becomes clear that Julia is a descendant of Common Lisp. While Common Lisp has many detractors (and not entirely without reason), nobody can claim that the family of languages it spawned aren't well designed. On the contrary, languages like NewtonScript, Dylan, [Cecil and Diesel,] Goo, PLOT, and now Julia all have a hard to grasp quality without a name that makes them an improvement over many of their successors.

In the video A Concept Design for C++ and the related paper Design of Concept Libraries for C++ Bjarne Stroustrup and Andrew Sutton describe how they're going avoid the problems that lead to concepts getting voted out of C++11. In a nutshell they seem to be focusing on the simplest thing that could possibly work for STL (C++'s Standard Template Library).

C++ does not provide facilities for directly expressing what a function template requires of its set of parameters. This is a problem that manifests itself as poor error messages, obscure bugs, lack of proper overloading, poor specification of interfaces, and maintenance problems.

Many have tried to remedy this (in many languages) by adding sets of requirements, commonly known as "concepts." Many of these efforts, notably the C++0x concept design, have run into trouble by focusing on the design of language features.

This talk presents the results of an effort to first focus on the design of concepts and their use; Only secondarily, we look at the design of language features to support the resulting concepts. We describe the problem, our approach to a solution, give examples of concepts for the STL algorithms and containers, and finally show an initial design of language features. We also show how we use a library implementation to test our design.

So far, this effort has involved more than a dozen people, including the father of the STL, Alex Stepanov, but we still consider it research in progress rather than a final design. This design has far fewer concepts than the C++0x design and far simpler language support. The design is mathematically well founded and contains extensive semantic specifications (axioms).

Jon Purdy riffs on Hughe's famous "Why Functional Programming Matters" with a blog post on Why Concatenative Programming Matters.

From the syllabus of the Cambridge course on Usability of Programming Languages

Compiler construction is one of the basic skills of all computer scientists, and thousands of new programming, scripting and customisation languages are created every year. Yet very few of these succeed in the market, or are well regarded by their users. This course addresses the research questions underlying the success of new programmable tools. A programming language is essentially a means of communicating between humans and computers. Traditional computer science research has studied the machine end of the communications link at great length, but there is a shortage of knowledge and research methods for understanding the human end of the link. This course provides practical research skills necessary to make advances in this essential field. The skills acquired will also be valuable for students intending to pursue research in advanced HCI, or designing evaluation studies as a part of their MPhil research project.

Is this kind of HCI based research going to lead to better languages? Or more regurgitations of languages people are already comfortable with?

I have just learned that Dennis Ritchie (1941-2011) has passed away. His contributions changed the computing world. As everyone here knows, dmr developed C, and with Brian Kernighan co-authored K&R, a book that served many of us in school and in our professional lives and remains a classic text in the field, if only for its style and elegance. He was also one of the central figures behind UNIX. Major programming languages, notably C++ and Java, are descendants of Ritchie's work; many other programming languages in use today show traces of his influences.

Update

Bjarne Stroustrup puts the C revolution in perspective: They said it couldn’t be done, and he did it.

Steve Jobs (1955 - 2011) had a profound influence on the computing world. As others discuss his many contributions and accomplishments, I think it is appropriate that we discuss how these affected programming, and consequently programming languages. Bringing to life some of the ideas of the Mother of All Demos, Jobs had a hand in making event loops standard programming fare, and was there when Apple and NeXT pushed languages such as Objective-C and Dylan and various software frameworks, and decided to cease supporting others. Some of these were more successful than others, and I am sure members have views on their technical merits. This thread is for discussing Jobs -- from the perspective of programming languages and technologies.

Update:

Eric Schmidt on Jobs and OOP

Stephen Wolfram on Jobs and Mathematica

The iPhone mandate decision

A. Dehon, B. Karel, B. Montagu, B. Pierce, J. Smith, T. Knight, S. Ray, G. Sullivan, G. Malecha, G. Morrisett, R. Pollack, R. Morisset & O. Shivers. Preliminary design of the SAFE platform. In Proceedings of the 6th Workshop on Programming Languages and Operating Systems (PLOS 2011). ACM, Oct. 2011.

ABSTRACT — Safe is a clean-slate design for a secure host architecture, coupling advances in programming languages, operating systems, and hardware, and incorporating formal methods at every step. The project is still at an early stage, but we have identified a set of fundamental architectural choices that we believe will work together to yield a high-assurance system. We sketch the current state of the design and discuss several of these choices.

Proving an operating system correct down to the hardware specification and against a threat model does seem to demand new programming languages and higher-order constructive type theory.