Lambda the Ultimate

Interesting and wide-ranging interview with Adele Goldberg from Computer History
Transcript and Video at Computer History Also on YouTube

Adele Goldberg reflects on her life and career from her early days at the University of Chicago and Stanford University through her career at Xerox Palo Alto Research Center (PARC) and ParcPlace Systems.

Another Oral History interview with her by IEEE Global History Network

Goldberg discusses her educational and work history. She recalls her experiences as a student at the University of Michigan and at the University of Chicago. Next, she covers her stretch at Xeorx PARC, sharing her views on the work environment. Here she speaks at length about her work on Smalltalk, including her leading role in its commercialization. Goldberg is candid about the challenges she faced in forming and running spin-out company ParcPlace Systems. In addition, she discusses her two-year tenure as President of ACM. Finally, Goldberg offers advice for young women who are considering a career in computing.

I haven't seen this discussed here yet: http://www.puzzlescript.net/

It is an HTML5-based puzzle game engine that uses a simple language for patterns and substitutions to describe game rules. For example (taken from their introduction), the basic block-pushing logic of a Sokoban game can be given as:

[ > Player | Crate ] -> [ > Player | > Crate ]

This line says that when the engine sees the pattern to the left of ->, it should replace it with the pattern on the right. In this case, the rule can be read as something like: when there is a row or column ([]) that contains a player object (Player) next to (|) a crate object (Crate), and the player is trying to move toward the crate (>), then (->) make the crate move in the same direction.

Rules are matched and applied iteratively at each step (i.e., when the player acts), until there are no more matches, and then movement takes place. There are mechanisms for influencing the order in which rules are run, and for forcing subsets of the rules to be iterated. By default, rules apply to both rows and columns, but horizontal- or vertical-only rules can be created.

It is an interesting example of a very narrowly-focused DSL, based on a (relatively) uncommon model of computation. It's also very fun to play with!

Backpack: Retrofitting Haskell with Interfaces
Scott Kilpatrick, Derek Dreyer, Simon Peyton Jones, Simon Marlow
2014

Module systems like that of Haskell permit only a weak form of modularity in which module implementations directly depend on other implementations and must be processed in dependency order. Module systems like that of ML, on the other hand, permit a stronger form of modularity in which explicit interfaces express assumptions about dependencies, and each module can be typechecked and reasoned about independently.

In this paper, we present Backpack, a new language for building separately-typecheckable packages on top of a weak module system like Haskell's. The design of Backpack is inspired by the MixML module calculus of Rossberg and Dreyer, but differs significantly in detail. Like MixML, Backpack supports explicit interfaces and recursive linking. Unlike MixML, Backpack supports a more flexible applicative semantics of instantiation. Moreover, its design is motivated less by foundational concerns and more by the practical concern of integration into Haskell, which has led us to advocate simplicity—in both the syntax and semantics of Backpack—over raw expressive power. The semantics of Backpack packages is defined by elaboration to sets of Haskell modules and binary interface files, thus showing how Backpack maintains interoperability with Haskell while extending it with separate typechecking. Lastly, although Backpack is geared toward integration into Haskell, its design and semantics are largely agnostic with respect to the details of the underlying core language.

Microsoft's Joe Duffy and team have been (quietly) working on a new programming language, based on C# (for productivity, safety), but leveraging C++ features (for performance). I think it's fair to say - and agree with Joe - that a nirvana for a modern general purpose language would be one that satisfies high productivity (ease of use, intuitive, high level) AND guaranteed (type)safety AND high execution performance. As Joe outlines in his blog post (not video!):

At a high level, I classify the language features into six primary categories:

1) Lifetime understanding. C++ has RAII, deterministic destruction, and efficient allocation of objects. C# and Java both coax developers into relying too heavily on the GC heap, and offers only “loose” support for deterministic destruction via IDisposable. Part of what my team does is regularly convert C# programs to this new language, and it’s not uncommon for us to encounter 30-50% time spent in GC. For servers, this kills throughput; for clients, it degrades the experience, by injecting latency into the interaction. We’ve stolen a page from C++ — in areas like rvalue references, move semantics, destruction, references / borrowing — and yet retained the necessary elements of safety, and merged them with ideas from functional languages. This allows us to aggressively stack allocate objects, deterministically destruct, and more.


2) Side-effects understanding. This is the evolution of what we published in OOPSLA 2012, giving you elements of C++ const (but again with safety), along with first class immutability and isolation.


3) Async programming at scale. The community has been ’round and ’round on this one, namely whether to use continuation-passing or lightweight blocking coroutines. This includes C# but also pretty much every other language on the planet. The key innovation here is a composable type-system that is agnostic to the execution model, and can map efficiently to either one. It would be arrogant to claim we’ve got the one right way to expose this stuff, but having experience with many other approaches, I love where we landed.


4) Type-safe systems programming. It’s commonly claimed that with type-safety comes an inherent loss of performance. It is true that bounds checking is non-negotiable, and that we prefer overflow checking by default. It’s surprising what a good optimizing compiler can do here, versus JIT compiling. (And one only needs to casually audit some recent security bulletins to see why these features have merit.) Other areas include allowing you to do more without allocating. Like having lambda-based APIs that can be called with zero allocations (rather than the usual two: one for the delegate, one for the display). And being able to easily carve out sub-arrays and sub-strings without allocating.


5) Modern error model. This is another one that the community disagrees about. We have picked what I believe to be the sweet spot: contracts everywhere (preconditions, postconditions, invariants, assertions, etc), fail-fast as the default policy, exceptions for the rare dynamic failure (parsing, I/O, etc), and typed exceptions only when you absolutely need rich exceptions. All integrated into the type system in a 1st class way, so that you get all the proper subtyping behavior necessary to make it safe and sound.


6) Modern frameworks. This is a catch-all bucket that covers things like async LINQ, improved enumerator support that competes with C++ iterators in performance and doesn’t demand double-interface dispatch to extract elements, etc. To be entirely honest, this is the area we have the biggest list of “designed but not yet implemented features”, spanning things like void-as-a-1st-class-type, non-null types, traits, 1st class effect typing, and more. I expect us to have a few of these in our mid-2014 checkpoint, but not all of them.

What do you think?

For a few years now, I've been working on a textbook introducing the Coq proof assistant. It's been available freely online, and I'd like to announce now the availability of a print version from MIT Press. The site I've linked to includes links to order the book online.

Quick context on why LtUers might be interested in Coq: it supports machine checking of mathematical proofs, including in program verification and PL metatheory, some of the most popular applications of proof assistant technology.

Quick context on what distinguishes this book from other Coq resources: it focuses on the engineering techniques to develop large formal developments effectively. It turns out that there are some reusable lessons on how to write formal proofs so that they tend to continue to work even when theorem statements change over the courses of projects.

I'm grateful to MIT Press for agreeing to this experiment where I may continue distributing free versions of the book online.

Alan Schmitt just posted an invitation to participate in this event which will take place at POPL. I think anyone who can attend should.

R7RS-small draft was ratified by Steering Committee a few days ago at the Scheme 2013 workshop.

The announcement is here.

The final draft is here (PDF).

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.

The Université catholique de Louvain has joined the edX consortium this year, and as part of edX Peter Van Roy is preparing a MOOC (Massive Open Online Course) called Paradigms of Computer Programming starting next February.

As you'd expect the course uses the CTM book and is based on the course Peter has been teaching, it will thus present a multi-paradigm approach to programming and include non-traditional computational models such as the deterministic dataflow model for concurrent programming.

I wonder who will end up signing up for this course. I think the option of auditing might appeal to folks who found CTM interesting but are way beyond the category of beginning programmers for whom the course is officially designed.

This interesting blog post argues that in recent years Python has gained libraries making it the choice language for scientific computing (over MATLAB and R primarily).

I find the details discussed in the post interesting. Two small points that occur to me are that in several domains Mathematica is still the tool of choice. From what I could see nothing free, let alone open source, is even in the same ballpark in these cases. Second, I find it interesting that several of the people commenting mentioned IPython. It seems to be gaining ground as the primary environment many people use.