We've mentioned some empirical studies of programming languages a few times, but I haven't seen a comprehensive list we can use as a reference.
Fortunately, I just came across this pretty decent overview of existing literature on how types impact development. Agree or disagree with Dan Luu's position, the comprehensive list warrants a front-page post in my opinion.
One point worth noting is that all the studies used relatively inexpressive languages with bland type systems, like C and Java, and compared those against typed equivalents. A future study ought to compare a more expressive language, like OCaml, Haskell or F#, which should I think would yield more pertinent data to this age-old debate.
Part of the benefits of types allegedly surround documentation to help refactoring without violating invariants. So another future study I'd like to see is one where participants develop a program meeting certain requirements in their language of choice. They will have as much time as needed to satisfy a correctness test suite. They should then be asked many months later to add a new feature to the program they developed. I expect that the maintenance effort required of a language is more important than the effort required of initial development, because programs change more often than they are written from scratch.
This could be a good thread on how to test the various beliefs surrounding statically typed and dynamically languages. If you have any studies that aren't mentioned above, or some ideas on what would make a good study, let's hear it!
The Royal Society will award Xavier Leroy the Milner Award 2016
... in recognition of his research on the OCaml functional programming language and on the formal verification of compilers.
It is very moving to see how far we have come, from Milner's great ideas of the 1970s to tools as powerful and as widely used as OCaml and Coq.
Michael Greenberg, Kathleen Fisher, and David Walker, "Tracking the Flow of Ideas through the Programming Languages Literature", SNAPL 2015.
How have conferences like ICFP, OOPSLA, PLDI, and POPL evolved over the last 20 years? Did generalizing the Call for Papers for OOPSLA in 2007 or changing the name of the umbrella conference to SPLASH in 2010 have any effect on the kinds of papers published there? How do POPL and PLDI papers compare, topic-wise? Is there related work that I am missing? Have the ideas in O’Hearn’s classic paper on separation logic shifted the kinds of papers that appear in POPL? Does a proposed program committee cover the range of submissions expected for the conference? If we had better tools for analyzing the programming language literature, we might be able to answer these questions and others like them in a data-driven way. In this paper, we explore how topic modeling, a branch of machine learning, might help the programming language community better understand our literature.
The authors have produced some really interesting visualizations of how the topic content of various conferences has evolved over time (it's interesting to note that OOPSLA isn't really about OO software development any more, and that PLDI appears to have seen an increasing emphasis on verification and test generation).
Also of potential interest to LtU readers: there is a prototype tool at http://tmpl.weaselhat.com/ that is based on the work presented in this paper. It allows you to upload a paper PDF, and will return the 10 most closely related papers according to the POPL/PLDI topic model. It could be a handy research tool. But, if nothing else, it's a fun way to see what else is related to a paper you're interested in.
Sergi Valverde and Ricard Solé, "Punctuated equilibrium in the large scale evolution of programming languages", SFI working paper 2014-09-030
Here we study the large scale historical development of programming languages, which have deeply marked social and technological advances in the last half century. We analyse their historical connections using network theory and reconstructed phylogenetic networks. Using both data analysis and network modelling, it is shown that their evolution is highly uneven, marked by innovation events where new languages are created out of improved combinations of different structural components belonging to previous languages. These radiation events occur in a bursty pattern and are tied to novel technological and social niches. The method can be extrapolated to other systems and consistently captures the major classes of languages and the widespread horizontal design exchanges, revealing a punctuated evolutionary path.
The results developed here are perhaps not that surprising to people familiar with the history of programming languages. But it's interesting to see it all formalized and analyzed.
Eugenia Cheng's new popular coscience book is out, in the U.K. under the title Cakes, Custard and Category Theory: Easy recipes for understanding complex maths, and in the U.S. under the title How to Bake Pi: An Edible Exploration of the Mathematics of Mathematics:
Most people imagine maths is something like a slow cooker: very useful, but pretty limited in what it can do. Maths, though, isn't just a tool for solving a specific problem - and it's definitely not something to be afraid of. Whether you're a maths glutton or have forgotten how long division works (or never really knew in the first place), the chances are you've missed what really makes maths exciting. Calling on a baker's dozen of entertaining, puzzling examples and mathematically illuminating culinary analogies - including chocolate brownies, iterated Battenberg cakes, sandwich sandwiches, Yorkshire puddings and Möbius bagels - brilliant young academic and mathematical crusader Eugenia Cheng is here to tell us why we should all love maths.
From simple numeracy to category theory ('the mathematics of mathematics'), Cheng takes us through the joys of the mathematical world. Packed with recipes, puzzles to surprise and delight even the innumerate, Cake, Custard & Category Theory will whet the appetite of maths whizzes and arithmophobes alike. (Not to mention aspiring cooks: did you know you can use that slow cooker to make clotted cream?) This is maths at its absolute tastiest.
Cheng, one of the Catsters, gives a guided tour of mathematical thinking and research activities, and through the core philosophy underlying category theory. This is the kind of book you can give to your grandma and grandpa so they can boast to their friends what her grandchildren are doing (and bake you a nice dessert when you come and visit :) ). A pleasant weekend reading.
Don Syme receives the Royal Academy of Engineering's Silver Medal for his work on F#. The citation reads:
F# is known for being a clear and more concise language that interoperates well with other systems, and is used in applications as diverse asanalysing the UK energy market to tackling money laundering. It allows programmers to write code with fewer bugs than other languages, so users can get their programme delivered to market both rapidly and accurately. Used by major enterprises in the UK and worldwide, F# is both cross-platform and open source, and includes innovative features such as unit-of-measure inference, asynchronous programming and type providers, which have in turn influenced later editions of C# and other industry languages.
These are sad news indeed. I am sure almost everyone here read at least one paper by Paul and many knew him personally. When I just started thinking about programming languages I was fascinated by DSLs and his work was simply inspiring. His voice will be missed.
Discussions of Paul Hudak's work
Update:There is some confusion about the situation. Please see the comments for further information.
Presented annually to the author of the outstanding doctoral dissertation in the area of Programming Languages. The award includes a prize of $1,000. The winner can choose to receive the award at ICFP, OOPSLA, POPL, or PLDI.
I guess it is fairly obvious why professors should propose their students (the deadline is January 4th 2015). Newly minted PhD should, for similar reasons, make sure their professors are reminded of these reasons. I can tell you that the competition is going to be tough this year; but hey, you didn't go into programming language theory thinking it is going to be easy, did you?
Zélus : A Synchronous Language with ODEs
Timothy Bourke, Marc Pouzet
Zélus is a new programming
language for modeling systems that mix discrete logical time and
continuous time behaviors. From a user's perspective, its main
originality is to extend an existing Lustre-like
synchronous language with Ordinary Differential Equations (ODEs). The
extension is conservative: any synchronous program expressed as
data-flow equations and hierarchical automata can be composed
arbitrarily with ODEs in the same source code.
A dedicated type system and causality analysis ensure that all
discrete changes are aligned with zero-crossing events so that no side
effects or discontinuities occur during integration. Programs are
statically scheduled and translated into sequential code that, by
construction, runs in bounded time and space. Compilation is effected
by source-to-source translation into a small synchronous subset which
is processed by a standard synchronous compiler architecture. The
resultant code is paired with an off-the-shelf numeric solver.
We show that it is possible to build a modeler for explicit hybrid
systems à la Simulink/Stateflow on top of
an existing synchronous language, using it both as a semantic basis
and as a target for code generation.
Synchronous programming languages (à la Lucid
Synchrone) are language designs for reactive systems with discrete
time. Zélus extends them gracefully to hybrid discrete/continuous
systems, to interact with the physical world, or simulate it -- while
preserving their strong semantic qualities.
The paper is short (6 pages) and centered around examples rather than
the theory -- I enjoyed it. Not being familiar with the domain, I was
unsure what the "zero-crossings" mentioned in the introductions are,
but there is a good explanation further down in the paper:
The standard way to detect events in a numeric solver is
via zero-crossings where a solver monitors expressions for changes in
sign and then, if they are detected, searches for a more precise
instant of crossing.
The Zélus website has a 'publications' page with
more advanced material, and an 'examples' page with
At the same time, Flow is a gradual type system. Any parts of your program that are dynamic in nature can easily bypass the type checker, so you can mix statically typed code with dynamic code.
Flow also supports a highly expressive type language. Flow types can express much more fine-grained distinctions than traditional type systems. For example, Flow helps you catch errors involving null, unlike most type systems.
Read more here.
Here's the announcement from Facebook.