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.
Cyrus Omar, Darya Kurilova, Ligia Nistor, Benjamin Chung, Alex Potanin, and Jonathan Aldrich, "Safely Composable Type-Specific Languages", ECOOP14.
Programming languages often include specialized syntax for common datatypes (e.g. lists) and some also build in support for specific specialized datatypes (e.g. regular expressions), but user-defined types must use general-purpose syntax. Frustration with this causes developers to use strings, rather than structured data, with alarming frequency, leading to correctness, performance, security, and usability issues. Allowing library providers to modularly extend a language with new syntax could help address these issues. Unfortunately, prior mechanisms either limit expressiveness or are not safely composable: individually unambiguous extensions can still cause ambiguities when used together. We introduce type-specific languages (TSLs): logic associated with a type that determines how the bodies of generic literals, able to contain arbitrary syntax, are parsed and elaborated, hygienically. The TSL for a type is invoked only when a literal appears where a term of that type is expected, guaranteeing non-interference. We give evidence supporting the applicability of this approach and formally specify it with a bidirectionally typed elaboration semantics for the Wyvern programming language.
It is increasingly important for applications to protect user privacy. Unfortunately, it is often non-trivial for programmers to enforce privacy policies. We have developed Jeeves to make it easier for programmers to enforce information flow policies: policies that describe who can see what information flows through a program. Jeeves allows the programmer to write policy-agnostic programs, separately implementing policies on sensitive values from other functionality. Just like Wooster's clever valet Jeeves in Wodehouse's stories, the Jeeves runtime does the hard work, automatically enforcing the policies to show the appropriate output to each viewer.
From what I gather, Jeeves takes Aspect Oriented approach to privacy. This is of course not a new idea. I presume that many of the classic problems with AOP would apply to Jeeves. Likewise, using information flow analysis for handling privacy policies is not an new idea. Combining the two, however, seems like a smart move. Putting the enforcement at the run-time level makes this sound more practical than other ideas I have heard before. Still, I personally think that specifying privacy policies at the end-user level and clarifying the concept of privacy at the normative, legal and conceptual levels are more pressing concerns. Indeed, come to think of it: I don't really recall a privacy breach that was caused by a simple information flow bug. Privacy expectations are broken on purpose by many companies and major data breaches occur when big databases are shared (recall the Netflix Prize thing). Given this, I assume the major use-case is for Apps, maybe even as a technology that someone like Apple could use to enforce the compliance of third-party Apps to their privacy policies.
I haven't looked too closely, so comments from more informed people are welcome.
Jeeves is implemented as an embedded DSL in Scala and Python.
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.
Koka extends the idea of using row polymorphism to encode an effect system and the relations between them. Daan Leijen is the primary researcher behind it and his research was featured previously on LtU, mainly on row polymorphism in the Morrow Language.
So far there's no paper available on the language design, just the slides from a Lang.Next talk (which doesn't seem to have video available at Channel 9), but it's in the program for HOPE 2012.
It's from Twitter, It's open source, It's about Scala. What's not to like?
Software Engineering with Formal Methods: The Development of a Storm Surge Barrier Control System - Seven Myths of Formal Methods Revisited (2001), by Jan Tretmans, Klaas Wijbrans, Michel Chaudron:
Bos is the software system which controls and operates the storm surge barrier in the Nieuwe Waterweg near Rotterdam. It is a complex, safety-critical system of average size, which was developed by CMG Den Haag B.V., commissioned by Rijkswaterstaat (RWS) â€“ the Dutch Ministry of Transport, Public Works and Water Management. It was completed in October 1998 on time and within budget.
CMG used formal methods in the development of the Bos software. This paper discusses the experiences obtained from their use. Some people claim that the use of formal methods helps in developing correct and reliable software, others claim that formal methods are useless and unworkable. Some of these claims have almost become myths. A number of these myths are described and discussed in a famous article: Seven Myths of Formal Methods [Hal90]. The experiences obtained from using formal methods for the development of Bos will be discussed on the basis of this article. We will discuss to what extent these myths are true for the Bos project.
The data for this survey were collected by means of interviews with software engineers working on the Bos project. These include the project manager, designers, implementers and testers, people who participated from the beginning in 1995 until the end in 1998 as well as engineers who only participated in the implementation phase, and engineers with and without previous, large-scale software engineering experience.
This paper concentrates on the experiences of the software engineers with formal methods. These experiences, placed in the context of the seven myths, are described in section 3. This paper does not discuss technical details about the particular formal methods used or the way they were used; see [Kar97, Kar98] for these aspects. Moreover, formal methods were only one technique used in the development of Bos. The overall engineering approach and the way diï¬€erent methods and techniques were combined to assure the required safetycritical quality, are described [WBG98, WB98]. Testing in Bos is described in more detail in [GWT98], while [CTW99] will give a more systematic analysis of the results of the interviews
with the developers.
Discussion of formal methods and verification has come up a few times here on LtU. In line with the recent discussions on the need for more empirical data in our field, this was an interesting case study on the use of formal methods. The seven myths of formal methods are reviewed in light of a real project:
- Myth 1: Formal methods can guarantee that software is perfect
- Myth 2: Formal methods are all about program proving
- Myth 3: Formal methods are only useful for safety-critical system
- Myth 4: Formal methods require highly trained mathematicians
- Myth 5: Formal methods increase the cost of developmen
- Myth 6: Formal methods are unacceptable to users
- Myth 7: Formal methods are not used on real, large-scale software
Extensible Programming with First-Class Cases, by Matthias Blume, Umut A. Acar, and Wonseok Chae:
We present language mechanisms for polymorphic, extensible records and their exact dual, polymorphic sums with extensible first-class cases. These features make it possible to easily extend existing code with new cases. In fact, such extensions do not require any changes to code that adheres to a particular programming style. Using that style, individual extensions can be written independently and later be composed to form larger components. These language mechanisms provide a solution to the expression problem.
We study the proposed mechanisms in the context of an implicitly typed, purely functional language PolyR. We give a type system for the language and provide rules for a 2-phase transformation: first into an explicitly typed Î»-calculus with record polymorphism, and finally to efficient index-passing code. The first phase eliminates sums and cases by taking advantage of the duality with records.
We implement a version of PolyR extended with imperative features and pattern matchingâ€”we call this language MLPolyR. Programs in MLPolyR require no type annotationsâ€”the implementation employs a reconstruction algorithm to infer all types. The compiler generates machine code (currently for PowerPC) and optimizes the representation of sums by eliminating closures generated by the dual construction.
This is an elegant solution to the expression problem for languages with pattern matching. This paper was posted twice in LtU comments, but it definitely deserves its own story. Previous solutions to the exression problem are rather more involved, like Garrigue's use of recursion and polymorphic variants, because they lack support for extensible records which makes this solution so elegant.
Extensible records and first-class cases unify object-oriented and functional paradigms on a deeper level, since they enable first-class messages to be directly encoded. Add a sensible system for dynamics, and I argue you have most of the power people claim of dynamic languages without sacrificing the safety of static typing.
Microsoft has recently detailed their "Compiler as a Service" initiative in a whitepaper. The whitepaper calls the project Roslyn.
Related, IBM sponsors the Eclipse IMP project for its X10 language (and the X10DT). IMP is also used for Eelco Visser's Spoofax IDE and WebDSL IDE.