Object-Functional

Pure Subtype Systems

Pure Subtype Systems, by DeLesley S. Hutchins:

This paper introduces a new approach to type theory called pure subtype systems. Pure subtype systems differ from traditional approaches to type theory (such as pure type systems) because the theory is based on subtyping, rather than typing. Proper types and typing are completely absent from the theory; the subtype relation is defined directly over objects. The traditional typing relation is shown to be a special case of subtyping, so the loss of types comes without any loss of generality.

Pure subtype systems provide a uniform framework which seamlessly integrates subtyping with dependent and singleton types. The framework was designed as a theoretical foundation for several problems of practical interest, including mixin modules, virtual classes, and feature-oriented programming.

The cost of using pure subtype systems is the complexity of the meta-theory. We formulate the subtype relation as an abstract reduction system, and show that the theory is sound if the underlying reductions commute. We are able to show that the reductions commute locally, but have thus far been unable to show that they commute globally. Although the proof is incomplete, it is “close enough” to rule out obvious counter-examples. We present it as an open problem in type theory.

A thought-provoking take on type theory using subtyping as the foundation for all relations. He collapses the type hierarchy and unifies types and terms via the subtyping relation. This also has the side-effect of combining type checking and partial evaluation. Functions can accept "types" and can also return "types".

Of course, it's not all sunshine and roses. As the abstract explains, the metatheory is quite complicated and soundness is still an open question. Not too surprising considering type checking Type:Type is undecidable.

Hutchins' thesis is also available for a more thorough treatment. This work is all in pursuit of Hitchens' goal of feature-oriented programming.

Types for Flexible Objects

Types for Flexible Objects, by Pottayil Harisanker Menon, Zachary Palmer, Alexander Rozenshteyn, Scott Smith:

Scripting languages are popular in part due to their extremely flexible objects. These languages support numerous object features, including dynamic extension, mixins, traits, and first-class messages. While some work has succeeded in typing these features individually, the solutions have limitations in some cases and no project has combined the results.

In this paper we define TinyBang, a small typed language containing only functions, labeled data, a data combinator, and pattern matching. We show how it can directly express all of the aforementioned flexible object features and still have sound typing. We use a subtype constraint type inference system with several novel extensions to ensure full type inference; our algorithm refines parametric polymorphism for both flexibility and efficiency. We also use TinyBang to solve an open problem in OO literature: objects can be extended after being messaged without loss of width or depth subtyping and without dedicated metatheory. A core subset of TinyBang is proven sound and a preliminary implementation has been constructed.

An interesting paper I stumbled across quite by accident, it purports quite an ambitious set of features: generalizing previous work on first-class cases while supporting subtyping, mutation, and polymorphism all with full type inference, in an effort to match the flexibility of dynamically typed languages.

It does so by introducing a host of new concepts that are almost-but-not-quite generalizations of existing concepts, like "onions" which are kind of a type-indexed extensible record, and "scapes" which are sort of a generalization of pattern matching cases.

Instead of approaching objects via a record calculus, they approach it using its dual as variant matching. Matching functions then have degenerate dependent types, which I first saw in the paper Type Inference for First-Class Messages with Match-Functions. Interesting aside, Scott Smith was a coauthor on this last paper too, but it isn't referenced in the "flexible objects" paper, despite the fact that "scapes" are "match-functions".

Overall, quite a dense and ambitous paper, but the resulting TinyBang language looks very promising and quite expressive. Future work includes making the system more modular, as it currently requires whole program compilation, and adding first-class labels, which in past work has led to interesting results as well. Most work exploiting row polymorphism is particularly interesting because it supports efficient compilation to index-passing code for both records and variants. It's not clear if onions and scapes are also amenable to this sort of translation.

Edit: a previous paper was published in 2012, A Practical, Typed Variant Object Model -- Or, How to Stand On Your Head and Enjoy the View. BigBang is their language that provides syntactic sugar on top of TinyBang.

Edit 2: commas fixed, thanks!

Dependent Types for JavaScript

Dependent Types for JavaScript, by Ravi Chugh, David Herman, Ranjit Jhala:

We present Dependent JavaScript (DJS), a statically-typed dialect of the imperative, object-oriented, dynamic language. DJS supports the particularly challenging features such as run-time type-tests, higher-order functions, extensible objects, prototype inheritance, and arrays through a combination of nested refinement types, strong updates to the heap, and heap unrolling to precisely track prototype hierarchies. With our implementation of DJS, we demonstrate that the type system is expressive enough to reason about a variety of tricky idioms found in small examples drawn from several sources, including the popular book JavaScript: The Good Parts and the SunSpider benchmark suite.

Some good progress on inferring types for a very dynamic language. Explicit type declarations are placed in comments that start with "/*:".

/*: x∶Top → {ν ∣ite Num(x) Num(ν) Bool(ν)} */
function negate(x) {
    if (typeof x == "number") { return 0 - x; }
    else { return !x; }
}

Tool Demo: Scala-Virtualized

Tool Demo: Scala-Virtualized

This paper describes Scala-Virtualized, which extends the Scala language and compiler with a small number of features that enable combining the benefits of shallow and deep embeddings of DSLs. We demonstrate our approach by showing how to embed three different domain-specific languages in Scala. Moreover, we summarize how others have been using our extended compiler in their own research and teaching. Supporting artifacts of our tool include web-based tutorials, nightly builds, and an Eclipse update site hosting an up-to-date version of the Scala IDE for Eclipse based on the Virtualized Scala compiler and standard library.

Scala has always had a quite good EDSL story thanks to implicits, dot- and paren-inference, and methods-as-operators. Lately there are proposals to provide it with both macros-in-the-camlp4-sense and support for multi-stage programming. This paper goes into some depth on the foundations of the latter subject.

Deca, an LtU-friendly bare metal systems programming language

The Deca programming language is "a language designed to provide the advanced features of sophisticated, high-level programming languages while still programming as close as possible to the bare metal. It brings in the functional, object-oriented, and generic programming paradigms without requiring a garbage collector or a threading system, so programmers really only pay in performance for the features they use." The latter link provides a list of features that Deca does, will, and won't provide. Features provided include type inference, universally- and existentially- quantified types, and "a strong region-and-effect system that prohibits unsafe escaping pointers and double-free errors".

The Deca language and ideas behind it are documented in a thesis, The design and implementation of a modern systems programming language (PDF):

Low-level systems programming has remained one of the most consistently difficult tasks in software engineering, since systems programmers must routinely deal with details that programming-language and systems researchers have preferred to abstract away. At least partially, the difficulty arises from not applying the state of the art in programming-languages research to systems programming. I therefore describe the design and implementation of Deca, a systems language based on modern PL principles. Deca makes use of decades in programming-languages research, particularly drawing from the state of the art in functional programming, type systems, extensible data-types and subroutines, modularity, and systems programming-languages research. I describe Deca's feature-set, examine the relevant literature, explain design decisions, and give some of the implementation details for Deca language features. I have been writing a compiler for Deca to translate it into machine code, and I describe the overall architecture of this compiler and some of its details.

The source code for the Deca compiler, decac, is available here. The compiler is implemented in Scala and generates LLVM bytecode. (The author points out in the comments below that this implementation is a work in progress.)

The author of Deca is LtU member Eli Gottlieb, who back in 2008 posted in the forum asking for feedback on his language: Practical Bits of Making a Compiler for a New Language.

There's some more discussion of Deca over at Hacker News.

Thorn

Thorn is

a dynamically-typed concurrent language in which lightweight isolated processes communicate by message passing. Thorn includes powerful aggregate data types, a class-based object system, first-class functions, an expressive module system, and a variety of features supporting the gradual evolution of prototype scripts into robust programs.

Thorn is implemented by a compiler targeting the JVM and a Java interpreter, and syntactically resembles Scala, at least superficially.

One of those "features" is a unique (as far as I know) soft type system:

In Thorn, the type dyn (for dynamic) is assumed as default (and never written explicitly). At the other extreme, Thorn supports concrete types, as used in statically typed programming languages. A variable of a concrete type T is guaranteed to refer to a value of that type (or a subtype). [...] While concrete types help with performance and correctness, they introduce restrictions on how software can be used and make rapid development more difficult; scripting languages do not favor them.

As an intermediate step between the two, we propose like types, getting some of the safety of concrete types while retaining the flexibility of dynamic types. Concrete types for var x:T or fun f(x:T) are used in two main places. At a method call x.m(), a static type check ensures that x actually has an m method. At a binding or assignment, like x := y; or f(y), a static type check can ensure that y's value makes sense to assign to x, can reject it entirely, or can inspire a dynamic check. Like types, var x: like T or fun f(x:like T), give the expressive power of concrete type checks on method calls, but do not constrain binding or
assignment. They do require runtime checks and thus may cause programs to fail with runtime type errors: sometimes fewer and never more than dynamic types do.

Concurrency is also a little odd:

Every component (marked by the keyword spawn) runs in a different JVM. Component handles contains sufficient information to identify the node and port on which the component runs.

A couple of papers are linked to the home page; "Thorn - Robust, Concurrent, Extensible Scripting on the JVM", by Bard Bloom, et. al., is a general description of the language, from which come the quotes above; and "Integrating Typed and Untyped Code in a Scripting Language", by Tobias Wrigstad, et. al., with more information about like types.

I have not seen Thorn here before. Apologies if I have just missed it.

Type Classes as Objects and Implicits

Type Classes as Objects and Implicits

Type classes were originally developed in Haskell as a disciplined alternative to ad-hoc polymorphism. Type classes have been shown to provide a type-safe solution to important challenges in software engineering and programming languages such as, for example, retroactive extension of programs. They are also recognized as a good mechanism for concept-based generic programming and, more recently, have evolved into a mechanism for type-level computation. This paper presents a lightweight approach to type classes in object-oriented (OO) languages with generics using the CONCEPT pattern and implicits (a type-directed implicit parameter passing mechanism).

This paper also shows how Scala’s type system conspires with implicits to enable, and even surpass, many common extensions of the Haskell type class system, making Scala ideally suited for generic programming in the large.

Martin Odersky and team's design decisions around how to do type classes in a unified OO and FP language continue to bear fascinating fruit. Implicits look less and less like "poor man's type classes," and more and more like an improvement upon type classes, in my opinion given a quick read of this paper.

Objects to Unify Type Classes and GADTs

Objects to Unify Type Classes and GADTs, by Bruno C. d. S. Oliveira and Martin Sulzmann:

We propose an Haskell-like language with the goal of unifying type classes and generalized algebraic datatypes (GADTs) into a single class construct. We treat classes as first-class types and we use objects (instead of type class instances and data constructors) to define the values of those classes. We recover the ability to define functions by pattern matching by using sealed classes. The resulting language is simple and intuitive and it can be used to define, with similar convenience, the same programs that we would define in Haskell. Furthermore, unlike Haskell, dictionaries (or
objects) can be explicitly (as well as implicitly) passed to functions and we can program in a simple object-oriented style directly.

A very interesting paper on generalizing and unifying type classes and GADTs. Classes are now first-class values, resulting in a language that resembles a traditional, albeit more elegant, object-oriented language, and which supports a form of first-class "lightweight modules".

The language supports the traditional use of implicit type class dispatch, but also supports explicit dispatch, unlike Haskell. The authors suggest this could eliminate much of the duplication in the Haskell standard library of functions that take a type class or an explicit function, eg. insert/insertBy and sort/sortBy, although some syntactic sugar is needed to make this more concise.

Classes are open to extension by default, although a class can also be explicitly specified as "sealed", in which case extension is forbidden and you can pattern match on the cases. Furthermore, GADTs can now also carry methods, thus introducing dispatch to algebraic types. This fusion does not itself solve the expression problem, though it does ease the burden through the first-class support of both types of extension. You can see the Scala influences here.

I found this paper via the Haskell sub-reddit, which also links to a set of slides. The authors acknowledge Scala as an influence, and as future work, suggest extensions like type families and to support more module-like features, such as nesting and opaque types.

ActorScript(TM): Industrial strength integration of local and nonlocal concurrency for Client-cloud Computing

ActorScript(TM): Industrial strength integration of local and nonlocal concurrency for Client-cloud Computing by Carl Hewitt, 2009.
ActorScript is based on a mathematical model of computation that treats “Actors” as the universal primitives of concurrent digital computation [Hewitt, Bishop, and Steiger 1973; Hewitt 1977]. Actors been used both as a framework for a theoretical understanding of concurrency, and as the theoretical basis for several practical implementations of concurrent systems.
I hope I do not need to introduce Carl Hewitt or his Actor model. This paper is a modern attempt to expose that model via a practical PL.

Factor Mixins

Mixins, a very interesting post from Slava Pestov's Factor blog.

Factor's object system allows the following operations without forcing unnecessary coupling:

* Defining new operations over existing types
* Defining existing operations over new types
* Importing existing mixin method suites into new types
* Importing new method suites into existing types
* Defining new operations in existing mixin method suites
* Defining new mixin method suites which implement existing operations

That's pretty much what I want from an object-functional language.

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