Existing languages provide good support for typeful programming of standalone programs. In a distributed system, however, there may be interaction between multiple instances of many distinct programs, sharing some (but not necessarily all) of their module structure, and with some instances rebuilt with new versions of certain modules as time goes on. In this paper we discuss programminglanguage support for such systems, focussing on their typing and naming issues.We describe an experimental language, Acute, which extends an ML core to support distributed development, deployment, and execution, allowing type-safe interaction between separately-built programs. The main features are: (1) type-safe marshalling of arbitrary values; (2) type names that are generated (freshly and by hashing) to ensure that type equality tests suffice to protect the invariants of abstract types, across the entire distributed system; (3) expression-level names generated to ensure that name equality tests suffice for type-safety of associated values, e.g. values carried on named channels; (4) controlled dynamic rebinding of marshalled values to local resources; and (5) thunkification of threads and mutexes to support computation mobility.These features are a large part of what is needed for typeful distributed programming. They are a relatively lightweight extension of ML, should be efficiently implementable, and are expressive enough to enable a wide variety of distributed infrastructure layers to be written as simple library code above the byte-string network and persistent store APIs. This disentangles the language runtime from communication intricacies. This paper highlights the main design choices in Acute. It is supported by a full language definition (of typing, compilation, and operational semantics), by a prototype implementation, and by example distribution libraries.

We present a sound type-based 'usage analysis' for a realistic lazy functional language. Accurate information on the usage of program subexpressions in a lazy functional language permits a compiler to perform a number of useful optimisations. However, existing analyses are either ad-hoc and approximate, or defined over restricted languages.Our work extends the Once Upon A Type system of Turner, Mossin, and Wadler (FPCA'95). Firstly, we add type polymorphism, an essential feature of typed functional programming languages. Secondly, we include general Hsskell-style user-defined algebraic data types. Thirdly, we explain and solve the 'poisoning problem', which causes the earlier analysis to yield poor results. Interesting design choices turn up in each of these areas.Our analysis is sound with respect to a Launchbury-style operational semantics, and it is straightforward to implement. Good results have been obtained from a prototype implementation, and we are currently integrating the system into the Glasgow Haskell Compiler.

Most programming languages adopt static binding, but for distributed programming an exclusive reliance on static binding is too restrictive: dynamic binding is required in various guises, for example when a marshalled value is received from the network, containing identifiers that must be rebound to local resources. Typically it is provided only by ad-hoc mechanisms that lack clean semantics.In this paper we adopt a foundational approach, developing core dynamic rebinding mechanisms as extensions to simply-typed callby-value λ-calculus. To do so we must first explore refinements of the call-by-value reduction strategy that delay instantiation, to ensure computations make use of the most recent versions of rebound definitions. We introduce redex-time and destruct-time strategies. The latter forms the basis for a λmarsh calculus that supports dynamic rebinding of marshalled values, while remaining as far as possible statically-typed. We sketch an extension of λmarsh with concurrency and communication, giving examples showing how wrappers for encapsulating untrusted code can be expressed. Finally, we show that a high-level semantics for dynamic updating can also be based on the destruct-time strategy, defining a λupdate calculus with simple primitives to provide type-safe updating of running code. We thereby establish primitives and a common semantic foundation for a variety of real-world dynamic rebinding requirements.

Type abstraction is a key feature of ML-like languages for writing large programs. Marshalling is necessary for writing distributed programs, exchanging values via network byte-streams or persistent stores. In this paper we combine the two, developing compile-time and run-time semantics for marshalling, that guarantee abstraction-safety between separately-built programs.We obtain a namespace for abstract types that is global, i.e. meaningful between programs, by hashing module declarations. We examine the scenarios in which values of abstract types are communicated from one program to another, and ensure, by constructing hashes appropriately, that the dynamic and static notions of type equality mirror each other. We use singleton kinds to express abstraction in the static semantics; abstraction is tracked in the dynamic semantics by coloured brackets. These allow us to prove preservation, erasure, and coincidence results. We argue that our proposal is a good basis for extensions to existing ML-like languages, pragmatically straightforward for language users and for implementors.

Type abstraction is a key feature of ML-like languages for writing large programs. Marshalling is necessary for writing distributed programs, exchanging values via network byte-streams or persistent stores. In this paper we combine the two, developing compile-time and run-time semantics for marshalling, that guarantee abstraction-safety between separately-built programs.We obtain a namespace for abstract types that is global, i.e. meaningful between programs, by hashing module declarations. We examine the scenarios in which values of abstract types are communicated from one program to another, and ensure, by constructing hashes appropriately, that the dynamic and static notions of type equality mirror each other. We use singleton kinds to express abstraction in the static semantics; abstraction is tracked in the dynamic semantics by coloured brackets. These allow us to prove preservation, erasure, and coincidence results. We argue that our proposal is a good basis for extensions to existing ML-like languages, pragmatically straightforward for language users and for implementors.

Most programming languages adopt static binding, but for distributed programming an exclusive reliance on static binding is too restrictive: dynamic binding is required in various guises, for example, when a marshalled value is received from the network, containing identifiers that must be rebound to local resources. Typically, it is provided only by ad hoc mechanisms that lack clean semantics. In this paper, we adopt a foundational approach, developing core dynamic rebinding mechanisms as extensions to the simply typed call-byvalue λ calculus. To do so, we must first explore refinements of the call-by-value reduction strategy that delay instantiation, to ensure computations make use of the most recent versions of rebound definitions. We introduce redex-time and destruct-time strategies. The latter forms the basis for a λ marsh calculus that supports dynamic rebinding of marshalled values, while remaining as far as possible statically typed. We sketch an extension of λ marsh with concurrency and communication, giving examples showing how wrappers for encapsulating untrusted code can be expressed. Finally, we show that a high-level semantics for dynamic updating can also be based on the destruct-time strategy, defining a λ update calculus with simple primitives to provide type-safe updating of running code. We show how the ideas of this simple calculus extend to more real-world, module-level dynamic updating in the style of Erlang. We thereby establish primitives and a common semantic foundation for a variety of real-world dynamic rebinding requirements.

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