Standard Ml

A weak reference is a reference to an object that is not followed by the pointer tracer when garbage collection is called. That is, a weak reference cannot prevent the object it references from being garbage collected. Weak references remain a troublesome programming feature largely because there is not an accepted, precise semantics that describes their behavior (in fact, we are not aware of any formalization of their semantics). The trouble is that weak references allow reachable objects to be garbage collected, therefore allowing garbage collection to influence the result of a program. Despite this difficulty, weak references continue to be used in practice for reasons related to efficient storage management, and are included in many popular programming languages (Standard ML, Haskell, OCaml, and Java). We give a formal semantics for a calculus called λweak that includes weak references and is derived from Morrisett, Felleisen, and Harper's λgc. λgc formalizes the notion of ...

Many modern programming languages support basic generics, sufficient to implement type-safe polymorphic containers. Some languages have moved beyond this basic support, and in doing so have enabled a broader, more powerful form of generic programming. This paper reports on a comprehensive comparison of facilities for generic programming in eight programming languages: C++, Standard ML, Objective Caml, Haskell, Eiffel, Java, C# (with its proposed generics extension), and Cecil. By implementing a substantial example in each of these languages, we illustrate how the basic roles of generic programming can be represented in each language. We also identify eight language properties that support this broader view of generic programming: support for multi-type concepts, multiple constraints on type parameters, convenient associated type access, constraints on associated types, retroactive modeling, type aliases, separate compilation of algorithms and data structures, and implicit argument t...

We describe the methodology and current features for ML2000, a new-generation design of ML. ML2000 adds a number of features to Standard ML and Caml, providing better support for extensibility and code reuse, while also fixing latent problems. Although none of the features is particularly novel on its own, the combination of features and design methodology are.

We present the EWD design environment and methodology, a modeling and simulation framework suited for complex and heterogeneous embedded systems with varying degrees of expressibility and modeling fidelity. This environment promotes the use of multiple models of computation (MoCs) to support heterogeneity and metamodeling for conformance tests of syntactic and static semantics during the process of modeling. Therefore, EWD is

Advanced programming languages such as Standard ML have rarely been used for systems programming tasks such as operating systems and network communications. In order to understand more fully the requirements of systems programming, we have implemented a suite of industry-standard network communication protocols in a completely type-safe extension of Standard ML. While the implementation has only recently become operational, we already observe acceptable communications throughput. We make careful use of the Standard ML modules system, with the core component of the implementation being a signature which is generic to all communications protocols. This generic protocol is then specialized for specific protocols, and these are implemented by functors parameterized by generic protocols. This leads naturally to a layered system structure and also provides an important and useful “mix-and-match” capability in composing protocols into complex networking systems.We have found the advanced features of Standard ML, in particular the modules system, static typing, and higher-order functions, to be extremely useful in building complex communications systems. The type compatibility of the various components of a system is guaranteed by the compiler. Furthermore, we find it significant that most of the information needed to understand the structure and interactions in our code can be obtained from a study of the signatures alone. Perhaps most important is that we have been able to use the expressive power of Standard ML modules to give concrete expression to previously ad hoc system-structuring concepts developed by other researchers in the field of network communications. For language designers and implementors, our experience has also pointed out specific areas for further work that may lead to advanced languages that are useful for systems programming.

We describe a method of measuring lifetime characteristics of heap objects, and discuss ways in which such quantitative object behaviour measurements can help improve language implementations, especially garbage collection performance. For Standard ML of New Jersey, we find that certain primary aspects of object behaviour are qualitatively the same across benchmark programs, in particular the rapid object decay. We show that the heap-only allocation implementation model is the cause of this similarity. We confirm the weak generational hypothesis for SML/NJ and discuss garbage collector configuration tuning. Our approach is to obtain object statistics directly from program execution, rather than simulation, for reasons of simplicity and speed. Towards this end, we exploit the flexibility of the garbage collector toolkit as a measurement tool. Careful numerical analysis of the acquired data is necessary to arrive at relevant object lifetime measures. This study fills a gap in quantita...

We reflect on our experiences from work on the design and semantic underpinnings of Extended ML, a specification language which supports the specification and formal development of Standard ML programs. Our aim is to isolate problems and issues that are intrinsic to the general enterprise of designing a specification language for use with a given programming language. Consequently the lessons learned go far beyond our original aim of designing a specification language for ML.

Moscow ML implements Standard ML (SML), as defined in the 1997 Definition of Standard ML, including the SML Modules language and some extensions. Moreover, Moscow ML supports most required parts of the SML Basis Library. It supports separate compilation and the generation of stand-alone executables. This document explains how to use the Moscow ML system. A companion document, the Moscow ML Language Overview, summarizes Moscow ML syntax and the most common built-in functions [9]. Another companion document, the Moscow ML Library Documentation, describes in detail all Moscow ML library modules [10].

Abstract Handling exceptional occurrences during computation is a problem in most functional programming languages, even where the computation is eager and sequential. A version of the error value method is presented which allows lazy computation with deterministic semantics for parallel evaluation even in the presence of errors. The realization of this technique is illustrated by reference PSML, a referentially transparent variant of standard ML designed for parallel evaluation

The FoxNet is an implementation of the standard TCP/IP networking protocol stack using the Standard ML (SML) language. SML is a type-safe programming language with garbage collection, a unique and advanced module system, and machine-independent semantics. The FoxNet is a user-space implementation of TCP/IP that is built in SML by composing modular protocol elements; each element independently implements one of the standard protocols. One specific combination of these elements implements the standard ...

A weak reference is a reference to an object that is not followed by the pointer tracer when garbage collection is called. That is, a weak reference cannot prevent the object it references from being garbage collected. Weak references remain a troublesome programming feature largely because there is not an accepted, precise semantics that describes their behavior (in fact, we are not aware of any formalization of their semantics). The trouble is that weak references allow reachable objects to be garbage collected, therefore allowing garbage collection to influence the result of a program. Despite this difficulty, weak references continue to be used in practice for reasons related to efficient storage management, and are included in many popular programming languages (Standard ML, Haskell, OCaml, and Java). We give a formal semantics for a calculus called λweak that includes weak references and is derived from Morrisett, Felleisen, and Harper's λgc. λgc formalizes the notion of ...

This paper describes a memory discipline that combines region-based memory management and copying garbage collection by extending Cheney's copying garbage collection algorithm to work with regions. The paper presents empirical evidence that region inference very significantly reduces the number of garbage collections; and evidence that the fastest execution is obtained by using regions alone, without garbage collection. The memory discipline is implemented for Standard ML in the ML Kit compiler and measurements show that for a variety of benchmark programs, code generated by the compiler is as efficient, both with respect to execution time and memory usage, as programs compiled with Standard ML of New Jersey, another state-of-the-art Standard ML compiler.