Object-oriented units of measurement

ACM SIGPLAN Notices, 2008

X10 is a modern object-oriented language designed for productivity and performance in concurrent and distributed systems. In this setting, dependent types offer significant opportunities for detecting design errors statically, documenting design decisions, eliminating costly runtime checks (e.g., for array bounds, null values), and improving the quality of generated code. We present the design and implementation of constrained types, a natural, simple, clean, and expressive extension to object-oriented programming: A type C(:c) names a class or interface C and a constraint c on the immutable state of C and in-scope final variables. Constraints may also be associated with class definitions (representing class invariants) and with method and constructor definitions (representing preconditions). Dynamic casting is permitted. The system is parametric on the underlying constraint system: the compiler supports a simple equalitybased constraint system but, in addition, supports extension with new constraint systems using compiler plugins.

2021

In scientific and engineering applications, physical quantities expressed as units of measurement (UoM) are used regularly. If the algebraic properties of a system’s UoM information are incorrectly handled at run-time then catastrophic problems can arise. Much work has gone into creating libraries, languages and tools to ensure developers can leverage UoM information in their designs and codes. While there are technical solutions that allow units of measurement to be specified at both the model and code level, a broader assessment of their strengths and weaknesses has not been undertaken. Inspired by a survey of practitioners, we review four competing methods that support unit checking of code bases. The most straightforward solution is for the programming language to Natively support UoM as this allows for efficient unit conversion and static checking. Alas, none of the mainstream languages provide such support. Libraries might seem compelling, and all popular programming languages...

1996

Object-oriented programming languages oopl's provide important support for today's large-scale software development projects. Unfortunately, the typing issues arising from the object-oriented features that provide this support are substantially di erent from those that arise in typing procedural languages. Attempts to adapt procedural type systems to object-oriented languages have resulted in languages like Simula, C++, and Object Pascal, which h a v e o v erly restrictive t ype systems. Among other things, the rigidity of these systems frequently force programmers to use type casts, which are a notorious source of hard-to-nd bugs. These restrictive type systems also mean that many programming idioms common to untyped oopl's such as Smalltalk are not typeable. One source of this lack of exibility is the con ation of subtyping and inheritance. Brie y, inheritance is an implementation technique in which new object de nitions may be given as incremental modi cations to existing de nitions. Subtyping concerns substitutivity: when can one object safely replace another? By tying subtyping to inheritance, existing oopl's greatly reduce the number of legal substitutions in a system, and hence their degree of polymorphism. Attempts to x this rigidity h a v e resulted in unsound type systems, most notably Ei el's.

Our objective is to understand the notion of type in programming languages, present a model of typed, polymorphic programming languages that reflects recent research in type theory, and examine the relevance of recent research to the design of practical programming languages. Object-oriented languages provide both a framework and a motivation for exploring the interaction among the concepts of type, data abstraction, and polymorphism, since they extend the notion of type to data abstraction and since type inheritance is an important form of polymorphism. We develop a X-calculus-based model for type systems that allows us to explore these interactions in a simple setting, unencumbered by complexities of production programming languages. The evolution of languages from untyped universes to monomorphic and then polymorphic type systems is reviewed. Mechanisms for polymorphism such as overloading, coercion, subtyping, and parameterization are examined. A unifying framework for polymorphic type systems is developed in terms of the typed A-calculus augmented to include binding of types by quantification as well as binding of values by abstraction. The typed X-calculus is augmented by universal quantification to model generic functions with type parameters, existential quantification and packaging (information hiding) to model abstract data types, and bounded quantification to model subtypes and type inheritance. In this way we obtain a simple and precise characterization of a powerful type system that includes abstract data types, parametric polymorphism, and multiple inheritance in a single consistent framework. The mechanisms for type checking for the augmented X-calculus are discussed. The augmented typed X-calculus is used as a programming language for a variety of illustrative examples. We christen this language Fun because fun instead of X is the functional abstraction keyword and because it is pleasant to deal with. Fun is mathematically simple and can serve as a basis for the design and implementation of real programming languages with type facilities that are more powerful and expressive than those of existing programming languages. In particular, it provides a basis for the design of strongly typed object-oriented languages.

Software: Practice and Experience, 2008

When physical quantities are used in programs they are typically represented as raw numbers, with the units in which they were measured only being given in comments, if at all. This can lead to errors from the use of dimensionally inconsistent expressions, or the comparison of two quantities of the same dimension but measured in different units, which are not discovered until run time. Any program working with the physical world has this issue, with scientific modelling being a major application. Implementors of models have the time-consuming and error-prone task of adding in dynamic units checks and conversions manually. Most existing programming languages do not provide support for representing units explicitly (although extensions to some have been proposed). With the advent of domain-specific modelling languages, incorporating code generation techniques, we propose checking physical units at the level of the modelling language, removing the need for such a support in the underlying implementation language. We present our work in the context of one such modelling language: CellML, developed at the University of Auckland with a focus on modelling biological systems. We have developed an intuitive algorithm for performing automatic conversions between quantities measured in different units. It both requires fewer conversion operations than current approaches and makes more sensible choices about which quantities to convert. Uniquely, by using partial evaluation techniques it is also capable of dealing robustly with quantities raised to arbitrary powers, even where the exponent is given by an expression. We demonstrate our algorithm on various examples. of mathematical models of reality is well known: similarly to the use of types for catching nonsensical programs, we know that an equation cannot be correct if constraints on the dimensions of the quantities involved are not met. For example, if a length and a time are added together, we know that the model must be incorrect in some fashion. Similarly if lengths measured in metres and feet are compared without a suitable conversion then simulations of the model are unlikely to give sensible results.

Several software quality metrics have been proposed during the last decades to reduce risks and faultiness during software development. Despite these many efforts, most defined measurements fail to reach a satisfactory level of performance due to the ambiguities detected in the way their definitions are expressed and later on interpreted. The paper introduces a formal extension of a well-known library of measures named FLAME. While this library is expressed using the semi-formal language OCL (Object Constraint Language) upon the UML meta-model, our extension make use of formal methods to provide a more precise and accurate measurements by proposing a formal definitions of software metrics upon a formal expression of the UML metamodel. Unlike the original definition of the library, this extension supports formal proofs and guarantees a unique interpretation which allows the built of tools support.

Theoretical Computer Science, 1995

In [3] we defined the)`&-calculus, a simple extension of the typed),-calculus to model typed object-oriented languages. To develop a formal study of type systems for object-oriented languages we define, in this paper, a metalanguage based on)`& and we show by a practical example how to use it to prove properties of a language. To this purpose we define a toy object-oriented language and its type-checking algorithm; then we translate this toy language into our metalanguage. The translation gives the semantics of the toy language and a theorem on the translation of well-typed programs proves the correction of the type-checker of the toy language. As an aside we also illustrate the expressivity of the)`&-based model by showing how to translate existing features like multiple inheritance and multiple dispatch, but also by integrating in the toy language new features directly suggested by the model, such as first-class messages, a generalization of the use of super and the use of explicit coercions.

Journal of Functional Programming, 1994

To illuminate the fundamental concepts involved in object-oriented programming languages, we describe the design of TOOPL, a paradigmatic, statically-typed, functional, object-oriented programming language which supports classes, objects, methods, hidden instance variables, subtypes and inheritance.It has proven to be quite difficult to design such a language which has a secure type system. A particular problem with statically type checking object-oriented languages is designing typechecking rules which ensure that methods provided in a superclass will continue to be type correct when inherited in a subclass. The type-checking rules for TOOPL have this feature, enabling library suppliers to provide only the interfaces of classes with actual executable code, while still allowing users to safely create subclasses. To achieve greater expressibility while retaining type-safety, we choose to separate the inheritance and subtyping hierarchy in the language.The design of TOOPL has been gui...

2003

In this paper we discuss some of the remaining problems in the design of static type systems for object-oriented programming languages. We look at typing problems involved in writing a simple interpreter as a good example of a simple problem leading to difficult typing issues. The difficulties encountered seem to arise in situations where a programmer desires to simultaneously refine mutually interdependent classes and object types.

Lecture Notes, December, 1998

In this document we hope to explore the foundations of object-oriented programming languages by providing a way of understanding these languages via a translation to an extended typed lambda calculus. We will start with a quite simple encoding of objects and classes, and then see that support for such features as subclasses and parametric polymorphism will push us into more complex encodings. Moreover these encodings will suggest the addition of new extensions (eg, MyType) to object-oriented programming ...