Abstract syntax trees (ASTs) are known from compiler construction where they build the intermediate data format which is passed from the analytic front-end to the synthetic back-end. In model driven software development ASTs are used as a model of the source code. The Object Management Group (OMG) has issued a request for proposals for AST models. Various levels of abstraction can be introduced. ASTs can be used for program analysis and for program transformation. In this paper we present an eclipse based representation framework for ASTs.

filib++ is an extension of the interval library filib originally developed at the University of Karlsruhe. The most important aim of filib is the fast computation of guaranteed bounds for interval versions of a comprehensive set of elementary functions. filib++ extends this library in two aspects. First, it adds a second mode, the extended mode, that extends the exception-free computation mode (using special values to represent infinities and NaNs known from the IEEE floating-point standard 754) to intervals. In this mode, the so-called containment sets are computed to enclose the topological closure of a range of a function over an interval. Second, our new design uses templates and traits classes to obtain an efficient, easily extendable, and portable C++ library.

Abstract Code transformation and analysis tools provide support for software engineering tasks such as style checking, testing, calculating software metrics as well as reverse‐ and re‐engineering. In this paper we describe the architecture and the applications of JTransform, a general Java source code processing and transformation framework. It consists of a Java parser generating a configurable parse tree and various visitors (transformers, tree evaluators) which produce different kinds of outputs. While our framework is written in Java, the paper further opens an opportunity for a new generation of XML‐based source code tools. Copyright © 2004 John Wiley & Sons, Ltd.

In this paper we show how to recover design information from Java source code. We take a pattern-based approach and proceed in a step by step manner deriving several layers of increasing abstraction. A compiler collects information about inheritance hierarchies and method call relations. It also looks for particular source text patterns coming from naming conventions or programming guidelines.The result of the compile phase is a graph acting as the starting graph of a graph grammar that describes our design recovery process. We define criteria for the automatic detection of associations and aggregations between classes, as well as for some of the popular design patterns such as composite or strategy.

In complex interval arithmetic three different types of intervals are introduced: rectangles, circles and circular sectors1, 4. The arithmetic operations for all three types of intervals should deliver the closest inclusion of the set of all possible values, i.e.

Usually, higher programming languages provide a floating point arithmetic without specifying the accuracy of the operations. In contrast, ADA defines the operations by means of model numbers and rounding (see [2], [11]). Nevertheless, this definition is not strong enough to satisfy the modern requirement of maximum accuracy in all spaces of scientific computation (see [7]-[9]). By this we mean that no computer representable element lies between the actual and the computer generated result of an operation. The object of this paper is to specify the new arithmetic in ADA for all usual numerical data types. The new arithmetic is made available in a convenient operator form.