Abstract Comprehensive testing of modern communication systems often requires large and complex test suites, which have to be maintained throughout the system life cycle. Industrial experience, with those written using the standardized Testing and Test Control Notation (TTCN‐3), has shown that this maintenance is a non‐trivial task and its burden can be reduced by means of appropriate concepts and tool support. To this aim, Motorola has collaborated with the University of Göttingen to develop TRex, an open‐source TTCN‐3 development environment, which notably provides suitable metrics and refactorings to enable the assessment and automatic restructuring of test suites. This article presents concepts like metrics and refactoring for the quality assurance of TTCN‐3 test suites and their implementation provided by the TRex tool. These means make it far easier to construct and maintain TTCN‐3 tests that are concise and optimally balanced with respect to maintainability quality characteristics. Copyright © 2008 John Wiley & Sons, Ltd.

This poster paper addresses the problem of choosing sets of software components to combine in component-based software engineering. It formulates both ranking and selection problems as feature subset selection problems to which search based software engineering can be applied. We will consider selection and ranking of elements from a set of software components from the component base of a large telecommunications organisation.

This paper addresses the problem of determining the next set of releases in the course of software evolution. It formulates both ranking and selection of candidate software components as a series of feature subset selection problems to which search based software engineering can be applied. The approach is automated using greedy and simulated annealing algorithms and evaluated using a set of software components from the component base of a large telecommunications organization. The results are compared to those obtained by a panel of (human) experts. The results show that the two automated approaches convincingly outperform the expert judgment approach

We develop reconfigurable designs to support radiosity, a computer graphics algorithm for producing highly realistic images of artificial scenes, but which is computationally expensive. We implement radiosity using stochastic raytracing, which affords both instruction-level and data parallelism. Our designs are parameterisable by bitwidth, allowing trade-offs between image quality and computation speed. We measure the speed of our designs for a Xilinx XC2V6000 device in the Celoxica RC2000 platform: at 53 MHz it can run up to five times faster than a software implementation on an Athlon MP 2600+ processor at 2.1 GHz. We estimate that retargeting our design for a Virtex-4 XCVSX55 device can result in over 160 times software speed, while a Spartan-3 XC3S5000 device can run more than 40 times faster than the software implementation.

Scenario based requirements specifications are the industry norm for defining communicating systems. These scenarios are often captured in the form of UML/MSC sequence diagrams. Errors are often introduced at this stage of the development process, which are costly to resolve if they are not detected early. This paper is concerned with the automatic detection and resolution of semantic errors that can occur in such scenarios.The paper discusses a semantic interpretation of scenario-based requirements and various types of defects (or pathologies) that can be detected. The paper defines the semantics and defects within a partial order theoretic framework. We introduce a UML 2.0 profile that captures various domain specific communication semantics, which can be used to determine the relevance of detected pathologies when different underlying implementation assumptions are made. The paper also discusses how to automatically resolve pathologies by using this profile to adapt the communication architecture in the requirements model.