T. J. Brown

Towards Performance Related Decision Support for Model Driven Engineering of Enterprise SOA Applications

Model driven performance engineering (MDPE) enables early performance feedback in a MDE process, in order to avoid late identification of performance problems which could cause significant additional development costs. In our past work we argued that a synchronization mechanism between development and performance analysis models is required to adequately integrate analysis results into the development process enabling performance related decision support. In this paper we present a solution for this requirement. We present a new multi-view based approach and its implementation enabling systematic performance related decision support. We currently apply our research on the model driven engineering of process orchestrations on top of SAPs enterprise service oriented architecture (Enterprise SOA).

Feature-Guided Architecture Development for Embedded System Families

Software product-line engineering aims to maximize reuse by exploiting the commonality within families of related systems. Its success depend on capturing the commonality and variability, and using this to evolve a reference architecture for the product family. With embedded system families, the possibility of variability in hardware and operating system platforms is an added complication. In this paper we outline a strategy for evolving reference architectures from bi-directional feature models. The proposed strategy complements information provided by the feature model with scenarios that help to elaborate feature behavior.

A self-optimising coprocessor model for portable parallel image processing

This paper describes an approach taken to achieve both portability and efficiency in the context of image processing. It outlines the EPIC architecture (Extensible Parallel Image Coprocessor), an image processing-specific software architecture capable of efficient implementation on a range of parallel machines. EPIC is currently being implemented using a network of C40 processors.

Achieving Portability and Efficiency Through Automatic Optimisation: An Investigation in Parallel Image Processing

This paper discusses the main achievements of the EPIC project, whose aim was to design a high level programming environment with an associated implementation for portable parallel image processing. The project was funded as part of the EPSRC Portable Software Tools for Parallel Architectures (PSTPA) programme. The paper summarises new portable programming abstractions for image processing, and outlines the automatically optimising implementation which achieves portability of application code and efficiency of implementation on a closely coupled distributed memory parallel system. The paper includes timings for optimised and unoptimised versions of typical image processing algorithms; it draws the main conclusion that it is possible to achieve portability with efficiency, for a specific application, by adopting a high level algebraic programming model, together with a transformation-based optimiser which reclaims the loss of efficiency which an algebraic approach traditionally entails.

The List_Tree — An Innovative Solution to Customer Portfolio Representation

The scale of BTs operations necessitates the use of very large scale computing systems, and the storage and management of large volumes of data. Customer product portfolios are an important form of data which can be difficult to store in a space-efficient way. The difficulties arise from the inherently structured form of product portfolios, and the fact that they change over time as customers add or remove products. This paper introduces a new data-modelling abstraction called the List_Tree. It has been designed specifically to support the efficient storage and manipulation of customer product portfolios, but may also prove useful in other applications with similar general requirements.