Functional Requirements-Based Automated Testing for Avionics

We propose and demonstrate a method for the reduction of testing effort in safety-critical software development using DO-178 guidance. We achieve this through the application of Bounded Model Checking (BMC) to formal low-level requirements, in order to generate tests automatically that are good enough to replace existing labor-intensive test writing procedures while maintaining independence from implementation artefacts. Given that existing manual processes are often empirical and subjective, we begin by formally defining a metric, which extends recognized best practice from code coverage analysis strategies to generate tests that adequately cover the requirements. We then formulate the automated test generation procedure and apply its prototype in case studies with industrial partners. In review, the method developed here is demonstrated to significantly reduce the human effort for the qualification of software products under DO-178 guidance

Automated post-fault diagnosis of power system disturbances

In order to automate the analysis of SCADA and digital fault recorder (DFR) data for a transmission network operator in the UK, the authors have developed an industrial strength multi-agent system entitled protection engineering diagnostic agents (PEDA). The PEDA system integrates a number of legacy intelligent systems for analyzing power system data as autonomous intelligent agents. The integration achieved through multi-agent systems technology enhances the diagnostic support offered to engineers by focusing the analysis on the most pertinent DFR data based on the results of the analysis of SCADA. Since November 2004 the PEDA system has been operating online at a UK utility. In this paper the authors focus on the underlying intelligent system techniques, i.e. rule-based expert systems, model-based reasoning and state-of-the-art multi-agent system technology, that PEDA employs and the lessons learnt through its deployment and online use

Virtual HR Departments: Getting Out of the Middle

In this chapter, we explore the notion of virtual HR departments: a network-based organization built on partnerships and mediated by information technologies in order to be simultaneously strategic, flexible, cost-efficient, and service-oriented. We draw on experiences and initiatives at Merck Pharmaceuticals in order to show how information technology in establishing an infrastructure for virtual HR. Then, we present a model for mapping the architecture of HR activities that includes both internal and external sourcing options. We conclude by offering some recommendations for management practice as well as future research

Adding generic contextual capabilities to wearable computers

Context-awareness has an increasingly important role to play in the development of wearable computing systems. In order to better define this role we have identified four generic contextual capabilities: sensing, adaptation, resource discovery, and augmentation. A prototype application has been constructed to explore how some of these capabilities could be deployed in a wearable system designed to aid an ecologist's observations of giraffe in a Kenyan game reserve. However, despite the benefits of context-awareness demonstrated in this prototype, widespread innovation of these capabilities is currently stifled by the difficulty in obtaining the contextual data. To remedy this situation the Contextual Information Service (CIS) is introduced. Installed on the user's wearable computer, the CIS provides a common point of access for clients to obtain, manipulate and model contextual information independently of the underlying plethora of data formats and sensor interface mechanisms

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

An automated ETL for online datasets

While using online datasets for machine learning is commonplace today, the quality of these datasets impacts on the performance of prediction algorithms. One method for improving the semantics of new data sources is to map these sources to a common data model or ontology. While semantic and structural heterogeneities must still be resolved, this provides a well established approach to providing clean datasets, suitable for machine learning and analysis. However, when there is a requirement for a close to real time usage of online data, a method for dynamic Extract-Transform-Load of new sources data must be developed. In this work, we present a framework for integrating online and enterprise data sources, in close to real time, to provide datasets for machine learning and predictive algorithms. An exhaustive evaluation compares a human built data transformation process with our system’s machine generated ETL process, with very favourable results, illustrating the value and impact of an automated approach