1,721,017 research outputs found
Modeling scenarios for the performance prediction of distributed real-time embedded systems
No full textAutonomous defence systems are typically characterized by hard constraints on space, weight and power. These constraints have a strong impact on the non-functional properties and especially performance of the final system. System execution modelling tools permit early prediction of the performance of model driven systems; however they are intended for one shot analysis, not for repeatable, interactive use. In this paper we propose a Domain Specific Language for describing scenarios to repeatedly test a system execution model within a Synthetic Environment. We exemplify it by describing and executing a scenario involving an UAV and a CMS.Katrina Falkner, Vanea Chiprianov, Nickolas Falkner, Claudia Szabo, Gavin Pudd
A model-driven engineering method for DRE defence systems performance analysis and prediction
No full textAutonomous, Distributed Real-Time Embedded (DRE) defence systems are typically characterized by hard constraints on space, weight, and power. These constraints have a strong impact on the nonfunctional properties of the final system, especially its performance. System execution modeling tools permit early prediction of the performance of model-driven systems; however, the focus to date has been on the practical aspects and creating tools that work in specific cases, rather than on the process and methodology applied. In this chapter, the authors present an integrated method to performance analysis and prediction of model-driven DRE defense systems. They present both the tools to support the process and a method to define these tools. The authors explore these tools and processes within an industry case study from a defense context.Katrina Falkner, Vanea Chiprianov, Nickolas Falkner, Claudia Szabo, Gavin Pudd
Reflecting on three offerings of a community-centric MOOC for K-6 computer science teachers
No full textA number of institutions and organisations provide online or face-to-face professional learning as part of outreach initiatives to increase skill levels and support for teachers in K-12 Computing education. With a number of countries introducing new K-12 Computer Science curricula around the globe, this provides a prime opportunity for the Computer Science education community to transform and develop models of teacher professional learning that address teachers' needs at-scale. This paper explores the theoretical underpinnings of a community-based professional learning MOOC for Australian teachers for K-6 Computer Science. This paper reflects on data collected from three offerings of the MOOC, presented in light of the theory and design considerations. This paper provides valuable insights of the design of community-centric MOOCs, and acts as a guide for the construction of online professional learning opportunities for Computer Science educators.Katrina Falkner, Rebecca Vivian, Nickolas Falkner, Sally-Ann William
Applying validated pedagogy to MOOCs: an introductory programming course with media computation
No full textSignificant advances have been made in the learning and teaching of Introductory Programming, including the integration of active and contextualised learning pedagogy. However, Massively Open Online Courses (MOOCs), where Computer Science and, more specifically, introductory programming courses dominate, do not typically adopt such pedagogies or lessons learned from more traditional learning environments. Moreover, the improvement of learning within the MOOC context in terms of discipline-specific pedagogy, and the improvement of student learning outcomes and processes have not been studied in depth. This paper reports findings from a foundation programming skills MOOC that supports the learning of fundamental Computer Science concepts and the development of programming skills through a media computation approach, based upon digital artworks and animations. In this paper, we explore the course activity data as well as a sample of students' source code submissions to investigate their engagement with the course and the quality and development of their programming skill over the six weeks of the course duration.Katrina Falkner, Nickolas Falkner, Claudia Szabo, Rebecca Vivia
The internet topology zoo
No full textThe study of network topology has attracted a great deal of attention in the last decade, but has been hampered by a lack of accurate data. Existing methods for measuring topology have flaws, and arguments about the importance of these have overshadowed the more interesting questions about network structure. The Internet Topology Zoo is a store of network data created from the information that network operators make public. As such it is the most accurate large-scale collection of network topologies available, and includes meta-data that couldn’t have been measured. With this data we can answer questions about network structure with more certainty than ever before — we illustrate its power through a preliminary analysis of the PoP-level topology of over 140 networks. We find a wide range of network designs not conforming as a whole to any obvious model.Simon Knight, Hung X. Nguyen, Nickolas Falkner, Rhys Bowden and Matthew Rougha
The development of a dashboard tool for visualising online teamwork discussions
No full textMany software development organisations today adopt global software engineering (GSE) and agile models; requiring software engineers to collaborate and develop software in flexible, distributed, online teams. However, many employers have expressed concern that graduates lack teamwork skills and one of the most commonly occurring problems with GSE models are issues with project management. Team managers and educators often oversee a number of teams and the large corpus of data, in combination with agile models, make it difficult to efficiently assess factors such as team role distribution and emotional climate. Current methods and tools for monitoring software engineering (SE) teamwork in both industry and education settings typically focus on member contributions, reflection, or product outcomes, which are limited in terms of real-time feedback and accurate behavioural analysis. We have created a dashboard that extracts and communicates team role distribution and team emotion information in real-time. Our proof of concept provides a real-time analysis of teamwork discussions and visualises team member emotions, the roles they have adopted and overall team sentiment during the course of a collaborative problemsolving project. We demonstrate and discuss how such a tool could be useful for SE team management and training and the development of teamwork skills in SE university courses.Rebecca Vivian, Hamid Tarmazdi, Katrina Falkner, Nickolas Falkner and Claudia Szab
An automated system for emulated network experimentation
No full textEmulated networks and systems, where router and server software are run in virtual environments, allow network operators and researchers to perform experiments at large scale more economically than in testbeds. Running real code provides a greater level of realism than simulation. However, large scale comes with a problem: running real software means each test needs at least as much configuration as a real network. To recognise the true value of emulation at scale, we need to reduce the complexity of building, configuring, deploying, and measuring emulated networks. We present a system to facilitate emulation by providing translation from a high-level network design into a concrete set of configurations that are automatically deployed into one of several emulation platforms. Our system can be used to construct multi-domain networks in minutes, and is scalable to networks with over a thousand devices. It is modular, allowing support for different protocols, topology designs, and target platforms: Quagga, JunOS, IOS, etc. Users, from both the research community and industry, have already demonstrated its value in research and education.Simon Knight, Hung Nguyen, Olaf Maennel, Iain Phillips, Nickolas Falkner, Randy Bush, Matthew Rougha
Generalized graph products for network design and analysis
No full textNetwork design, as it is currently practiced, involves putting devices together to create a network. However, a network is more than the sum of its parts, both in terms of the services it provides, and the potential for bugs. Devices are important, but their combination into a network should follow from expression of high-level policy, not the minutiae of network device configuration. Ideally we want to consider the network as a whole object. In this paper we develop generalized graph products that allow the mathematical design of a network in terms of small subgraphs that directly express business policy. The result is a flexible algebraic description of networks suitable for manipulation and proof. The approach is more than just design - it allows for analysis of existing networks providing an understanding of the policies used in their construction, something which can be difficult if the original designers no longer work on that network. We apply the approach to several real world networks to demonstrate how it can provide insight, and improve design.Eric Parsonage, Hung X. Nguyen, Rhys Bowden, Simon Knight, Nickolas Falkner, Matthew Rougha
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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