4,401 research outputs found

    A comparative evaluation of dynamic visualisation tools

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    Despite their potential applications in software comprehension, it appears that dynamic visualisation tools are seldom used outside the research laboratory. This paper presents an empirical evaluation of five dynamic visualisation tools - AVID, Jinsight, jRMTool, Together ControlCenter diagrams and Together ControlCenter debugger. The tools were evaluated on a number of general software comprehension and specific reverse engineering tasks using the HotDraw objectoriented framework. The tasks considered typical comprehension issues, including identification of software structure and behaviour, design pattern extraction, extensibility potential, maintenance issues, functionality location, and runtime load. The results revealed that the level of abstraction employed by a tool affects its success in different tasks, and that tools were more successful in addressing specific reverse engineering tasks than general software comprehension activities. It was found that no one tool performs well in all tasks, and some tasks were beyond the capabilities of all five tools. This paper concludes with suggestions for improving the efficacy of such tools

    A survey of agent-oriented methodologies

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    This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

    On the role of domain ontologies in the design of domain-specific visual modeling langages

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    Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user’s perspective, the language’s modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community

    A review of information flow diagrammatic models for product-service systems

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    A product-service system (PSS) is a combination of products and services to create value for both customers and manufacturers. Modelling a PSS based on function orientation offers a useful way to distinguish system inputs and outputs with regards to how data are consumed and information is used, i.e. information flow. This article presents a review of diagrammatic information flow tools, which are designed to describe a system through its functions. The origin, concept and applications of these tools are investigated, followed by an analysis of information flow modelling with regards to key PSS properties. A case study of selection laser melting technology implemented as PSS will then be used to show the application of information flow modelling for PSS design. A discussion based on the usefulness of the tools in modelling the key elements of PSS and possible future research directions are also presented

    Engineering simulations for cancer systems biology

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    Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

    Visual Detection of Structural Changes in Time-Varying Graphs Using Persistent Homology

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    Topological data analysis is an emerging area in exploratory data analysis and data mining. Its main tool, persistent homology, has become a popular technique to study the structure of complex, high-dimensional data. In this paper, we propose a novel method using persistent homology to quantify structural changes in time-varying graphs. Specifically, we transform each instance of the time-varying graph into metric spaces, extract topological features using persistent homology, and compare those features over time. We provide a visualization that assists in time-varying graph exploration and helps to identify patterns of behavior within the data. To validate our approach, we conduct several case studies on real world data sets and show how our method can find cyclic patterns, deviations from those patterns, and one-time events in time-varying graphs. We also examine whether persistence-based similarity measure as a graph metric satisfies a set of well-established, desirable properties for graph metrics
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