CBSD needs to customize and compose components. Customization and composition can cause faults which are hard to detect by existing testing techniques, since components have different structures from traditional progr...
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XP/Agile education and training remains a challenge from the perspective of determining relevant content;identifying effective methods for delivery;and maintaining the focus and motivation of students. This panel brin...
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Recent advancement and wide use of highthroughput technologies for biological research are producing enormous size of biological datasets distributed worldwide. Data mining techniques and machine learning methods prov...
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Recent advancement and wide use of highthroughput technologies for biological research are producing enormous size of biological datasets distributed worldwide. Data mining techniques and machine learning methods provide useful tools for knowledge discovery in this field. The goal of this paper is to present the design of a pattern classifier to mine distributed biological dataset. The proposed classifier is built around a special class of computing model termed as Fuzzy Cellular Automata (FCA). A concrete example of the effectiveness of this approach is provided by demonstrating its success in gene identification problem. Extensive experimental results confirm the scalability of the FCA to handle distributed biological datasets. Application of the proposed model to solve gene identification problem establishes the FCA as the classifier ideally suited for biological data mining in a distributed environment.
In this research, we are developing our understanding of how the high performance computing community develops effective parallel implementations of programs by collecting the folklore within the community. We use thi...
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The G12 project recently started by National IGT Australia (NICTA) is an ambitious project to develop a software platform for solving large scale industrial combinatorial optimisation problems. The core design involve...
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Efficient and successful joining of torn pieces of papers to reconstruct the original documents is an important and challenging issue in many disciplines, especially in forensics and investigation sciences. Automation...
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Efficient and successful joining of torn pieces of papers to reconstruct the original documents is an important and challenging issue in many disciplines, especially in forensics and investigation sciences. Automation of the process by means of appropriate techniques can speed up the problem solving substantially. In this paper, we propose a fast, efficient, and useful technique for the reconstruction of hand-torn pages of documents from their images, using contour descriptors for shape-based matching. Chain code of the closed digital arc representing a contour, and its Minkowski sum, have been exploited in our reconstruction work. Experimental results demonstrate the strength and robustness of the method.
Dealing with dependability requirements is a complex task for stakeholders and analysts as many different aspects of a system must be taken into account at the same time: services characteristics and quality propertie...
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Dealing with dependability requirements is a complex task for stakeholders and analysts as many different aspects of a system must be taken into account at the same time: services characteristics and quality properties, failure modes and tolerable failure rates, reactions and recovery time in case of failure, and so on. Visualization helps cope with this complexity. In this paper, we build upon a practical framework for eliciting and modeling dependability requirements to show how graphical data representation can facilitate requirements analysis during the requirements elicitation and definition process. An air traffic control system, adopted as a testbed within the NASA high dependability computing project, is used as a case study
software process improvement is an iterative activity, normally involving measurement, analysis, and change. For most organizations, the existing software process has substantial momentum and is seemingly immovable. A...
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software process improvement is an iterative activity, normally involving measurement, analysis, and change. For most organizations, the existing software process has substantial momentum and is seemingly immovable. Any change to existing process activities causes turbulence in the organization, which can be a significant barrier to adoption of the quality improvement initiative. This paper presents a quiescent, non-invasive, and adoption-centric approach to process improvement for software maintenance. The approach realizes the goal of improving the efficiency of existing processes by minimizing changes to existing workflows and focusing on integrating enhancements at the micro-level of the system. By leveraging information buried in existing data, making it explicit, and integrating the results with known facts, more informed decision-making is made possible. The approach is illustrated with a model problem concerning redocumentation of an embedded control system in the context of performing higher-quality software maintenance
software measurement programs can help organizations make better decisions regarding their software projects. However, creating and establishing software measurement programs can be both costly and difficult. This pap...
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software measurement programs can help organizations make better decisions regarding their software projects. However, creating and establishing software measurement programs can be both costly and difficult. This paper addresses the problem by focusing on reusability of metrics for software measurement programs through the identification of measurement patterns. We illustrate our work with identifying measurement patterns by providing an extensive and detailed measurement example that is broken down into interdependent building blocks and activities.
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