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Software clustering is one of the important techniques to comprehend software systems. However, presented techniques to date require human interactions to refine clustering results. In this paper, we proposed a novel dependency-based software clustering algorithm, SArF. SArF has two characteristics. First, SArF eliminates the need of the(More)
—To facilitate understanding the architecture of a software system, we developed SArF Map technique that visualizes software architecture from feature and layer viewpoints using a city metaphor. SArF Map visualizes implicit software features using our previous study, SArF dependency-based software clustering algorithm. Since features are high-level(More)
Process mining has been studied for many years but has not been so widely adopted in real business practices. In this study, we propose a practical approach to process mining. This approach has three characteristics. Firstly, we make use of transaction databases of business systems that don't necessarily have an identifier throughout a process instance,(More)
Software clustering techniques have been used to analyze the reality of software structure. The visualization of the detected clusters has also been studied. However, the features implemented by the detected clusters are not obvious and understanding them is a crucial part of the industrial use of software clustering. In this study, we examined the existing(More)
The purpose of this study is to control the series of actions in the pouring process to improve the productivity of the factory, the safety of workers, and the quality of the product. A mathematical model of the pouring processes was built; based on the model, a forward tilting control input was designed to hold the liquid in the sprue cup at a constant(More)
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