Abstract
Run-time state clustering can be available to solve many software problems. As the representations of GUI states are structural, it is a challenging task for GUI run-time states clustering. In this paper, XML documents are adopted to represent and retrieve GUI states and a structural XML-based approach is proposed for clustering GUI states. This approach takes into account differences of features of XML element/attribute labels in forming clusters during XML document comparison. These labels stand for windows, widgets, properties and their value in GUI state descriptions. In this approach, a new step was added in the K-means clustering process to calculate the weights of features in each cluster so that the important features of a state cluster could be identified by the weight values. Experimental results on real GUI state datasets confirmed this new algorithm performed well in practice, and experimental evaluation showed that this proposed algorithm was almost accurate.
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Feng, J., ShangGuan, T. (2012). Application of XML Data Mining in GUI Run-Time State Clustering. In: Liu, B., Ma, M., Chang, J. (eds) Information Computing and Applications. ICICA 2012. Lecture Notes in Computer Science, vol 7473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34062-8_81
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DOI: https://doi.org/10.1007/978-3-642-34062-8_81
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