Applying modern data mining in electronic design automation and test has become an area of growing interest in recent years. This paper reviews some of the recent developments in the area. It begins by introducing several key concepts in machine learning and data mining, followed by a review of different learning approaches. Then, the experience of developing a practical data mining application is described, including promises demonstrated through positive results based on industrial settings and challenges explained in the respective application contexts. Future research directions are summarized at the end.
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Li-C. Wang (2016) studied this question.
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