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文章基本信息

  • 标题:Test Case Suite Reduction of High Dimensional Data by Automatic Subspace Clustering
  • 本地全文:下载
  • 作者:Bhawna Jyoti ; Aman Kumar Sharma
  • 期刊名称:International Journal of Soft Computing & Engineering
  • 电子版ISSN:2231-2307
  • 出版年度:2014
  • 卷号:4
  • 期号:1
  • 页码:159-162
  • 出版社:International Journal of Soft Computing & Engineering
  • 摘要:Mostly, testing techniques are designed for data which are having low dimensional space and less intention is paid to the testing of high dimensional data. In this paper, data undergoes a process of dimensionality reduction by principal component analysis (PCA) which leads to the automate subspace clustering of data. The combination of distributed based approach and coverage based approach is used to test the test cases sampled from each cluster formed. The contribution of this paper is related to the dimensionality reduction as well as test case suite reduction by discovering patterns in software testing in a rigorous manner.
  • 关键词:Dimensionality reduction using PCA; clustering; the test suite minimization.
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