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  • 标题:On Average Case Analysis Through Statistical Bounds : Linking Theory to Practice
  • 本地全文:下载
  • 作者:Niraj Kumar Singh ; Soubhik Chakraborty ; Dheeresh Kumar Mallick
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2013
  • 卷号:3
  • 期号:6
  • 页码:145-149
  • DOI:10.5121/csit.2013.3615
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type. Such a methodology is plagued with its inherent limitations. In this paper we argue as to why we should prefer weight based statistical bounds, which permit mixing of operations, instead as a robust approach. Empirical analysis is an important idea and should be used to supplement and compliment its existing theoretical counterpart as empirically we can work on weights (e.g. time of an operation can be taken as its weight). Not surprisingly, it should not only be taken as an opportunity so as to amend the mistakes already committed knowingly or unknowingly but also to tell a new story
  • 关键词:Theoretical analysis; empirical analysis; statistical bounds; empirical-O; average case analysis; ;computer experiment section
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