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  • 标题:Implicit complexity for coinductive data: a characterization of corecurrence
  • 本地全文:下载
  • 作者:Daniel Leivant ; Ramyaa Ramyaa
  • 期刊名称:Electronic Proceedings in Theoretical Computer Science
  • 电子版ISSN:2075-2180
  • 出版年度:2011
  • 卷号:75
  • 页码:1-14
  • DOI:10.4204/EPTCS.75.1
  • 出版社:Open Publishing Association
  • 摘要:We propose a framework for reasoning about programs that manipulate coinductive data as well as inductive data. Our approach is based on using equational programs, which support a seamless combination of computation and reasoning, and using productivity (fairness) as the fundamental assertion, rather than bi-simulation. The latter is expressible in terms of the former. As an application to this framework, we give an implicit characterization of corecurrence: a function is definable using corecurrence iff its productivity is provable using coinduction for formulas in which data-predicates do not occur negatively. This is an analog, albeit in weaker form, of a characterization of recurrence (i.e. primitive recursion) in [Leivant, Unipolar induction, TCS 318, 2004].
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