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  • 标题:A Generic Framework for Higher-Order Generalizations
  • 本地全文:下载
  • 作者:David M. Cerna ; Temur Kutsia
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2019
  • 卷号:131
  • 页码:1-19
  • DOI:10.4230/LIPIcs.FSCD.2019.10
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:We consider a generic framework for anti-unification of simply typed lambda terms. It helps to compute generalizations which contain maximally common top part of the input expressions, without nesting generalization variables. The rules of the corresponding anti-unification algorithm are formulated, and their soundness and termination are proved. The algorithm depends on a parameter which decides how to choose terms under generalization variables. Changing the particular values of the parameter, we obtained four new unitary variants of higher-order anti-unification and also showed how the already known pattern generalization fits into the schema.
  • 关键词:anti-unification; typed lambda calculus; least general generalization
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