{"title":"概率线性λ演算的双模拟","authors":"Yuxin Deng, Yuan Feng","doi":"10.1109/TASE.2017.8285625","DOIUrl":null,"url":null,"abstract":"We investigate a notion of probabilistic program equivalence under linear contexts. We show that both a statebased and a distribution-based bisimilarity are sound coinductive proof techniques for reasoning about higher-order probabilistic programs, but only the distribution-based one is complete for linear contextual equivalence. The completeness proof is novel and directly constructs linear contexts from transitions, rather than the traditional approach of characterizing bisimilarities as testing equivalences.","PeriodicalId":221968,"journal":{"name":"2017 International Symposium on Theoretical Aspects of Software Engineering (TASE)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Bisimulations for probabilistic linear lambda calculi\",\"authors\":\"Yuxin Deng, Yuan Feng\",\"doi\":\"10.1109/TASE.2017.8285625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We investigate a notion of probabilistic program equivalence under linear contexts. We show that both a statebased and a distribution-based bisimilarity are sound coinductive proof techniques for reasoning about higher-order probabilistic programs, but only the distribution-based one is complete for linear contextual equivalence. The completeness proof is novel and directly constructs linear contexts from transitions, rather than the traditional approach of characterizing bisimilarities as testing equivalences.\",\"PeriodicalId\":221968,\"journal\":{\"name\":\"2017 International Symposium on Theoretical Aspects of Software Engineering (TASE)\",\"volume\":\"185 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Symposium on Theoretical Aspects of Software Engineering (TASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TASE.2017.8285625\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Symposium on Theoretical Aspects of Software Engineering (TASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TASE.2017.8285625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bisimulations for probabilistic linear lambda calculi
We investigate a notion of probabilistic program equivalence under linear contexts. We show that both a statebased and a distribution-based bisimilarity are sound coinductive proof techniques for reasoning about higher-order probabilistic programs, but only the distribution-based one is complete for linear contextual equivalence. The completeness proof is novel and directly constructs linear contexts from transitions, rather than the traditional approach of characterizing bisimilarities as testing equivalences.