FreezeML: complete and easy type inference for first-class polymorphism

Frank Emrich, S. Lindley, Jan Stolarek, J. Cheney, Jonathan Coates
{"title":"FreezeML: complete and easy type inference for first-class polymorphism","authors":"Frank Emrich, S. Lindley, Jan Stolarek, J. Cheney, Jonathan Coates","doi":"10.1145/3385412.3386003","DOIUrl":null,"url":null,"abstract":"ML is remarkable in providing statically typed polymorphism without the programmer ever having to write any type annotations. The cost of this parsimony is that the programmer is limited to a form of polymorphism in which quantifiers can occur only at the outermost level of a type and type variables can be instantiated only with monomorphic types. Type inference for unrestricted System F-style polymorphism is undecidable in general. Nevertheless, the literature abounds with a range of proposals to bridge the gap between ML and System F. We put forth a new proposal, FreezeML, a conservative extension of ML with two new features. First, let- and lambda-binders may be annotated with arbitrary System F types. Second, variable occurrences may be frozen, explicitly disabling instantiation. FreezeML is equipped with type-preserving translations back and forth between System F and admits a type inference algorithm, an extension of algorithm W, that is sound and complete and which yields principal types.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3385412.3386003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

ML is remarkable in providing statically typed polymorphism without the programmer ever having to write any type annotations. The cost of this parsimony is that the programmer is limited to a form of polymorphism in which quantifiers can occur only at the outermost level of a type and type variables can be instantiated only with monomorphic types. Type inference for unrestricted System F-style polymorphism is undecidable in general. Nevertheless, the literature abounds with a range of proposals to bridge the gap between ML and System F. We put forth a new proposal, FreezeML, a conservative extension of ML with two new features. First, let- and lambda-binders may be annotated with arbitrary System F types. Second, variable occurrences may be frozen, explicitly disabling instantiation. FreezeML is equipped with type-preserving translations back and forth between System F and admits a type inference algorithm, an extension of algorithm W, that is sound and complete and which yields principal types.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
FreezeML:为一级多态性提供完整和简单的类型推断
ML在提供静态类型多态性方面非常出色,程序员无需编写任何类型注释。这种简约的代价是程序员被限制在一种形式的多态性中,在这种形式中,量词只能出现在类型的最外层,类型变量只能用单态类型实例化。一般来说,不受限制的System F-style多态性的类型推断是不可确定的。然而,文献中有大量的建议来弥合ML和System f之间的差距。我们提出了一个新的建议,FreezeML,一个ML的保守扩展,有两个新特性。首先,let和lambda绑定器可以用任意System F类型注释。其次,变量的出现可能会被冻结,显式地禁用实例化。FreezeML配备了系统F之间的类型保持转换,并允许类型推断算法,这是算法W的扩展,它是健全和完整的,并且产生主要类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Type error feedback via analytic program repair Inductive sequentialization of asynchronous programs Decidable verification under a causally consistent shared memory SympleGraph: distributed graph processing with precise loop-carried dependency guarantee Debug information validation for optimized code
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1