{"title":"Dynamic data polyvariance using source-tagged classes","authors":"S. Spoon, O. Shivers","doi":"10.1145/1146841.1146845","DOIUrl":null,"url":null,"abstract":"The DDP (Demand-driven/Pruning) analysis algorithm allows us to perform data-flow analyses of programming languages that are dynamically typed and have higher-order control flow, such as Smalltalk or Scheme. Because it is demand-driven and employs search pruning, it scales to large code bases. However, versions of the algorithm previously described [19] do not handle data polymorphism well, conservatively merging separate data flows that go through distinct instantiations of a collection type. In this paper, we describe a new extension to DDP that helps to disentangle these flows, permitting more precise results. The extension is based on source-tagging classes so that each reference to a class in the source code yields a subdivision of the type associated with that class. An initial implementation of this polyvariant analysis has been added to the DDP-based tool Chuck, a part of the integrated Squeak program-development environment; we show examples of the tool in action.","PeriodicalId":344101,"journal":{"name":"Dynamic Languages Symposium","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dynamic Languages Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1146841.1146845","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
The DDP (Demand-driven/Pruning) analysis algorithm allows us to perform data-flow analyses of programming languages that are dynamically typed and have higher-order control flow, such as Smalltalk or Scheme. Because it is demand-driven and employs search pruning, it scales to large code bases. However, versions of the algorithm previously described [19] do not handle data polymorphism well, conservatively merging separate data flows that go through distinct instantiations of a collection type. In this paper, we describe a new extension to DDP that helps to disentangle these flows, permitting more precise results. The extension is based on source-tagging classes so that each reference to a class in the source code yields a subdivision of the type associated with that class. An initial implementation of this polyvariant analysis has been added to the DDP-based tool Chuck, a part of the integrated Squeak program-development environment; we show examples of the tool in action.