Marco Comini , Giorgio Levi , Maria Chiara Meo , Giuliana Vitiello
{"title":"Abstract diagnosis","authors":"Marco Comini , Giorgio Levi , Maria Chiara Meo , Giuliana Vitiello","doi":"10.1016/S0743-1066(98)10033-X","DOIUrl":null,"url":null,"abstract":"<div><p>We show how declarative diagnosis techniques can be extended to cope with verification of operational properties, such as computed and correct answers, and of abstract properties, such as <em>depth(k)</em> answers and groundness dependencies. The extension is achieved by using a simple semantic framework, based on abstract interpretation. The resulting technique (abstract diagnosis) leads to elegant bottom-up and top-down verification methods, which do not require to determine the symptoms in advance, and which are effective in the case of abstract properties described by finite domains.</p></div>","PeriodicalId":101236,"journal":{"name":"The Journal of Logic Programming","volume":"39 1","pages":"Pages 43-93"},"PeriodicalIF":0.0000,"publicationDate":"1999-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0743-1066(98)10033-X","citationCount":"64","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Logic Programming","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S074310669810033X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 64
Abstract
We show how declarative diagnosis techniques can be extended to cope with verification of operational properties, such as computed and correct answers, and of abstract properties, such as depth(k) answers and groundness dependencies. The extension is achieved by using a simple semantic framework, based on abstract interpretation. The resulting technique (abstract diagnosis) leads to elegant bottom-up and top-down verification methods, which do not require to determine the symptoms in advance, and which are effective in the case of abstract properties described by finite domains.