L. Burgueño, R. Clarisó, Jordi Cabot, S. Gérard, Antonio Vallecillo
{"title":"软件模型中的信念不确定性","authors":"L. Burgueño, R. Clarisó, Jordi Cabot, S. Gérard, Antonio Vallecillo","doi":"10.1109/MiSE.2019.00011","DOIUrl":null,"url":null,"abstract":"This paper discusses the representation of Belief Uncertainty in software models. This kind of uncertainty refers to the situation in which the modeler, or any other belief agent, is uncertain about the behavior of the system, or the statements that the model expresses about it. In this work, we propose to assign a degree of belief to model statements (let they be constraints, or any other model expression), which is expressed by a probability (called credence, in statistical terms) that represents a quantification of such a subjective degree of belief. We discuss how it can be represented using current modeling notations, and how to operate with it in order to make informed decisions.","PeriodicalId":340157,"journal":{"name":"2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Belief Uncertainty in Software Models\",\"authors\":\"L. Burgueño, R. Clarisó, Jordi Cabot, S. Gérard, Antonio Vallecillo\",\"doi\":\"10.1109/MiSE.2019.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses the representation of Belief Uncertainty in software models. This kind of uncertainty refers to the situation in which the modeler, or any other belief agent, is uncertain about the behavior of the system, or the statements that the model expresses about it. In this work, we propose to assign a degree of belief to model statements (let they be constraints, or any other model expression), which is expressed by a probability (called credence, in statistical terms) that represents a quantification of such a subjective degree of belief. We discuss how it can be represented using current modeling notations, and how to operate with it in order to make informed decisions.\",\"PeriodicalId\":340157,\"journal\":{\"name\":\"2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MiSE.2019.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MiSE.2019.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper discusses the representation of Belief Uncertainty in software models. This kind of uncertainty refers to the situation in which the modeler, or any other belief agent, is uncertain about the behavior of the system, or the statements that the model expresses about it. In this work, we propose to assign a degree of belief to model statements (let they be constraints, or any other model expression), which is expressed by a probability (called credence, in statistical terms) that represents a quantification of such a subjective degree of belief. We discuss how it can be represented using current modeling notations, and how to operate with it in order to make informed decisions.