W. Abdelmoez, D. Nassar, M. Shereshevsky, N. Gradetsky, R. Gunnalan, H. Ammar, Bo Yu, A. Mili
{"title":"Error propagation in software architectures","authors":"W. Abdelmoez, D. Nassar, M. Shereshevsky, N. Gradetsky, R. Gunnalan, H. Ammar, Bo Yu, A. Mili","doi":"10.1109/METRIC.2004.1357923","DOIUrl":null,"url":null,"abstract":"The study of software architectures is emerging as an important discipline in software engineering, due to its emphasis on large scale composition of software products, and its support for emerging software engineering paradigms such as product line engineering, component based software engineering, and software evolution. Architectural attributes differ from code-level software attributes in that they focus on the level of components and connectors, and that they are meaningful for an architecture. In this paper, we focus on a specific architectural attribute, which is the error propagation probability throughout the architecture, i.e. the probability that an error that arises in one component propagates to other components. We introduce, analyze, and validate formulas for estimating these probabilities using architectural level information.","PeriodicalId":261807,"journal":{"name":"10th International Symposium on Software Metrics, 2004. Proceedings.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"92","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"10th International Symposium on Software Metrics, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/METRIC.2004.1357923","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 92
Abstract
The study of software architectures is emerging as an important discipline in software engineering, due to its emphasis on large scale composition of software products, and its support for emerging software engineering paradigms such as product line engineering, component based software engineering, and software evolution. Architectural attributes differ from code-level software attributes in that they focus on the level of components and connectors, and that they are meaningful for an architecture. In this paper, we focus on a specific architectural attribute, which is the error propagation probability throughout the architecture, i.e. the probability that an error that arises in one component propagates to other components. We introduce, analyze, and validate formulas for estimating these probabilities using architectural level information.