{"title":"Aspects of software design analysis: Concurrency and blocking","authors":"C. U. Smith, J. Browne","doi":"10.1145/800199.806169","DOIUrl":null,"url":null,"abstract":"This paper extends previous work on development of a methodology for the prediction of the performance of computer software systems from design level specifications and continuing through implementation. The effects of synchronized behavior, such as results from data reservation in multi-thread executions of data base systems, and competition for host system resources are incorporated. The previous methodology uses hierarchical graphs to represent the execution of software on some host computer system (or on some abstract machine). Performance metrics such as response time were obtained from analysis of these graphs assuming execution of a single copy on a dedicated host. This paper discusses the mapping of these execution graphs upon queueing network models of the host computing environment to yield performance metric estimates for more complex and realistic processing environments.","PeriodicalId":32394,"journal":{"name":"Performance","volume":"79 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"1980-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Performance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/800199.806169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
This paper extends previous work on development of a methodology for the prediction of the performance of computer software systems from design level specifications and continuing through implementation. The effects of synchronized behavior, such as results from data reservation in multi-thread executions of data base systems, and competition for host system resources are incorporated. The previous methodology uses hierarchical graphs to represent the execution of software on some host computer system (or on some abstract machine). Performance metrics such as response time were obtained from analysis of these graphs assuming execution of a single copy on a dedicated host. This paper discusses the mapping of these execution graphs upon queueing network models of the host computing environment to yield performance metric estimates for more complex and realistic processing environments.