Qing Wang, Nan Jiang, L. Gou, Xia Liu, Mingshu Li, Yongji Wang
{"title":"BSR:用于建立和细化软件过程性能基线的基于统计的方法","authors":"Qing Wang, Nan Jiang, L. Gou, Xia Liu, Mingshu Li, Yongji Wang","doi":"10.1145/1134285.1134368","DOIUrl":null,"url":null,"abstract":"High-level process management is quantitative management. The Process Performance Baseline (PPB) of process or subprocess under statistical management is the most important concept. It is the basis of process control and improvement. The existing methods for establishing process baseline are too coarse-grained or have some limitation, which lead to inaccurate or ineffective quantitative management. In this paper, we propose an approach called BSR (Baseline-Statistic-Refinement) for establishing and refining software process performance baseline, and present the experience result to validate its effectiveness for quantitative process management.","PeriodicalId":246572,"journal":{"name":"Proceedings of the 28th international conference on Software engineering","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"BSR: a statistic-based approach for establishing and refining software process performance baseline\",\"authors\":\"Qing Wang, Nan Jiang, L. Gou, Xia Liu, Mingshu Li, Yongji Wang\",\"doi\":\"10.1145/1134285.1134368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-level process management is quantitative management. The Process Performance Baseline (PPB) of process or subprocess under statistical management is the most important concept. It is the basis of process control and improvement. The existing methods for establishing process baseline are too coarse-grained or have some limitation, which lead to inaccurate or ineffective quantitative management. In this paper, we propose an approach called BSR (Baseline-Statistic-Refinement) for establishing and refining software process performance baseline, and present the experience result to validate its effectiveness for quantitative process management.\",\"PeriodicalId\":246572,\"journal\":{\"name\":\"Proceedings of the 28th international conference on Software engineering\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 28th international conference on Software engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1134285.1134368\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th international conference on Software engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1134285.1134368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BSR: a statistic-based approach for establishing and refining software process performance baseline
High-level process management is quantitative management. The Process Performance Baseline (PPB) of process or subprocess under statistical management is the most important concept. It is the basis of process control and improvement. The existing methods for establishing process baseline are too coarse-grained or have some limitation, which lead to inaccurate or ineffective quantitative management. In this paper, we propose an approach called BSR (Baseline-Statistic-Refinement) for establishing and refining software process performance baseline, and present the experience result to validate its effectiveness for quantitative process management.