G. Triantafyllos, S. Vassiliadis, J. Delgado-Frías
{"title":"软件度量和微码:一个案例研究","authors":"G. Triantafyllos, S. Vassiliadis, J. Delgado-Frías","doi":"10.1002/(SICI)1096-908X(199605)8:3%3C199::AID-SMR129%3E3.0.CO;2-N","DOIUrl":null,"url":null,"abstract":"In this paper, we report the findings of an investigation undertaken at IBM to determine whether or not existing software metrics are applicable to the microcode of large computer systems. As part of this investigation, we calculated several metrics from the microcode developed for the IBM 4381 and IBM 9370 computer systems, and used them as predictive parameters for a number of existing error prediction models. The microcode used in this case study exceeds 1.2 million lines of code written in 12 languages and comprises the microcode for the IBM ES/4381 and IBM ES/9370 computer systems. Our results suggest that only a few of the existing metrics are linearly independent, and that none of the metrics examined can be used in a regression model as a reliable error predictor.","PeriodicalId":383619,"journal":{"name":"J. Softw. Maintenance Res. Pract.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Software Metrics and Microcode: A Case Study\",\"authors\":\"G. Triantafyllos, S. Vassiliadis, J. Delgado-Frías\",\"doi\":\"10.1002/(SICI)1096-908X(199605)8:3%3C199::AID-SMR129%3E3.0.CO;2-N\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we report the findings of an investigation undertaken at IBM to determine whether or not existing software metrics are applicable to the microcode of large computer systems. As part of this investigation, we calculated several metrics from the microcode developed for the IBM 4381 and IBM 9370 computer systems, and used them as predictive parameters for a number of existing error prediction models. The microcode used in this case study exceeds 1.2 million lines of code written in 12 languages and comprises the microcode for the IBM ES/4381 and IBM ES/9370 computer systems. Our results suggest that only a few of the existing metrics are linearly independent, and that none of the metrics examined can be used in a regression model as a reliable error predictor.\",\"PeriodicalId\":383619,\"journal\":{\"name\":\"J. Softw. Maintenance Res. Pract.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Softw. Maintenance Res. Pract.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/(SICI)1096-908X(199605)8:3%3C199::AID-SMR129%3E3.0.CO;2-N\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Softw. Maintenance Res. Pract.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/(SICI)1096-908X(199605)8:3%3C199::AID-SMR129%3E3.0.CO;2-N","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we report the findings of an investigation undertaken at IBM to determine whether or not existing software metrics are applicable to the microcode of large computer systems. As part of this investigation, we calculated several metrics from the microcode developed for the IBM 4381 and IBM 9370 computer systems, and used them as predictive parameters for a number of existing error prediction models. The microcode used in this case study exceeds 1.2 million lines of code written in 12 languages and comprises the microcode for the IBM ES/4381 and IBM ES/9370 computer systems. Our results suggest that only a few of the existing metrics are linearly independent, and that none of the metrics examined can be used in a regression model as a reliable error predictor.