{"title":"使用进化方法估计遗留应用程序升级时间","authors":"Michal Fornadel, P. Lacko, A. Danko","doi":"10.1109/CINTI.2013.6705247","DOIUrl":null,"url":null,"abstract":"The paper proposes an approach for predicting application upgrade time that is being upgraded from one version to another. The focus is primarily concentrated on applications with upgrades consisting mainly of upgrading the relational database. Chosen application databases have the same schema but the content of tables varies. Data from the upgrades are processed and the proposed solution predicting duration of upgrade for the database which is set to be upgraded provides an estimation whose accuracy is dependent on the number of performed upgrades. The solution is demonstrated on particular enterprise application.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"397 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Estimation of legacy application upgrade time using evolutionary approach\",\"authors\":\"Michal Fornadel, P. Lacko, A. Danko\",\"doi\":\"10.1109/CINTI.2013.6705247\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes an approach for predicting application upgrade time that is being upgraded from one version to another. The focus is primarily concentrated on applications with upgrades consisting mainly of upgrading the relational database. Chosen application databases have the same schema but the content of tables varies. Data from the upgrades are processed and the proposed solution predicting duration of upgrade for the database which is set to be upgraded provides an estimation whose accuracy is dependent on the number of performed upgrades. The solution is demonstrated on particular enterprise application.\",\"PeriodicalId\":439949,\"journal\":{\"name\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"volume\":\"397 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINTI.2013.6705247\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINTI.2013.6705247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of legacy application upgrade time using evolutionary approach
The paper proposes an approach for predicting application upgrade time that is being upgraded from one version to another. The focus is primarily concentrated on applications with upgrades consisting mainly of upgrading the relational database. Chosen application databases have the same schema but the content of tables varies. Data from the upgrades are processed and the proposed solution predicting duration of upgrade for the database which is set to be upgraded provides an estimation whose accuracy is dependent on the number of performed upgrades. The solution is demonstrated on particular enterprise application.
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