{"title":"CASE工具对软件开发效果的实证分析","authors":"Jongmoon Baik, B. Boehm","doi":"10.5555/543101.543102","DOIUrl":null,"url":null,"abstract":"During the last couple of decades, CASE (Computer Aided Software Engineering) tools have played a critical role in improvement of software productivity and quality by assisting tasks in software development processes. Many initiatives in the field were pursued in the 1980’s and 1990’s to provide more effective CASE technologies and development environments. Even though the CASE field is no longer active research area, most software development teams use a huge range of CASE tools that are typically assembled over some period with the hope of productivity and quality improvements throughout the software development process. The variety and proliferation of tools in the current CASE market makes it difficult to understand what kinds of tasks are supported and how much effort can be reduced by using CASE tools. In this paper, we provide a classification of CASE tools by activity coverage in a software development lifecycle. We also report a experimental result of Bayesian analysis on CASE tool effects with a extended set of tool rating scales from COCOMO (COnstructive COst MOdel) II with which CASE tools are effectively evaluated. Index Terms CASE (Computer Aided Software Engineering), Software Cost Estimation, COCOMO (COnstructive COst MOdel) II,","PeriodicalId":177607,"journal":{"name":"ACIS Int. J. Comput. Inf. Sci.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Empirical analysis of CASE tool effects on software development effort\",\"authors\":\"Jongmoon Baik, B. Boehm\",\"doi\":\"10.5555/543101.543102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"During the last couple of decades, CASE (Computer Aided Software Engineering) tools have played a critical role in improvement of software productivity and quality by assisting tasks in software development processes. Many initiatives in the field were pursued in the 1980’s and 1990’s to provide more effective CASE technologies and development environments. Even though the CASE field is no longer active research area, most software development teams use a huge range of CASE tools that are typically assembled over some period with the hope of productivity and quality improvements throughout the software development process. The variety and proliferation of tools in the current CASE market makes it difficult to understand what kinds of tasks are supported and how much effort can be reduced by using CASE tools. In this paper, we provide a classification of CASE tools by activity coverage in a software development lifecycle. We also report a experimental result of Bayesian analysis on CASE tool effects with a extended set of tool rating scales from COCOMO (COnstructive COst MOdel) II with which CASE tools are effectively evaluated. Index Terms CASE (Computer Aided Software Engineering), Software Cost Estimation, COCOMO (COnstructive COst MOdel) II,\",\"PeriodicalId\":177607,\"journal\":{\"name\":\"ACIS Int. J. Comput. Inf. Sci.\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACIS Int. J. Comput. Inf. Sci.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5555/543101.543102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACIS Int. J. Comput. Inf. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/543101.543102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Empirical analysis of CASE tool effects on software development effort
During the last couple of decades, CASE (Computer Aided Software Engineering) tools have played a critical role in improvement of software productivity and quality by assisting tasks in software development processes. Many initiatives in the field were pursued in the 1980’s and 1990’s to provide more effective CASE technologies and development environments. Even though the CASE field is no longer active research area, most software development teams use a huge range of CASE tools that are typically assembled over some period with the hope of productivity and quality improvements throughout the software development process. The variety and proliferation of tools in the current CASE market makes it difficult to understand what kinds of tasks are supported and how much effort can be reduced by using CASE tools. In this paper, we provide a classification of CASE tools by activity coverage in a software development lifecycle. We also report a experimental result of Bayesian analysis on CASE tool effects with a extended set of tool rating scales from COCOMO (COnstructive COst MOdel) II with which CASE tools are effectively evaluated. Index Terms CASE (Computer Aided Software Engineering), Software Cost Estimation, COCOMO (COnstructive COst MOdel) II,