文章基本信息

标题：DATA ANALYSIS IN SOFTWARE EFFORT ESTIMATION USING IMPROVED DELPHI METHOD
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作者：ASHISH RAI ; G. P. GUPTA ; PANKAJ KUMAR 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：3
页码：846-855
出版社：Journal of Theoretical and Applied
摘要：Software Estimation Accuracy is one of the most difficult tasks for the software developers. Defining the project duration, effort estimation and estimated cost, early in the development phase is greatest challenge has to be achieved for software projects. Inaccurate effort estimation of software development is one of the most important reasons of computer and IT major project failures. Low effort estimates may lead to project management problems, delayed deliveries, budget overruns and poor software quality, too high effort estimates may lead to loss of business opportunities and improper and inefficient use of resources. The projects main focus at Simulate Research Laboratory is to improve judgment-based effort estimation methods, which is most frequently used by the software industries. By introducing better mental steps in effort estimation, we can achieve significant improvement in software development estimation processes. There are great challenge while studying expert judgment like Delphi Estimation. To understand the use of multidisciplinary competencies, especially financial resources enables studies in realistic software development process, psychology and software engineering. This paper explores the relationship between development effort, team size and software size. The main objective of this research is to improve the existing Delphi method for the estimation of software development effort using hybrid approach. Proposed, improved method has been validated by using 15 NASA project dataset and the results show that the improved Delphi method for software effort estimation resulted in slightly better as compared to results obtained earlier.
关键词：Effort Estimation; Productivity; Algorithmic Model; Variance; MMRE; Pred.