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  • 标题:Predictive Approach towards Software Effort Estimation using Evolutionary Support Vector Machine
  • 本地全文:下载
  • 作者:Tahira Mahboob ; Sabheen Gull ; Sidrish Ehsan
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2017
  • 卷号:8
  • 期号:5
  • DOI:10.14569/IJACSA.2017.080554
  • 出版社:Science and Information Society (SAI)
  • 摘要:The project effort measurement is one of the most important estimates done in project management domain. This measure is done in advance using some traditional methods like Function Point analysis, Use case analysis, PERT analysis, Analogous, Poker, etc. Classical models have limitations that they are burdensome to implement, especially when there are LOC (lines of code) or objects’ count required in measurement. Sometimes historical information regarding a project is also considered to estimate the projects’ effort. But these estimates are then needed to be adjusted. The idea proposed in this research is to determine what factors regarding a project are directly related to the effort estimation. Other than that a model is proposed to predict the effort using minimum number of parameters in software project development.
  • 关键词:Correlation coefficient; Decision tree; Effort Estimation; Evolutionary Support Vector Machine; Software project management
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