Predictive Approach towards Software Effort Estimation using Evolutionary Support Vector Machine

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.

@article{Mahboob2017,
  title     = {Predictive Approach towards Software Effort Estimation using Evolutionary Support Vector Machine},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {5},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Tahira Mahboob and Sabheen Gull and Sidrish Ehsan and Bushra Sikandar},
  doi       = {10.14569/IJACSA.2017.080554},
  url       = {https://doi.org/10.14569/IJACSA.2017.080554}
}