An Investigation into the Suitability of k-Nearest Neighbour (k-NN) for Software Effort Estimation

Software effort estimation is an increasingly significant field, due to the overwhelming role of software in today’s global market. Effort estimation involves forecasting the effort in person-months or hours required for developing a software. It is vital to ideal planning and paramount for controlling the software development process. However, there is presently no optimal method to accurately estimate the effort required to develop a software system. Inaccurate estimation leads to poor use of resources and perhaps failure of the software project. Effort estimation also plays a key role in deducing cost of a software project. Software cost estimation includes the generation of the effort estimates and project duration to predict cost required to develop software project. Thus, effort is very essential and there is always need to enhance the accuracy as much as possible. This study evaluates and compares the potential of Constructive COst MOdel II (COCOMO II) and k-Nearest Neighbor (k-NN) on software project dataset. By the analysis of results received from each method, it may be concluded that the proposed method k-NN yields better performance over the other technique utilized in this study.

@article{Olu-Ajayi2017,
  title     = {An Investigation into the Suitability of k-Nearest Neighbour (k-NN) for Software Effort Estimation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {6},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Razak Olu-Ajayi},
  doi       = {10.14569/IJACSA.2017.080628},
  url       = {https://doi.org/10.14569/IJACSA.2017.080628}
}