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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 12, 2017.
Abstract: Due to dynamic nature of current software development methods, changes in requirements are embraced and given proper consideration. However, this triggers the rank reversal problem which involves re-prioritizing requirements based on stakeholders’ feedback. It incurs significant cost because of time elapsed in large number of human interactions. To solve this issue, a Semi-Automated Framework for soFtware Requirements priOritizatioN (SAFFRON) is presented in this paper. For a particular requirement, SAFFRON predicts appropriate stakeholders’ ratings to reduce human interactions. Initially, item-item collaborative filtering is utilized to estimate similarity between new and previously elicited requirements. Using this similarity, stakeholders who are most likely to rate requirements are determined. Afterwards, collaborative filtering based on latent factor model is used to predict ratings of those stakeholders. The proposed approach is implemented and tested on RALIC dataset. The results illustrate consistent correlation, similar to state of the art approaches, with the ground truth. In addition, SAFFRON requires 13.5-27% less human interaction for reprioritizing requirements.
Syed Ali Asif, Zarif Masud, Rubaida Easmin and Alim Ul Gias, “SAFFRON: A Semi-Automated Framework for Software Requirements Prioritization” International Journal of Advanced Computer Science and Applications(IJACSA), 8(12), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081265
@article{Asif2017,
title = {SAFFRON: A Semi-Automated Framework for Software Requirements Prioritization},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081265},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081265},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {12},
author = {Syed Ali Asif and Zarif Masud and Rubaida Easmin and Alim Ul Gias}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.