Selection of Requirement Elicitation Techniques: A Neural Network based Approach

Abstract: Requirement Elicitation is key activity of requirement engineering and has a strong impact on design and other phases of software development life cycle. Poor requirement engineering practices lead to project failure. A sound requirement elicitation process is the foundation for the overall quality of software product. Due to criticality and high impact of this phase on overall success and failure of projects, it is very necessary to perform the requirements elicitation activities in a perfect and specific manner. The most difficult and demanding jobs during Requirement Elicitation phase is to select appropriate and specific technique from a wide array of techniques and tools. In this paper, a new approach is proposed using an artificial neural network for selection of requirement elicitation technique from a wide variety of tools and techniques that are available. The training of Neural Network is done by back propagation algorithm. The trained and resultant network can be used as a base for selection of requirement elicitation techniques.

Mohd Muqeem, Sultan Ahmad, Jabeen Nazeer, Md. Faizan Farooqui and Afroj Alam. “Selection of Requirement Elicitation Techniques: A Neural Network based Approach”. International Journal of Advanced Computer Science and Applications (IJACSA) 13.1 (2022). http://dx.doi.org/10.14569/IJACSA.2022.0130144

@article{Muqeem2022,
title = {Selection of Requirement Elicitation Techniques: A Neural Network based Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130144},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130144},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Mohd Muqeem and Sultan Ahmad and Jabeen Nazeer and Md. Faizan Farooqui and Afroj Alam}
}