Proceedings of the 3rd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2022, 24-25 March 2022, New Delhi, India

Research Article

Enhancing Software Requirements Selection Process Using Genetic Algorithm

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  • @INPROCEEDINGS{10.4108/eai.24-3-2022.2319030,
        author={Mohd.  Nazim and Javed  Ahmad and Warda  Farhan and Md  Ansari and Saba  Hoda and Varishth  Bhaskar},
        title={Enhancing Software Requirements Selection Process Using Genetic Algorithm},
        proceedings={Proceedings of the 3rd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2022, 24-25 March 2022, New Delhi, India},
        publisher={EAI},
        proceedings_a={ICIDSSD},
        year={2023},
        month={5},
        keywords={crossover fitness value genetic algorithm institute examination system mutation software requirements selection},
        doi={10.4108/eai.24-3-2022.2319030}
    }
    
  • Mohd. Nazim
    Javed Ahmad
    Warda Farhan
    Md Ansari
    Saba Hoda
    Varishth Bhaskar
    Year: 2023
    Enhancing Software Requirements Selection Process Using Genetic Algorithm
    ICIDSSD
    EAI
    DOI: 10.4108/eai.24-3-2022.2319030
Mohd. Nazim1,*, Javed Ahmad1, Warda Farhan1, Md Ansari1, Saba Hoda1, Varishth Bhaskar1
  • 1: Department of CSE, SEST, Jamia Hamdard, New Delhi 110062
*Contact email: mohdnazim@jamiahamdard.ac.in

Abstract

Software requirements selection is an important phase of the software development process. It is very difficult to decide the most important software requirements from a large set. Therefore, the capability of the genetic algorithm to assist in making better decisions on the software requirements selection is demonstrated in this paper using a practical case study. The objective of the genetic algorithm implemented in the software requirements selection function is to get a better decision in selecting the appropriate software requirements based on a range of criteria in various circumstances. To acquire information on assessment criteria and requirements, we used an Institute Examination System. The results obtained from experiments based on different criteria by prioritizing different software requirements have proved the capability of genetic algorithm to select the best solution. Our proposed genetic algorithm based software requirements selection approach is compatible with existing genetic algorithm based techniques and as well as the some other fuzzy based techniques also.