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The use of knapsack 0/1 in prioritizing software requirements and Markov chain to predict software success

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Abstract

Requirements prioritization is one of the most valuable aspects of software engineering. This is primarily due to the fact that resources, be it time, skillset, or budget, are limited. Existing complex methodologies, such as analytical heuristic process (AHP) and planning game, face low adoption in the industry, promoting the need for more accessible techniques. This research introduces a novel contribution to software engineering by offering a simple and scalable approach to requirement prioritization (RP) and software acceptance prediction. The proposed approach consists of two key methods, knapsack 0/1 and Markov, to optimize RP and predict software acceptance respectively. By considering constraints, organizations can make enlightened decisions on handling requirements and optimize their minimum viable product. The results showcase significant time efficiency, with an average worst-case time of 5.645s for 10,000 requirements and an upper bound of 0.023s for the Markov prediction. This study aims to provide practitioners with a practical solution for prioritizing requirements and predicting software outcomes from user acceptance tests. By simplifying the process and offering compelling time complexity, this approach contributes to the enhancement of software development practices.

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Acknowledgements

We want to thank the Department of computer science, KNUST for their support and encouragement which contributed to the success of the research conducted.

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This research did not receive any funding or grant from any organization, person, or body.

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Authors and Affiliations

  1. Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Isaac Aduhene Armah, James Ben Hayfron-Acquah, Kate Takyi, Rose-Mary Owusuaa Mensah Gyening & Michael Eshun

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  1. Isaac Aduhene Armah
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  2. James Ben Hayfron-Acquah
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  3. Kate Takyi
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  4. Rose-Mary Owusuaa Mensah Gyening
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All authors were involved equally in the preparation and writing of the manuscript, review of the manuscript, experimentations, implementations, and analysis of results. The order and appearance of author names do not bear any effect on their contribution.

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Correspondence to Kate Takyi.

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We declare that there are no competing interests concerning the research conducted. Non-financial interests: The research conducted bears no financial interests from any organization, persons, or bodies.

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Armah, I.A., Hayfron-Acquah, J.B., Takyi, K. et al. The use of knapsack 0/1 in prioritizing software requirements and Markov chain to predict software success. Int. j. inf. tecnol. 16, 1967–1979 (2024). https://doi.org/10.1007/s41870-023-01476-4

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