A Rough-Set Theory based Approach for the Detection of Requirements Discordances among Stakeholders of an Information System

Faiz Akram , Tanvir Ahmad , Mohd Sadiq

Journal of Systems Science and Systems Engineering ›› : 1 -31.

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Journal of Systems Science and Systems Engineering ›› :1 -31. DOI: 10.1007/s11518-026-5727-7
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A Rough-Set Theory based Approach for the Detection of Requirements Discordances among Stakeholders of an Information System
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Abstract

Detection of discordances among the stakeholders is an important activity of stakeholders’ analysis process which needs to be completed prior to starting of the software requirements elicitation process. Various fuzzy based methods have been developed for the detection of discordances among the stakeholders in which vague or uncertain statements of stakeholders’ perceptions on software requirements are expressed by linguistic terms. Based on our review, we found that these methods focus on subjective justifications and lacks objectivity, and as a result it may affect the stakeholders’ analysis process and subsequently may lead to inappropriate decision-making during the information system development process. Therefore, to address this issue, in this paper we developed a method for the detection of discordances among stakeholders of an information system using rough-set theory. The implementation of the proposed method is discussed by considering the stakeholders and requirements of library information system.

Keywords

Functional requirements / non-functional requirements / fuzzy logic / rough-set theory / information system / software requirements elicitation

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Faiz Akram, Tanvir Ahmad, Mohd Sadiq. A Rough-Set Theory based Approach for the Detection of Requirements Discordances among Stakeholders of an Information System. Journal of Systems Science and Systems Engineering 1-31 DOI:10.1007/s11518-026-5727-7

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References

[1]

Achterkamp M C, Vos J F J. Critically identifying stakeholders: Evaluating boundary critique as a vehicle for stakeholder identification. Systems Research and Behavioral Science, 2007, 24(1): 3-14.

[2]

Ahmad Y, Wan-Kadir W M N, Husain S, Husain S, Ibrahim N. An intuitionistic fuzzy based approach to resolve detected ambiguities in the user requirements document. IEEE Access, 2021, 9: 114547-114563.

[3]

Akram F, Ahmad T, Sadiq M. Detection of requirements discordances among stakeholders under fuzzy environment. Evolution in Computational Intelligence: Proceedings of the 10th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2022), 2023. June 18–19.

[4]

Akram F, Ahmad T, Sadiq M. Recommendation systems-based software requirements elicitation process: A systematic literature review. Journal of Engineering and Applied Science, 2024, 71(1): 29.

[5]

Akram F, Ahmad T, Sadiq M. An integrated fuzzy adjusted cosine similarity and TOPSIS based recommendation system for information system requirements selection. Decision Analytics Journal, 2024, 11: 100443.

[6]

Baghizadeh Z, Cecez-Kecmanovic D, Schlagwein D. Review and critique of the information systems development project failure literature: An argument for exploring information systems development project distress. Journal of Information Technology, 2020, 35(2): 123-142.

[7]

Ballejos L C, Montagna J M. Method for stakeholder identification in interorganizational environments. Requirements Engineering, 2008, 13(4): 281-297.

[8]

Ballejos L C, Montagna J M. Modeling stakeholders for information systems design processes. Requirements Engineering, 2011, 16(4): 281-296.

[9]

Crane A, Ruebottom T. Stakeholder theory and social identity: Rethinking stakeholder identification. Journal of Business Ethics, 2011, 102: 77-87. Suppl..

[10]

Fuentes-Fernández R, Gómez-Sanz J J, Pavón J. Understanding the human context in requirements elicitation. Requirements Engineering, 2010, 15(3): 267-283.

[11]

Gartner Inc. Gartner forecasts worldwide IT spending to grow 7.5% in 2024, 2024

[12]

Gupta S K, Gunasekaran A, Antony J, Gupta S, Bag S, Roubaud D. Systematic literature review of project failures: Current trends and scope for future research. Computers & Industrial Engineering, 2019, 127: 274-285.

[13]

Hassan T, Mohammad C W, Sadiq M. StakeSoNet: Analysis of stakeholders using social networks. 2020 IEEE 17th India Council International Conference (INDICON), 2020. December 10–13, 2020.

[14]

Hassan T, Mohammad C W, Sadiq M. Using social network and fuzzy set theory for elicitation and prioritization of software requirements. International Journal of Computer Theory and Engineering, 2022, 14(3): 126-134.

[15]

Hidellaarachchi D, Grundy J, Hoda R, Madampe K. The effects of human aspects on the requirements engineering process: A systematic literature review. IEEE Transactions on Software Engineering, 2022, 48(6): 2105-2127.

[16]

Horkoff J, Aydemir F B, Cardoso E, Li T, Maté A, Paja E, Giorgini P. Goal-oriented requirements engineering: An extended systematic mapping study. Requirements Engineering, 2019, 24(2): 133-160.

[17]

Hughes D L, Rana N P, Simintiras A C. The changing landscape of IS project failure: An examination of the key factors. Journal of Enterprise Information Management, 2017, 30(1): 142-165.

[18]

Iriarte C, Bayona S. IT projects success factors: A literature review. International Journal of Information Systems and Project Management, 2020, 8(2): 49-78.

[19]

Kaiya H, Horai H, Saeki M. AGORA: Attributed goal-oriented requirements analysis method. Proceedings of the IEEE International Conference on Requirements Engineering, 2002. September 9–13, 2002.

[20]

Kaiya H, Shinbara D, Kawano J, Saeki M. Improving the detection of requirements discordances among stakeholders. Requirements Engineering, 2005, 10(4): 289-303.

[21]

Khan F M, Khan J A, Assam M, Almasoud A S, Abdelmaboud A, Hamza M A M. A comparative systematic analysis of stakeholder identification methods in requirements elicitation. IEEE Access, 2022, 10: 30982-31011.

[22]

Lang G, Miao D, Fujita H. Three-way group conflict analysis based on Pythagorean fuzzy set theory. IEEE Transactions on Fuzzy Systems, 2020, 28(3): 447-461.

[23]

Lee C, Lee H, Seol H, Park Y. Evaluation of new service concepts using rough set theory and group analytic hierarchy process. Expert Systems with Applications, 2012, 39(3): 3404-3412.

[24]

Lim S L, Finkelstein A. StakeRare: Using social networks and collaborative filtering for large-scale requirements elicitation. IEEE Transactions on Software Engineering, 2012, 38(3): 707-735.

[25]

Lim S L, Quercia D, Finkelstein A. StakeSource: Harnessing the power of crowdsourcing and social networks in stakeholder analysis. Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering, 2010. May 1–8, 2010.

[26]

Lim S L, Quercia D, Finkelstein A. StakeNet: Using social networks to analyse the stakeholders of large-scale software projects. Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering, 2010. May 1–8, 2010.

[27]

Lima Junior F R, Osiro L, Carpinetti L C R. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing Journal, 2014, 21: 194-209.

[28]

Lopes M E R F, Forster C H Q. Application of human error theories for the process improvement of Requirements Engineering. Information Sciences, 2013, 250: 142-161.

[29]

Mariyam F, Mehfuz S, Sadiq M. RAGOSRA: Rough attributed goal-oriented software requirements analysis method. Journal of Intelligent & Fuzzy Systems, 2023, 44(5): 7833-7843

[30]

McAulay L, Doherty N, Keval N. The stakeholder dimension in information systems evaluation. Journal of Information Technology, 2002, 17(4): 241-255.

[31]

Mohammad C W, Shahid M, Hussain S Z. Fuzzy attributed goal-oriented software requirements analysis with multiple stakeholders. International Journal of Information Technology, 2021, 13(6): 1-9.

[32]

Pacheco C, Garcia I. A systematic literature review of stakeholder identification methods in requirements elicitation. Journal of Systems and Software, 2012, 85(9): 2171-2181.

[33]

Perini A, Ricca F, Susi A, Bazzanella C. An empirical study to compare the accuracy of AHP and CBRanking techniques for requirements prioritization. Proceedings of the 5th International Workshop on Comparative Evaluation in Requirements Engineering (CERE), 2007. October 16, 2007.

[34]

Pawlak Z. Rough sets. International Journal of Computer and Information Sciences, 1982, 11(5): 341-356.

[35]

Pawlak Z. Rough set theory and its applications to data analysis. Cybernetics and Systems, 1998, 29(7): 661-688.

[36]

Pawlak Z, Skowron A. Rudiments of rough sets. Information Sciences, 2007, 177(1): 3-27.

[37]

Rauf M A, Bibi S, Ali S, AlSaedi T, Ur Rehman S, Mahmood K, Kundi M. A cost effective communication model for requirements elicitation in global software development. Scientific Reports, 2023, 13(1): 18730.

[38]

Remencius T, Sillitti A, Succi G. Assessment of software developed by a third-party: A case study and comparison. Information Sciences, 2016, 328: 237-249.

[39]

Sadiq M. A fuzzy set-based approach for the prioritization of stakeholders on the basis of the importance of software requirements. IETE Journal of Research, 2017, 63(5): 616-629.

[40]

Sadiq M, Devi V S. Prioritization and selection of the software requirements using rough-set theory. IETE Journal of Research, 2021, 69(8): 5169-5186.

[41]

Sadiq M, Devi V S. Fuzzy-soft set approach for ranking the functional requirements of software. Expert Systems with Applications, 2022, 193: 116452.

[42]

Sadiq M, Jain S K. A fuzzy based approach for the selection of goals in goal oriented requirements elicitation process. International Journal of System Assurance Engineering and Management, 2015, 6(2): 157-164

[43]

Sakthivel S. Methodological requirements for information systems development. Journal of Information Technology, 1992, 7(3): 141-148.

[44]

Schneider S, Wollersheim J, Krcmar H, Sunyaev A. How do requirements evolve over time? A case study investigating the role of context and experiences in the evolution of enterprise software requirements. Journal of Information Technology, 2018, 33(2): 151-170.

[45]

Shaikh A A, Karjaluoto H. Making the most of information technology & systems usage: A literature review, framework and future research agenda. Computers in Human Behavior, 2015, 49: 541-566.

[46]

Skowron A, Ramanna S, Peters J F. Conflict analysis and information systems: A rough set approach. Rough Sets and Knowledge Technology (RSKT 2006), 2006. July 24–26, 2006.

[47]

Standish Group. CHAOS report 2015, 2015

[48]

Sun B, Chen X, Zhang L, Ma W. Three-way decision making approach to conflict analysis and resolution using probabilistic rough set over two universes. Information Sciences, 2020, 507: 809-822.

[49]

Zhai L Y, Khoo L P, Zhong Z W. A rough set enhanced fuzzy approach to quality function deployment. International Journal of Advanced Manufacturing Technology, 2008, 37(5): 613-624.

[50]

Zhai L Y, Khoo L P, Zhong Z W. Towards a QFD-based expert system: A novel extension to fuzzy QFD methodology using rough set theory. Expert Systems with Applications, 2010, 37(12): 8888-8896.

[51]

Zhang Q, Xie Q, Wang G. A survey on rough set theory and its applications. CAAI Transactions on Intelligence Technology, 2016, 1(4): 323-333.

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