Fuzzy-Based Methods for the Selection and Prioritization of Software Requirements: A Systematic Literature Review

Abstract

Software requirements (SRs) selection is one of the major research issues in the field of software engineering which is used to select the requirements from the list of the elicited SRs on the basis of their ranks. There are different fuzzy-based techniques for computing the ranking values of SRs. Based on our review, we found different studies which focus on the literature review of the SRs selection and prioritization. There is no study which synthesizes the SRs selection methods under a fuzzy environment. Therefore, to address this issue, this paper presents a systematic literature review (SLR) in the area of fuzzy-based methods for the selection of SRs. Four research questions (RQs) have been formulated to identify the research gaps in the literature: RQ1: What are the different fuzzy-based methods for the selection of the SRs? RQ2: Which fuzzy number is mostly used during the computation process? RQ3: What kinds of datasets have been used in the SRs selection methods? RQ4: Which system/application has been used to select the SRs? Search items were extracted from the Journals, Conferences, and Workshops based on the RQs. Our SLR has identified 54 different studies. Selected studies were accessed based on the RQs thus identifying the research issues in the literature. After the analysis of the 54 studies, it was identified that the area of SRs selection has lots of research issues which can be addressed by applying the other soft computing techniques to find out the ranking order of SRs.

Appendix

Appendix A: Included Studies

Paper ID	Complete reference
S1	Gulzar, K., Sang, J., Ramzan, M., Kashif, M.: Fuzzy approach to prioritize usability requirements conflicts: an experimental evaluation. IEEE Access 5, 13,570–13,577 (2017)
S2	Mougouei, D., Powers, D.: A fuzzy-based optimization method for integrating value dependencies into software requirement selection. arXiv: 2003.04806v1, pp. 1–15 (2020)
S3	Babar, M.I., Ghazali, M., Jawawi, D.N.A., Shamsuddin, S.M., Ibrahim, N.: PHandler: An expert system for a scalable software requirements prioritization process. Knowl. Based Syst. 84, 179–202 (2015)
S4	Alrashoud, M., Abhari, A.: Perception-based software release planning. Intell. Autom. Soft Comput. 21(2), 175–195 (2015)
S5	Hujainah, F., Bakar, R.B.A., Abdulgabber, M.A., Zamli, K.Z.: Software requirements prioritisation: a systematic literature review on significance, stakeholders, techniques and challenges. IEEE Access 6, 71,497–71,523 (2018)
S6	Quamar, M.B., Gazi, Y.: On fuzzy qualitative and quantitative softgoal interdependency graph. Int. J. Comput. Appl. 122(5), 30–35 (2015)
S7	Achimugu, P., Selamat, A., Ibrahim, R., Mahrin, M. N.: A systematic literature review of software requirements prioritization research. Inf. Softw. Technol. 56(6), 568–585 (2014)
S8	Mishra, N., Khanum, A., Agarwal, K.: A review on approaches to optimize the requirement elicitation process. Int. J. Inf. Res. Rev. 2(10), 1293–1298 (2015)
S9	Mougouei, D., Powers, D. M. W., Mougouei, E.: A fuzzy framework for prioritization and partial selection of security requirements in software projects. J. Intell. Fuzzy Syst. 37(2), 1–17 (2019)
S10	Dabbagh, M., Lee, S.P.: An approach for prioritizing NFRs according to their relationship with FRs. Lect. Notes Softw. Eng. 3(1), 1–5 (2015)
S11	Ramzan, M., Jaffar, A., Shahid, A.: Value based intelligent requirement prioritization (VIRP): expert driven fuzzy logic based prioritization technique. Int. J. Innov. Comput. Inf. Control 7(3), 1017–1038 (2011)
S12	Achimugu, P., Selamat, A., Ibrahim, R.: Using the fuzzy multi-criteria decision making approach for software requirements prioritization. Jurnal Teknologi 77(13), 21–28 (2015)
S13	Şen, C.G., Baraçlı, H.: Fuzzy quality function deployment based methodology for acquiring enterprise software selection requirements. Expert Syst. Appl. 37, 3415–3426 (2010)
S14	Momeni, H., Motameni, H., Larimi, M.: A neuro-fuzzy based approach to software quality requirements prioritization. Int. J. Appl. Inf. Syst. (IJAIS) 7(7), 15–20 (2014)
S15	Veena, N., D’Souza, R.: A survey on multi-criteria decision making methods in software engineering. Int. J. Innov. Sci. Res. Technol. 3(7), 1–9 (2018)
S16	Bukhsh, F.A, Bukhsh, Z.A., Daneva, M.: A systematic literature review on requirement prioritization techniques and their empirical evaluation. Comput. Stand. Interf. 69, 1–39 (2019)
S17	Ahmad J., Mohammad C. W., Sadiq M.: On software security requirements elicitation and analysis methods. Inf. Technol. Ind. 9(1), 1–13 (2021)
S18	Sadiq, M., Afrin, A.: An integrated approach for the selection of software requirements using fuzzy AHP and fuzzy TOPSIS method. Int. J. Adv. Res. Dev. 2(6), 170–183 (2017)
S19	Sadiq, M., Mohammad, C.W., Khan, S.: Methods for the selection of software requirements: a literature review. J. Eng. Technol. 8, 108–128 (2019)
S20	Gupta, A., Gupta, C.: A novel collaborative requirement prioritization approach to handle priority vagueness and inter-relationships. J. King Saud Univ. Comput. Inf. Sci. 1–25 (2019)
S21	Sadiq, M.: A fuzzy set-based approach for the prioritization of stakeholders on the basis of the importance of software requirements. IETE J. Res. 63(5), 1–14 (2017)
S22	Ejnioui, A., Otero, C.,Otero L.: A simulation-based fuzzy multi-attribute decision making for prioritizing software requirements. In: Proceedings of the 1st Annual Conference on Research in Information Technology, pp. 37–42. RIIT’12, New York, NY, USA: ACM (2012)
S23	Jawale, B., Bhole, A.T.: Adaptive fuzzy hierarchical cumulative voting: a novel approach toward requirement prioritization. Int. J. Res. Eng. Technol. 4(5), 365–370 (2015)
S24	Bakhtiar, A., Hannan, A., Basit, A., Ahmad,J.: Prioritization of value based services of software by using AHP and fuzzy kano model. In: Proceedings of 3rd International Conference on Computational and Social Sciences, pp. 48–56, Johor Bahru, Malaysia (2015)
S25	Sadiq, M., Jain, S.K.: A fuzzy based approach for requirements prioritization in goal oriented requirements elicitation process. In: Proceeding of 2013 International Conference on Software Engineering and Knowledge Engineering, June 27–29, pp. 1–5 (2013)
S26	Jawale, B.B., Patnaik, G.K., Bhole, A.T.: Requirement prioritization using adaptive fuzzy hierarchical cumulative voting. In: IEEE 7th International Advance Computing Conference, pp. 95–102, Hyderabad (2017)
S27	Gambo, I., Ikono, R., Achimugu, P., Soriyan, A.: An integrated framework for prioritizing software specifications in requirements engineering. Int. J. Softw. Eng. Appl. 12(1), 33–46 (2018)
S28	Babar, M. I., Ramzan, M., Ghayyur, S. A. K.: Challenges and future trendsin software requirements prioritization. In: International Conference on Computer Networks and Information Technology, pp. 319 –324 (2011)
S29	Sharif, N., Zafar, K., Zyad, W.: Optimization of requirement prioritization using computational Intelligence technique. In: International Conference on Robotics and Emerging Allied Technologies in Engineering, pp. 228–234 (2014)
S30	Malhotra, M., Bedi, R. P. S.: Analysis of software requirements prioritization techniques. In: Proceedings of 2nd International Conference on Computer Science Networks and Information Technology, pp. 195–200, Montreal, Canada (2016)
S31	Ashfaque, F., Kumar, R.: Elicitation of preference matrix and contribution values in goal models using fuzzy based approach. Adv. Comput. Sci. Inf. Technol. 2(9), 38–42 (2015)
S32	Dhingra, S., Savithri, G., Madan, M., Manjula, R.: Selection of prioritization technique for software requirement using fuzzy logic and decision tree. In: Online International Conference on Green Engineering and Technologies, pp. 1–11 (2016)
S33	Mougouei, D., Powers, D. M. W.: Dependency-aware software requirements selection using fuzzy graphs and integer programming. arXiv:2003.05785v1, pp. 1–45 (2020)
S34	Ejnioui, A., Otero, C.E., Qureshi, A.A.: Software requirement prioritization using fuzzy multi-attribute decision making. IEEE Conference on Open Systems, pp. 1–6 (2012)
S35	Nayak, V., D’Souza, R.G.L.: Comparison of multi-criteria decision making methods used in requirement engineering. CiiT Int. J. Artif. Intell. Syst. Mach. Learn. 11(5), 92–96 (2019)
S36	Ahmad, K.S., Ahmad, N., Tahir, H., Khan, S.: Fuzzy_MoSCoW: a fuzzy based MoSCoW method for the prioritization of software requirements. In: International Conference on Intelligent Computing, Instrumentation and Control Technologies, pp. 433–437 (2017)
S37	Sadiq, M., Jain, S.: Applying fuzzy preference relation for requirements prioritization in goal oriented requirements elicitation process. Int. J. Syst. Assur. Eng. Manage. 5, 711–723 (2014)
S38	Ramzan, M., Jaffar, M.A., Iqbal, M.A., Anwar, S., Shahid, A.A.: Value based fuzzy requirement prioritization and its evaluation framework. In: Fourth International Conference on Innovative Computing, Information and Control, ICICIC, pp. 1464–1468 (2009)
S39	Sadiq, M., Neha.: Elicitation of testing requirements from the selected set of software’s functional requirements using fuzzy based approach. In: International Conference on Computational Intelligence in Data Mining, Springer, pp. 429–437, Springer, India (2017)
S40	Singh, Y.V., Kumar, B., Chand, S.: A novel approach of requirements prioritization using logarithmic fuzzy trapezoidal AHP for enhancing academic library service. In: 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), pp. 1164–1172, Greater Noida, India (2018)
S41	Sadiq, M., Jain, S. K.: A fuzzy based approach for the selection of goals in goal oriented requirements elicitation process. Int. J. Syst. Assur. Eng. Manage. 6(2), 157–164 (2015)
S42	Devadas, R., Srinivasan, G.N.: Review of different fuzzy logic approaches for prioritizing software requirements. Int. J. Sci. Technol. Rese. 8(9), 296–298 (2019)
S43	Alrezaamiri, H., Ebrahimnejad, A., Motameni, H.: Solving the next release problem by means of the fuzzy logic inference system with respect to the competitive market. J. Exp. Theoret. Artif. Intell. 32(6), 959–976 (2019)
S44	Achimugu, P., Selamat, A., Ibrahim, R., Mahrin, M.N.: An adaptive fuzzy decision matrix model for software requirements prioritization. In: Nguyen, N.T., Kowalczyk, N.T. (Eds.) Advanced Approaches to Intelligent Information and Database Systems, pp. 129–138. Springer, Cham, Switzerland (2014)
S45	Lima, D., Freitas, F., Campos, G., Souza, J.: A fuzzy approach to requirements Prioritization. In: International Symposium on Search Based Software Engineering, pp. 64–69, Springer, Berlin Heidelberg (2011)
S46	Singh, Y.V., Kumar, B., Chand, S., Kumar, J.: A comparative analysis and proposing ‘ANN fuzzy AHP model’ for requirements prioritization. Int. J. Inf. Technol. Comput. Sci. 4, 55–65 (2018)
S47	Mishra, N., Khanum, M.A., Agrawal, K.: Approach to prioritize the requirements using fuzzy logic. In: ACEIT Conference Proceeding, pp. 42–47 (2016)
S48	Mohammad, C.W., Shahid, M., Hussain, S.Z.: Fuzzy attributed goal oriented software requirements analysis with multiple stakeholders. Int. J. Inf. Technol. 1–9 (2018)
S49	Mougouei, D., Powers, D.M.W.: Modeling and selection of interdependent software requirements using fuzzy graphs. Int. J. Fuzzy Syst. 19(6), 1812–1828 (2017)
S50	Gerogiannis, V. C.,Tzikas, G.: Using fuzzy linguistic 2-tuples to collectively prioritize software requirements based on stakeholders’ evaluations. In: Proceedings of the 21st Pan-Hellenic Conference on Informatics 48, pp. 1–6 (2017)
S51	Ramzan, M.: Intelligent requirement prioritization using fuzzy logic. National University of Computer and Emerging Sciences, Islamabad, Pakistan, pp. 1–155 (2010)
S52	Sadiq, M., Khan, S., Mohammad, C. W.: Selection of software requirements using TOPSIS under fuzzy environment. Int. J. Comput. Appl. (2020)
S53	Alrashoud, M., Abhari, A.: Planning for the next software release using adaptive network-based fuzzy inference system. Intell. Decis. Technol. 11(2), 153–165 (2017)
S54	Alrezaamiri, H., Ebrahimnejad, A., Motameni, H.: Software requirement optimization using a fuzzy artificial chemical reaction optimization algorithm. Soft Comput. 23, 9979–9994 (2019)

Appendix B: Results of the Quality Scores of the Selected 54 Studies

Paper ID	QA-1	QA-2	QA-3	QA-4	Score
S1	1.0	0.5	1.0	1.0	3.5
S2	1.0	1.0	1.0	0	3.0
S3	0.5	1.0	1.0	0	2.5
S4	1.0	0.5	1.0	0	2.5
S5	1.0	0.5	0.5	0	2.0
S6	1.0	1.0	1.0	0	3.0
S7	1.0	0	1.0	0	2.0
S8	1.0	0	1.0	0	2.0
S9	1.0	1.0	1.0	0.5	3.5
S10	0.5	0.5	1.0	0.5	2.5
S11	1.0	0.5	0.5	0	2.0
S12	1.0	1.0	0.5	1.0	3.5
S13	1.0	1.0	1.0	0.5	3.5
S14	1.0	1.0	0.5	0	2.5
S15	0.5	0.5	1.0	0	2.0
S16	1.0	0	1.0	0	2.0
S17	1.0	1.0	1.0	0	3.0
S18	1.0	1.0	1.0	0.5	3.5
S19	1.0	0.5	0.5	0	2.0
S20	1.0	1.0	0.5	0	2.0
S21	1.0	1.0	1.0	0	3.0
S22	1.0	0.5	1.0	0	2.5
S23	1.0	0.5	1.0	0	2.5
S24	0.5	1.0	0.5	0	2.0
S25	1.0	1.0	1.0	0	3.0
S26	1.0	0.5	0.5	0	2.0
S27	0.5	0.5	1.0	0.5	2.5
S28	1.0	0.5	1.0	0	2.5
S29	0.5	1.0	1.0	0	2.5
S30	0	0.5	1.0	0.5	2.0
S31	1.0	1.0	1.0	0.5	3.5
S32	1.0	1.0	1.0	0	3.0
S33	1.0	1.0	1.0	0	3.0
S34	1.0	0	1.0	0	2.0
S35	1.0	0	1.0	0	2.0
S36	1.0	1.0	1.0	0.5	3.5
S37	1.0	1.0	1.0	0	3.0
S38	1.0	0	1.0	0	2.0
S39	1.0	1.0	1.0	0	3.0
S40	1.0	1.0	1.0	1.0	4.0
S41	0.5	1.0	1.0	0	2.5
S42	1.0	0	1.0	0	2.0
S43	1.0	1.0	1.0	0	3.0
S44	0.5	1.0	0.5	0	2.0
S45	1.0	0.5	0.5	0	2.0
S46	0.5	1.0	1.0	0	2.5
S47	1.0	1.0	1.0	0	3.0
S48	1.0	1.0	1.0	0	3.0
S49	1.0	1.0	1.0	0	3.0
S50	1.0	0.5	1.0	0	2.5
S51	1.0	1.0	1.0	0	3.0
S52	1.0	1.0	1.0	0	3.0
S53	0.5	1.0	0.5	0	2.0
S54	0.5	1.0	1.0	0	2.5