Abstract
The late correction of requirements costs up to 200 times as much as correction during requirement engineering. Requirements for systems do not arise naturally; they need to be engineered and done with great care and precision. Many software projects fall due to the elicitation of the requirements; for big data, it become more complicated due to its own specific characteristics; eliciting the requirements for big data must undertake the specific characteristics of big data such as (volume, variety, etc.); in fact, there are many research recommendation and perspectives in the literature to undertake big data characteristics, but unfortunately the studies to fill this gap are so rare. We analyzed the literature to identify the big data concepts that existing requirements engineering (RE) methods does not support. After, we elaborate an adopted KAOS method to make sure the elicitation of the requirements. We apply this new method (BKAOS) to an illustrative scenario to show its uses. We see that BKAOS is more suitable to elicit the requirements for big data projects and catch the right requirements; therefore, it reduce the effort and facilitate data analysis.
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References
Ali, R., Dalpiaz, F., Giorgini, P.: Requirements-driven deployment: customizing the requirements model for the host environment. Softw. Syst. Model. 13(1), 433–456 (2014). https://doi.org/10.1007/s10270-012-0255-y
Anderson, K.M.: Embrace the challenges: software engineering in a big data world. In: 2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering, pp. 19–25 (2015). https://doi.org/10.1109/BIGDSE.2015.12
Arruda, D.: Requirements engineering in the context of big data applications. ACM SIGSOFT Softw. Eng. Notes. 43(1), 1–6 (2018). https://doi.org/10.1145/3178315.3178323
Arruda, D., Madhavji, N.H.: State of requirements engineering research in the context of big data applications. In: Kamsties, E., Horkoff, J., Dalpiaz, F. (eds.) Requirements Engineering: Foundation for Software Quality, vol. 10753, pp. 307–323. Springer International Publishing (2018). https://doi.org/10.1007/978-3-319-77243-1_20
Attarha, M., Modiri, N.: Focusing on the Importance and the Role of Requirement Engineering 4. (n.d.).
Baig, M.I., Shuib, L., Yadegaridehkordi, E.: Big data adoption: state of the art and research challenges. Inf. Process. Manag. 56(6), 102095 (2019). https://doi.org/10.1016/j.ipm.2019.102095
Brambilla, M., Cabot, J., Wimmer, M.: Model-driven software engineering in practice: second edition. Synth. Lectures Softw. Eng. 3(1), 1–207 (2017). https://doi.org/10.2200/S00751ED2V01Y201701SWE004
Chen, M., Mao, S., Liu, Y.: Big Data: A Survey. Mob. Netw. Appl. 19(2), 171–209 (2014). https://doi.org/10.1007/s11036-013-0489-0
Chung, L., do Prado Leite, J.C.S.: On non-functional requirements in software engineering. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Conceptual Modeling: Foundations and Applications, vol. 5600, pp. 363–379. Springer, Berlin Heidelberg (2009). https://doi.org/10.1007/978-3-642-02463-4_19
Dardenne, A., van Lamsweerde, A., Fickas, S.: Goal-directed requirements acquisition. Sci. Comput. Program. 20(1–2), 3–50 (1993). https://doi.org/10.1016/0167-6423(93)90021-G
De Mauro, A., Greco, M., Grimaldi, M.: Understanding big data through a systematic literature review: the ITMI model. Int. J. Inf. Technol. Decis. Mak. 18(04), 1433–1461 (2019). https://doi.org/10.1142/S0219622019300040
Djeddi, C., Charrel, P.-J., Laboratory, I., Jaurès, J.: Extension of iStar for Big Data Projects, p. 8 (2018)
Eridaputra, H., Hendradjaya, B., Danar Sunindyo, W.: Modeling the requirements for big data application using goal oriented approach. In: 2014 International Conference on Data and Software Engineering (ICODSE), pp. 1–6 (2014). https://doi.org/10.1109/ICODSE.2014.7062702
Guzman, A., Martinez, A., Agudelo, F.V., Estrada, H., Perez, J., Ortiz, J.: A methodology for modeling ambient intelligence applications using i* framework. CEUR Workshop Proc. 1674, 6 (2016)
Horkoff, J., Aydemir, F.B., Cardoso, E., Li, T., Mate, A., Paja, E., Salnitri, M., Mylopoulos, J., Giorgini, P.: Goal-oriented requirements engineering: a systematic literature map. In: 2016 IEEE 24th International Requirements Engineering Conference (RE), pp. 106–115 (2016). https://doi.org/10.1109/RE.2016.41
IEEE Computer Society, ACM Sigsoft, IFIP Working Group 2.9: Classification of Research Efforts in Requirements Engineering. IEEE Computer Society Press (1997)
Katal, A., Wazid, M., Goudar, R.H.: Big data: issues, challenges, tools and good practices. In: 2013 Sixth International Conference on Contemporary Computing (IC3), pp. 404–409 (2013). https://doi.org/10.1109/IC3.2013.6612229
Lin, Y., Wang, H., Li, J., Gao, H.: Data source selection for information integration in big data era. Inf. Sci. 479, 197–213 (2019). https://doi.org/10.1016/j.ins.2018.11.029
Lockerbie, J., Maiden, N.A.M., Engmann, J., Randall, D., Jones, S., Bush, D.: Exploring the impact of software requirements on system-wide goals: a method using satisfaction arguments and i* goal modelling. Requir. Eng. 17(3), 227–254 (2012). https://doi.org/10.1007/s00766-011-0138-8
Madden, S.: From databases to big data. IEEE Internet Comput. 16(3), 4–6 (n.d.)
Madhavji, N.H., Miranskyy, A., Kontogiannis, K.: Big picture of big data software engineering: with example research challenges. In: 2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering, pp. 11–14 (2015). https://doi.org/10.1109/BIGDSE.2015.10
Mazón, J.-N., Pardillo, J., Trujillo, J.: A model-driven goal-oriented requirement engineering approach for data warehouses. In: Hainaut, J.-L., Rundensteiner, E.A., Kirchberg, M., Bertolotto, M., Brochhausen, M., Chen, Y.-P.P., Cherfi, S.S.-S., Doerr, M., Han, H., Hartmann, S., Parsons, J., Poels, G., Rolland, C., Trujillo, J., Yu, E., Zimányie, E. (eds.) Advances in Conceptual Modeling – Foundations and Applications, vol. 4802, pp. 255–264. Springer, Berlin/Heidelberg (2007). https://doi.org/10.1007/978-3-540-76292-8_31
Morandini, M., Penserini, L., Perini, A., Marchetto, A.: Engineering requirements for adaptive systems. Requir. Eng. 22(1), 77–103 (2017). https://doi.org/10.1007/s00766-015-0236-0
Noorwali, I., Arruda, D., Madhavji, N.H.: Understanding quality requirements in the context of big data systems. In: Proceedings of the 2nd International Workshop on BIG Data Software Engineering – BIGDSE ‘16, pp. 76–79 (2016). https://doi.org/10.1145/2896825.2896838
Otero, C.E., Peter, A.: Research directions for engineering big data analytics software. IEEE Intell. Syst. 30(1), 13–19 (2015). https://doi.org/10.1109/MIS.2014.76
Ramingwong, L.: A review of requirements engineering processes, problems and models. Int. J. Eng. Sci. Technol. 4, 6 (2012)
Sangeeta, Kapil, S.: Quality issues with big data analytics. In: 3rd International Conference on Computing for Sustainable Global Development (INDIACom). IEEE (2016)
van Lamsweerde, A.: Goal-oriented requirements engineering: a guided tour. In: Proceedings Fifth IEEE International Symposium on Requirements Engineering, pp. 249–262 (2000a). https://doi.org/10.1109/ISRE.2001.948567
van Lamsweerde, A.: Requirements engineering in the year 00: a research perspective. In: Proceedings of the 22nd International Conference on Software Engineering – ICSE ’00, pp. 5–19 (2000b). https://doi.org/10.1145/337180.337184
Werneck, V.M.B.: Comparing GORE Frameworks: I-star and KAOS. 12. (n.d.)
Yu, E. S.-K.: Modelling Strategic Relationships for Process Reengineering. 131. (n.d.)
Zowghi, D., Coulin, C.: Requirements elicitation: a survey of techniques, approaches, and tools. In: Aurum, A., Wohlin, C. (eds.) Engineering and Managing Software Requirements, pp. 19–46. Springer-Verlag (2005). https://doi.org/10.1007/3-540-28244-0_2
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Djeddi, C., Zarour, N.E., Charrel, PJ. (2022). A Requirement Elicitation Method for Big Data Projects. In: Sedkaoui, S., Khelfaoui, M., Benaichouba, R., Mohammed Belkebir, K. (eds) International Conference on Managing Business Through Web Analytics . Springer, Cham. https://doi.org/10.1007/978-3-031-06971-0_17
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