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A Controlled Experiment on Comparison of Data Perspectives for Software Requirements Documentation

  • Research Article - Computer Engineering and Computer Science
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Abstract

Requirements define what the stakeholders or end users want and what the system must have to satisfy their needs. The reason for poor requirements arises from a documentation format that paints an incomplete picture. Documentation methods lacking necessary details cause requirements engineers to waste time arguing over what to do and how to do it. This causes budget and schedule overruns. This research was conducted using the E-market application domain as a test context. Three documentation data perspectives were evaluated, namely entity relationship diagram (ERD), natural language (NL), and class diagram (CD), which are frequently applied to document stakeholders’ statements. Due to the lack of research in this area, a controlled experiment was conducted focusing on requirements documentation, in which ERD, NL, and CD were compared among 103 participants. The philosophy of this controlled experiment depends on the participant’s ability to transform each perspective into the use case model. This process will represent the efficiency of each perspective. It has been found that participants who used the ERD perspective had significantly higher scores in the experiment, reported a lower number of difficulties, and used less time than those who used the NL and CD perspectives. The study results indicate that the ERD is easier to understand, more helpful, and less time-consuming in documenting requirements than the other two perspectives. In conclusion, using the ERD perspective in developing the E-market application domain could be more effective for documenting preliminary requirements than the NL and CD perspectives.

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References

  1. Sharif, N.; Zafar, K.; Zyad, W.: Optimization of requirement prioritization using computational intelligence technique. In: Proceedings of the 2014 International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE 2014), Islamabad, Pakistan, pp. 228–234 (2014)

  2. Dragicevic, S.; Celar, S.: Method for elicitation, documentation and validation of software user requirements (MEDoV). In: Proceedings of the 2013 IEEE Symposium on Computers and Communications (ISCC), pp. 956–961 (2013)

  3. Pohl, K.; Rupp, C.: Requirements Engineering Fundamentals: A Study Guide for the Certified Professional for Requirements Engineering Exam—Foundation Level—IREB Compliant, Based on the German Version 2.2, 2nd edn. Rocky Nook Inc, Santa Barbara, CA (2015)

    Google Scholar 

  4. Ibrahim, N.; Kadir, W.; Deris, S.: Documenting requirements specifications using natural language requirements boilerplates. In: Proceedings of the Malaysian Software Engineering Conference (MySEC), pp. 19–24 (2014)

  5. Abbasi, M.A.; Jabeen, J.; Hafeez, Y.; Batool, D.; Fareen, N.: Assessment of requirement elicitation tools and techniques by various parameters. Sci. Publ. Group 3(2), 7–11 (2015)

    Google Scholar 

  6. Snijders, R.; Ozum, A.; Brinkkemper, S.; Dalpiaz, F.: Crowd-centric requirements engineering: a method based on crowdsourcing and gamification. Technical Report, Utrecht, the Netherlands (2015)

  7. Sofian, H.; Salim, S.; Shahamiri, S.: A requirements negotiation process model that integrates EasyWinWin with quality assurance and multi-criteria preference techniques. Arab. J. Sci. Eng. 39(6), 4667–4681 (2014)

    Article  Google Scholar 

  8. Shafia, M.A.; Abdollahzadeh, S.: Integrating fuzzy Kano and fuzzy TOPSIS for classification of functional requirements in national standardization system. Arab. J. Sci. Eng. 39(8), 6555–6565 (2014)

    Article  Google Scholar 

  9. Al-Shamailh, A.: An experimental comparison of ER and UML class diagrams. Int. J. Hybrid Inf. Technol. 8(2), 279–288 (2015)

    Article  Google Scholar 

  10. Khan, Y.; Mahmood, S.: Generating UML sequence diagrams from use case maps: a model transformation approach. Arab. J. Sci. Eng. 41(3), 965–986 (2016)

    Article  Google Scholar 

  11. Ul-Arif, S.; Khan, Q.; Ghayyur, S.A.K.: Requirements engineering processes, tools/technologies, and methodologies. Int. J. Rev. Comput. 2(1), 41–56 (2009)

    Google Scholar 

  12. Zowghi, D.; Coulin, C.: Requirements elicitation: a survey of techniques, approaches, and tools. In: Engineering and Managing Software Requirements, pp. 19–46. Springer, Berlin (2005)

  13. Aceituna, D.; Do, H.; Walia, G.S.; Lee, S.W.: Evaluating the use of model-based requirements verification method: a feasibility study. In: Proceedings of the 1st International Workshop on Empirical Requirements Engineering (EmpiRE), pp. 13–20 (2011)

  14. Bures, T.; Hnetynka, P.; Kroha, P.; Simko, V.: Requirement specifications using natural languages. Technical Report, Charles University, Prague, Czech Republic (2012)

  15. Mishra, D.; Mishra, A.; Yazici, A.: Successful requirement elicitation by combining requirement engineering techniques. In: Proceedings of the 1st International Conference on the Applications of Digital Information and Web Technologies (ICADIWT), pp. 258–263 (2008)

  16. Matheson, D.: Modeling requirements: the customer communication. In: Proceedings of the 2014 IEEE 5th International Workshop on Requirements Prioritization and Communication (RePriCo 2014), pp. 15–24 (2014)

  17. Al-Rawas, A.; Easterbrook, S.: Communication problems in requirements engineering: a field study. In: Proceedings of the First Westminster Conference on Professional Awareness in Software Engineering, London, pp. 1–2 (1996)

  18. Firesmith, D.: Common requirements problems, their negative consequences, and the industry best practices to help solve them. J. Object Technol. 6(1), 17–33 (2007)

    Article  Google Scholar 

  19. Michael, K.A.; Boniface, K.A.: Inadequate requirements engineering process: a key factor for poor software development in developing nations: a case study. Int. J. Comput. Electr. Autom. Control Inf. Eng. 8(9), 1462–1465 (2014)

    Google Scholar 

  20. Pfleeger, S.L.; Atlee, J. M.: Capturing the requirements. In: Software Engineering: Theory and Practice, 4th edn. Prentice Hall, Upper Saddle River, NJ (2009)

  21. ArunKumar, G.; Dillibabu, R.: Design and application of new quality improvement model: Kano lean six sigma for software maintenance project. Arab. J. Sci. Eng. 41(3), 997–1014 (2016)

    Article  Google Scholar 

  22. Wohlin, C.; Runeson, P.; Höst, M.; Ohlsson, M. C.; Regnell, B.; Wesslén, A.: Experiment process. In: Experimentation in Software Engineering, pp. 73–88. Springer, Berlin (2012)

  23. Ho, S.-B.; Chai, I.; Tan, C.H.: Leveraging framework documentation solutions for intermediate users in knowledge acquisition. Int. J. Inf. Sci. 3(1), 13–23 (2013)

    Google Scholar 

  24. Truscan, D.; Fernandes, J.; Lilius, J.: Tool support for DFD-UML model-based transformations. In: Proceedings of the 11th IEEE International Conference and Workshop on the Engineering of Computer-Based Systems (ECBS’04), pp. 388–397 (2004)

  25. Liu, L.; Li, T.; Kou, X.: Eliciting relations from natural language requirements documents based on linguistic and statistical analysis. In: Proceedings of the IEEE 38th Annual Computer Software and Applications Conference, pp. 191–200 (2014)

  26. Easterbrook, S.: Class and entity relationship diagrams. University of Toronto, Canada. http://webcache.googleusercontent.com/search?q=cache:wbYFhHmokCoJ:www.cs.toronto.edu/~sme/CSC340F/2005/slides/tutorial-classes_ERDs.pdf+&cd=6&hl=en&ct=clnk (2005). Accessed 25 May 2016

  27. Byrne, B.M.; Qureshi, Y.S.: UML class diagram or entity relationship diagram? An object-relational conceptual impedance mismatch. In: Proceedings of 6th International Conference of Education, Research and Innovation (ICERI2013), Seville, Spain, pp. 3594–3604 (2013)

  28. Alkoshman, M.M.: Unified modeling language and enhanced entity relationship: an empirical study. Int. J. Database Theory Appl. 8(3), 215–227 (2015)

    Article  Google Scholar 

  29. Elmasri, R.; Shamkant, B.N.: Fundamentals of Database Systems, 6th edn. Addison-Wesley, Boston (2010)

    MATH  Google Scholar 

  30. Kamalrudin, M.; Grundy, J.; Hosking, J.: Tool support for essential use cases to better capture software requirements. In: Proceedings of the IEEE/ACM International Conference on Automated Software Engineering, pp. 255–264 (2010)

  31. Shoval, P.; Shiran, S.: Entity-relationship and object-oriented data modeling—an experimental comparison of design quality. Data Knowl. Eng. 21(3), 297–315 (1997)

    Article  MATH  Google Scholar 

  32. De Lucia A.; Gravino C.; Oliveto R.; Tortora G.: Data model comprehension: an empirical comparison of ER and UML class diagrams. In: Proceedings of 16th IEEE International Conference on Program Comprehension, pp. 93–102 (2008)

  33. Bavota, G.; Gravino, C.; Oliveto R.; De Lucia A.; Tortora G.; Genero M.; Cruz-Lemus, J. A.: Identifying the weaknesses of UML class diagrams during data model comprehension. In: International Conference on Model Driven Engineering Languages and Systems, pp. 168–182. Springer, Berlin (2011)

  34. De Lucia, A.; Gravino, C.; Oliveto, R.; Tortora, G.: An experimental comparison of ER and UML class diagrams for data modeling. Empir. Softw. Eng. 15(5), 455–492 (2010)

    Article  Google Scholar 

  35. Tichy, W.F.: Hints for reviewing empirical work in software engineering. Empir. Softw. Eng. 5(4), 309–312 (2000)

    Article  Google Scholar 

  36. Svahnberg, M.; Aurum, A.; Wohlin, C.: Using students as subjects-an empirical evaluation. In: Proceedings of the Second ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, pp. 288–290 (2008)

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Authors and Affiliations

  1. Faculty of Computing and Informatics, Multimedia University, 63100, Cyberjaya, Malaysia

    Iyas Ibriwesh, Sin-Ban Ho & Ian Chai

  2. Faculty of Management, Multimedia University, 63100, Cyberjaya, Selangor, Malaysia

    Chuie-Hong Tan

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  1. Iyas Ibriwesh
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  2. Sin-Ban Ho
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  3. Ian Chai
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  4. Chuie-Hong Tan
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Correspondence to Iyas Ibriwesh.

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Ibriwesh, I., Ho, SB., Chai, I. et al. A Controlled Experiment on Comparison of Data Perspectives for Software Requirements Documentation. Arab J Sci Eng 42, 3175–3189 (2017). https://doi.org/10.1007/s13369-017-2425-2

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  • DOI: https://doi.org/10.1007/s13369-017-2425-2

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