The Effects of Native Language on Requirements Quality

• Autorzy: Cowperthwaite Fayona , Horkoff Jennifer , Kopczyńska Sylwia

Identyfikatory

DOI

10.15439/2023F9537

• Języki publikacji: EN

Abstrakty

EN

[Context and motivation] More and more often software development projects involve participants of diverse nationalities and languages. Thus, software companies tend to use English as their business language. Moreover, to better prepare for future jobs, students consciously choose university courses in English. [Question/problem] As a result there is an increasing number of software engineers who are working or studying in a language which is not their native language. The question arises whether native language has an effect on the quality of natural language requirements. [Principal ideas/results] From the analysis of the requirements formulated by 44 participants of our empirical study, it follows that native language may have a negative effect on requirements quality, e.g., ambiguity, variability, and grammar issues. Furthermore, different native languages might drive to different quality issues. [Contribution] In order to prevent quality issues, our findings might be used by educators to adjust their materials to cater to different language groups, while practitioners might use them to improve their requirements review process.

Słowa kluczowe

EN

computer science; natural language; company; software; grammar; business

PL

informatyka; język naturalny; firma; oprogramowanie; gramatyka; biznes

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2023
• Tom: Vol. 35
• Strony: 913--917
• Opis fizyczny: Bibliogr. 16 poz., tab.

Twórcy

autor

Cowperthwaite Fayona

• University of Gothenburg Sweden

• https://orcid.org/0000-0002-7501-7048

autor

Horkoff Jennifer

• University of Gothenburg Chalmers University of Technology Sweden

• https://orcid.org/0000-0002-2019-5277

autor

Kopczyńska Sylwia

• Poznan University of Technology Poland

• https://orcid.org/0000-0002-9550-3334

Bibliografia

• 1. N. Kiyavitskaya, N. Zeni, L. Mich, and D. M. Berry, “Requirements for tools for ambiguity identification and measurement in natural language requirements specifications,” Requir. Eng., vol. 13, no. 3, pp. 207–239, 2008.
• 2. G. Génova, J. M. Fuentes, J. Llorens, O. Hurtado, and V. Moreno, “A framework to measure and improve the quality of textual requirements,” Requir. Eng., vol. 18, no. 1, pp. 25–41, 2013.
• 3. “Iso/iec/ieee international standard - systems and software engineering – life cycle processes – requirements engineering,” ISO/IEC/IEEE 29148:2018(E), pp. 1–104, 2018.
• 4. B. Wake, “INVEST in good stories, and SMART tasks - XP123,” https://xp123.com/articles/invest-in-good-stories-and-smart-tasks/, Aug. 2003, accessed: 2022-3-4.
• 5. “What does INVEST stand for?” https://www.agilealliance.org/glossary/invest/, Dec. 2015, accessed: 2022-3-4.
• 6. F. Fabbrini, M. Fusani, S. Gnesi, and G. Lami, “The linguistic approach to the natural language requirements quality: benefit of the use of an automatic tool,” in Proceedings 26th Annual NASA Goddard Software Engineering Workshop. IEEE Comput. Soc, 2002.
• 7. V. Antinyan, M. Staron, A. Sandberg, and J. Hansson, “A complexity measure for textual requirements,” in 2016 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (IWSM-MENSURA). IEEE, 2016.
• 8. E. Knauss and C. E. Boustani, “Assessing the quality of software requirements specifications,” in 2008 16th IEEE International Requirements Engineering Conference. IEEE, 2008.
• 9. F. Cowperthwaite, J. Horkoff, and S. Kopczyńska, “The Effects of Native Language on Requirements Quality - Additional Material,” Feb. 2023. [Online]. Available: https://doi.org/10.5281/zenodo.7649140
• 10. J. M. Saldana, The coding manual for qualitative researchers, 2nd ed. London: SAGE Publications, 2013.
• 11. M. Bano, “Addressing the challenges of requirements ambiguity: A review of empirical literature,” in 2015 IEEE Fifth International Workshop on Empirical Requirements Engineering (EmpiRE), 2015, pp. 21–24.
• 12. V. Gervasi, A. Ferrari, D. Zowghi, and P. Spoletini, “Ambiguity in requirements engineering: Towards a unifying framework,” in From Software Engineering to Formal Methods and Tools, and Back. Cham: Springer International Publishing, 2019, pp. 191–210.
• 13. B. Gleich, O. Creighton, and L. Kof, “Ambiguity detection: Towards a tool explaining ambiguity sources,” in Requirements Engineering: Foundation for Software Quality. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 218–232.
• 14. A. Bajceta, M. L. Ortiz, W. Afzal, P. Lindberg, and M. Bohlin, “Using nlp tools to detect ambiguities in system requirements - a comparison study,” in 5th Workshop on Natural Language Processing for Requirements Engineering @ REFSQ, March 2022. [Online]. Available: http://www.ipr.mdh.se/publications/6390-
• 15. G. Lucassen, F. Dalpiaz, J. M. E. M. van der Werf, and S. Brinkkemper, “Improving agile requirements: the quality user story framework and tool,” Requir. Eng., vol. 21, no. 3, pp. 383–403, 2016.
• 16. G. Lucassen, F. Dalpiaz, J. M. E. M. van der Werf, and S. Brinkkemper, “Forging high-quality user stories: Towards a discipline for agile requirements,” in 2015 IEEE 23rd International Requirements Engineering Conference (RE). IEEE, 2015.

Uwagi

1. Thematic Tracks Short Papers

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).