Abstract
Context and Motivation: Natural language is the most common form to specify requirements in industry. The quality of the specification depends on the capability of the writer to formulate requirements aimed at different stakeholders: they are an expression of the customer’s needs that are used by analysts, designers and testers. Given this central role of requirements as a mean to communicate intention, assuring their quality is essential to reduce misunderstandings that lead to potential waste. Problem: Quality assurance of requirement specifications is largely a manual effort that requires expertise and domain knowledge. However, this demanding cognitive process is also congested by trivial quality issues that should not occur in the first place. Principal ideas: We propose a taxonomy of requirements quality assurance complexity that characterizes cognitive load of verifying a quality aspect from the human perspective, and automation complexity and accuracy from the machine perspective. Contribution: Once this taxonomy is realized and validated, it can serve as the basis for a decision framework of automated requirements quality assurance support.
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References
Ambriola, V., Gervasi, V.: Processing natural language requirements. In: Proceedings of 12th IEEE International Conference on Automated Software Engineering, pp. 36–45. IEEE, Incline Village, USA (1997)
Berander, P., Andrews, A.: Requirements prioritization. In: Aurum, A., Wohlin, C. (eds.) Engineering and Managing Software Requirements, Part 1, pp. 69–94. Springer Verlag, Heidelberg (2005)
Carew, D., Exton, C., Buckley, J.: An empirical investigation of the comprehensibility of requirements specifications. In: International Symposium on Empirical Software Engineering, p. 10. IEEE, Noosa Heads, Australia (2005)
Chen, F., Zhou, J., Wang, Y., Yu, K., Arshad, S., Khawaji, A., Conway, D.: Robust Multimodal Cognitive Load Measurement. Springer, Heidelberg (2016)
Chen, X., Francia, B., Li, M., McKinnon, B., Seker, A.: Shared information and program plagiarism detection. IEEE Trans. Inf. Theory 50(7), 1545–1551 (2004)
Damian, D., Chisan, J.: An empirical study of the complex relationships between requirements engineering processes and other processes that lead to payoffs in productivity, quality, and risk management. IEEE Trans. Softw. Eng. 32(7), 433–453 (2006)
Davis, A.M., Overmyer, S., Jordan, K., Caruso, J., Dandashi, F., Dinh, A., Kincaid, G., Ledeboer, G., Reynolds, P., Sitaram, P., Ta, A., Theofanos, M.: Identifying and measuring quality in a software requirements specification. In: Proceedings of 1st Intrnational Software Metrics Symposium, pp. 141–152. IEEE, Baltimore, USA (1993)
Fabbrini, F., Fusani, M., Gnesi, S., Lami, G.: An automatic quality evaluation for natural language requirements. In: Proceedings of 7th International Workshop on Requirements Engineering: Foundation for Software Quality. Interlaken, Switzerland (2001)
Femmer, H., Méndez Fernández, D., Wagner, S., Eder, S.: Rapid quality assurance with requirements smells. J. Syst. Softw. (2016, in Print)
Fowler, M., Highsmith, J.: The agile manifesto. Softw. Dev. 9(8), 28–35 (2001)
Génova, G., Fuentes, J.M., Llorens, J., Hurtado, O., Moreno, V.: A framework to measure and improve the quality of textual requirements. Requir. Eng. 18(1), 25–41 (2011)
Hassan, A.E., Hindle, A., Runeson, P., Shepperd, M., Devanbu, P., Kim, S.: Roundtable: what’s next in software analytics. IEEE Softw. 30(4), 53–56 (2013)
Heck, P., Zaidman, A.: A systematic literature review on quality criteria for agile requirements specifications. Softw. Q. J. (2016, in Print)
Kassab, M., Neill, C., Laplante, P.: State of practice in requirements engineering: contemporary data. Innov. Syst. Softw. Eng. 10(4), 235–241 (2014)
Pekar, V., Felderer, M., Breu, R.: Improvement methods for software requirement specifications: a mapping study. In: Proceedings of 9th International Conference on the Quality of Information and Communicating Technology, pp. 242–245. IEEE, Guimaraes, Portugal (2014)
Saavedra, R., Ballejos, L., Ale, M.: Software requirements quality evaluation: state of the art and research challenges. In: Proceedings of 14th Argentine Symposium on Software Engineering, Cordoba, Argentina (2013)
Sikora, E., Tenbergen, B., Pohl, K.: Industry needs and research directions in requirements engineering for embedded systems. Requir. Eng. 17(1), 57–78 (2012)
Sweller, J., Ayres, P., Kalyuga, S.: Intrinsic and extraneous cognitive load. In: Sweller, J., Ayres, P., Kalyuga, S. (eds.) Cognitive Load Theory. Explorations in the Learning Sciences, Instructional Systems and Performance Technologies, vol. 1, pp. 57–69. Springer, New York (2011)
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Unterkalmsteiner, M., Gorschek, T. (2017). Requirements Quality Assurance in Industry: Why, What and How?. In: Grünbacher, P., Perini, A. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2017. Lecture Notes in Computer Science(), vol 10153. Springer, Cham. https://doi.org/10.1007/978-3-319-54045-0_6
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DOI: https://doi.org/10.1007/978-3-319-54045-0_6
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