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How Do Quantifiers Affect the Quality of Requirements?

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Requirements Engineering: Foundation for Software Quality (REFSQ 2020)

Abstract

[Context] Requirements quality can have a substantial impact on the effectiveness and efficiency of using requirements artifacts in a development process. Quantifiers such as “at least”, “all”, or “exactly” are common language constructs used to express requirements. Quantifiers can be formulated by affirmative phrases (“At least”) or negative phrases (“Not less than”). [Problem] It is long assumed that negation in quantification negatively affects the readability of requirements, however, empirical research on these topics remains sparse. [Principal Idea] In a web-based experiment with 51 participants, we compare the impact of negations and quantifiers on readability in terms of reading effort, reading error rate and perceived reading difficulty of requirements. [Results] For 5 out of 9 quantifiers, our participants performed better on the affirmative phrase compared to the negative phrase. Only for one quantifier, the negative phrase was more effective. [Contribution] This research focuses on creating an empirical understanding of the effect of language in Requirements Engineering. It furthermore provides concrete advice on how to phrase requirements.

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  1. 1.

    https://doi.org/10.6084/m9.figshare.10248311.

References

  1. Atoum, I.: A novel framework for measuring software quality-in-use based on semantic similarity and sentiment analysis of software reviews. J. King Saud Univ. Comput. Inf. Sci. 32(1), 113–125 (2020)

    Google Scholar 

  2. Berry, D.M., Kamsties, E.: The syntactically dangerous all and plural in specifications. IEEE Softw. 22(1), 55–57 (2005)

    Article  Google Scholar 

  3. Chen, H., Cohen, P., Chen, S.: How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Commun. Stat. Simul. Comput. 39(4), 860–864 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  4. Christensen, K.R.: Negative and affirmative sentences increase activation in different areas in the brain. J. Neurolinguist. 22(1), 1–17 (2009)

    Article  Google Scholar 

  5. Cirilo, R.K., Foss, D.J.: Text structure and reading time for sentences. J. Verbal Learn. Verbal Behav. 19(1), 96–109 (1980)

    Article  Google Scholar 

  6. Cohen, J.: Statistical Power Analysis for the Behavioral Sciences. Routledge, New York (2013)

    Book  MATH  Google Scholar 

  7. Femmer, H., Vogelsang, A.: Requirements quality is quality in use. IEEE Softw. 36(3), 83–91 (2019)

    Article  Google Scholar 

  8. Femmer, H., Mèndez Fernàndez, D., Wagner, S., Eder, S.: Rapid quality assurance with requirements smells. J. Syst. Softw. 123, 190–213 (2017)

    Article  Google Scholar 

  9. Glanzberg, M.: Quantifiers, pp. 794–821. Oxford University Press, Oxford (2006)

    Google Scholar 

  10. Graesser, A.C., Hoffman, N.L., Clark, L.F.: Structural components of reading time. J. Verbal Learn. Verbal Behav. 19(2), 135–151 (1980)

    Article  Google Scholar 

  11. Keenan, E.L., Stavi, J.: A semantic characterization of natural language determiners. Linguist. Philos. 9(3), 253–326 (1986)

    Article  MATH  Google Scholar 

  12. Klare, G.R.: The measurement of readability: useful information for communicators. ACM J. Comput. Doc. 24(3), 107–121 (2000)

    Article  Google Scholar 

  13. MacKay, D.G.: To end ambiguous sentences. Percept. Psychophys. 1(5), 426–436 (1966)

    Article  Google Scholar 

  14. Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., Wesslén, A.: Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers, Norwell (2000)

    Book  MATH  Google Scholar 

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Correspondence to Katharina Winter or Andreas Vogelsang .

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Winter, K., Femmer, H., Vogelsang, A. (2020). How Do Quantifiers Affect the Quality of Requirements?. In: Madhavji, N., Pasquale, L., Ferrari, A., Gnesi, S. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2020. Lecture Notes in Computer Science(), vol 12045. Springer, Cham. https://doi.org/10.1007/978-3-030-44429-7_1

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  • DOI: https://doi.org/10.1007/978-3-030-44429-7_1

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