Data-driven elicitation, assessment and documentation of quality requirements in agile software development

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Abstract

Quality Requirements (QRs) are difficult to manage in agile software development. Given the pressure to deploy fast, quality concerns are often sacrificed for the sake of richer functionality. Besides, artefacts as user stories are not particularly well-suited for representing QRs. In this exploratory paper, we envisage a data-driven method, called Q-Rapids, to QR elicitation, assessment and documentation in agile software development. Q-Rapids proposes: (1) The collection and analysis of design and runtime data in order to raise quality alerts; (2) The suggestion of candidate QRs to address these alerts; (3) A strategic analysis of the impact of such requirements by visualizing their effect on a set of indicators rendered in a dashboard; (4) The documentation of the requirements (if finally accepted) in the backlog. The approach is illustrated with scenarios evaluated through a questionnaire by experts from a telecom company.

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Franch, X., Gómez, C., Jedlitschka, A., López, L., Martínez-Fernández, S., Oriol, M., & Partanen, J. (2018). Data-driven elicitation, assessment and documentation of quality requirements in agile software development. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10816 LNCS, pp. 587–602). Springer Verlag. https://doi.org/10.1007/978-3-319-91563-0_36

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