Data-Driven Elicitation, Assessment and Documentation of Quality Requirements in Agile Software Development [chapter]

Xavier Franch, Cristina Gómez, Andreas Jedlitschka, Lidia López, Silverio Martínez-Fernández, Marc Oriol, Jari Partanen
<span title="">2018</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
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
more &raquo; ... 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-91563-0_36">doi:10.1007/978-3-319-91563-0_36</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yn3hpsb5wbb25b3m4lahaydxhe">fatcat:yn3hpsb5wbb25b3m4lahaydxhe</a> </span>
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