Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem
Context: The quantification of stakeholders plays a fundamental role in the selection of appropriate requirements, as their judgement is a significant criterion, as not all stakeholders are equally important. The original proposals modelled stakeholder importance using a weighting approach that may...
| Main Authors: | , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
Elsevier
2023
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/14524 |
| _version_ | 1789406403225452544 |
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| author | del Águila, Isabel M. del Sagrado, José |
| author_facet | del Águila, Isabel M. del Sagrado, José |
| author_sort | del Águila, Isabel M. |
| collection | DSpace |
| description | Context: The quantification of stakeholders plays a fundamental role in the selection of appropriate requirements, as their judgement is a significant criterion, as not all stakeholders are equally important. The original proposals modelled stakeholder importance using a weighting approach that may not capture all the dimensions of stakeholder importance. Furthermore, actual projects involve a multitude of stakeholders, making it difficult to consider and compute all their weights. These facts lead us to search for strategies to adequately assess the importance concept, reducing the elicitation effort.
Objective: We propose grouping strategies as a means of reducing the number of stakeholders to manage in requirement selection while maintaining adequate stakeholder coverage (how selection meets stakeholder demands).
Methods: Our approach is based on the salience of stakeholders, defined in terms of their power, legitimacy, and urgency. Diverse strategies are applied to select important stakeholder groups. We use k-means, k-medoids, and hierarchical clustering, after deciding the number of clusters based on validation indices.
Results: Each technique found a different group of important stakeholders. The number of stakeholder groups suggested experimentally (3 or 4) coincides with those indicated by the literature as definitive, dominant, dependent, and dangerous for 4 groups; or critical, major, and minor for 3 groups. Either for all the stakeholders and for each important group, several requirements selection optimisation problems are solved. The tests do not find significant differences in coverage when important stakehold-
ers are filtered using clustering, regardless of the technique and number of groups, with a reduction between 66.32% and 87.75% in the number of stakeholders considered.
Conclusions: Applying clustering methods to data obtained from a project is useful in identifying the group of important stakeholders. The number of suggested groups matches the stakeholders’ theory, and the stakeholder coverage values are kept in the requirement selection. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14524 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2023 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-145242023-04-28T09:56:39Z Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem del Águila, Isabel M. del Sagrado, José Computer Science. Software engineering Context: The quantification of stakeholders plays a fundamental role in the selection of appropriate requirements, as their judgement is a significant criterion, as not all stakeholders are equally important. The original proposals modelled stakeholder importance using a weighting approach that may not capture all the dimensions of stakeholder importance. Furthermore, actual projects involve a multitude of stakeholders, making it difficult to consider and compute all their weights. These facts lead us to search for strategies to adequately assess the importance concept, reducing the elicitation effort. Objective: We propose grouping strategies as a means of reducing the number of stakeholders to manage in requirement selection while maintaining adequate stakeholder coverage (how selection meets stakeholder demands). Methods: Our approach is based on the salience of stakeholders, defined in terms of their power, legitimacy, and urgency. Diverse strategies are applied to select important stakeholder groups. We use k-means, k-medoids, and hierarchical clustering, after deciding the number of clusters based on validation indices. Results: Each technique found a different group of important stakeholders. The number of stakeholder groups suggested experimentally (3 or 4) coincides with those indicated by the literature as definitive, dominant, dependent, and dangerous for 4 groups; or critical, major, and minor for 3 groups. Either for all the stakeholders and for each important group, several requirements selection optimisation problems are solved. The tests do not find significant differences in coverage when important stakehold- ers are filtered using clustering, regardless of the technique and number of groups, with a reduction between 66.32% and 87.75% in the number of stakeholders considered. Conclusions: Applying clustering methods to data obtained from a project is useful in identifying the group of important stakeholders. The number of suggested groups matches the stakeholders’ theory, and the stakeholder coverage values are kept in the requirement selection. 2023-04-28T09:56:39Z 2023-04-28T09:56:39Z 2023-04-19 info:eu-repo/semantics/article I.M. del Águila, J. del Sagrado, Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem, Information and Software Technology, Volume 160, 2023, 107231, ISSN 0950-5849, https://doi.org/10.1016/j.infsof.2023.107231. http://hdl.handle.net/10835/14524 10.1016/j.infsof.2023.107231 en https://www.sciencedirect.com/science/article/pii/S095058492300085X info:eu-repo/semantics/openAccess Elsevier Postprint accepted to information and software technology |
| spellingShingle | Computer Science. Software engineering del Águila, Isabel M. del Sagrado, José Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title | Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title_full | Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title_fullStr | Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title_full_unstemmed | Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title_short | Salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| title_sort | salience-based stakeholder selection to maintain stakeholder coverage in solving the next release problem |
| topic | Computer Science. Software engineering |
| url | http://hdl.handle.net/10835/14524 |
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