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Using Bayesian networks to estimate strategic indicators in the context of rapid software development
dc.contributor.author | Manzano, Martí |
dc.contributor.author | Mendes, Emilia |
dc.contributor.author | Gómez Seoane, Cristina |
dc.contributor.author | Ayala Martínez, Claudia Patricia |
dc.contributor.author | Franch Gutiérrez, Javier |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació |
dc.date.accessioned | 2018-12-20T10:37:05Z |
dc.date.available | 2018-12-20T10:37:05Z |
dc.date.issued | 2018 |
dc.identifier.citation | Manzano, M., Mendes, E., Gómez, C., Ayala, C.P., Franch, X. Using Bayesian networks to estimate strategic indicators in the context of rapid software development. A: International Conference on Predictive Models and Data Analytics in Software Engineering. "Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering". New York: Association for Computing Machinery (ACM), 2018, p. 52-55. |
dc.identifier.isbn | 978-1-4503-6593-2 |
dc.identifier.uri | http://hdl.handle.net/2117/126068 |
dc.description.abstract | Background: During Rapid Software Development, a large amount of project and development data can be collected from different and heterogeneous data sources. Aims: Design a methodology to process these data and turn it into relevant strategic indicators to help companies make meaningful decisions. Method: We adapt an existing methodology to create and estimate strategic indicators using Bayesian Networks in the context of Rapid Software Development, and applied it to a use case. Results: Applying the methodology in the use case, we create a model to predict product quality based on software factors and metrics, using companies’ business knowledge and collected data. Conclusions: We proved the methodology’s feasibility and obtained positive feedback from the company’s use case. |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.publisher | Association for Computing Machinery (ACM) |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Enginyeria del software |
dc.subject.lcsh | Decision making |
dc.subject.lcsh | Bayesian statistical decision theory |
dc.subject.lcsh | Computer software -- Development |
dc.subject.other | Bayesian Network |
dc.subject.other | Rapid software development |
dc.subject.other | Strategic indicator |
dc.subject.other | Predictive analytics |
dc.subject.other | Business knowledge |
dc.subject.other | Heterogeneous data sources |
dc.subject.other | Large amounts |
dc.subject.other | Use-case |
dc.subject.other | Software design |
dc.title | Using Bayesian networks to estimate strategic indicators in the context of rapid software development |
dc.type | Conference report |
dc.subject.lemac | Decisió, Presa de |
dc.subject.lemac | Estadística bayesiana |
dc.subject.lemac | Programari -- Desenvolupament |
dc.contributor.group | Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering |
dc.identifier.doi | 10.1145/3273934.3273940 |
dc.relation.publisherversion | https://dl.acm.org/citation.cfm?id=3273940 |
dc.rights.access | Open Access |
local.identifier.drac | 23534269 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/732253/EU/Quality-Aware Rapid Software Development/Q-RAPIDS |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO/1PE/TIN2016-79269-R |
local.citation.author | Manzano, M.; Mendes, E.; Gómez, C.; Ayala, C.P.; Franch, X. |
local.citation.contributor | International Conference on Predictive Models and Data Analytics in Software Engineering |
local.citation.pubplace | New York |
local.citation.publicationName | Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering |
local.citation.startingPage | 52 |
local.citation.endingPage | 55 |