Supporting defect causal analysis in practice with cross-company data on causes of requirements engineering problems
| Autor: | Aline Paes, Alexandre Ferreira, Daniel Méndez Fernández, Rodrigo O. Spínola, Pablo Curty, Marcos Kalinowski, Stefan Wagner, Michael Felderer |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Process management Requirements engineering Computer science business.industry Bayesian network Inference 020207 software engineering Context (language use) 02 engineering and technology Defect causal analysis Software Engineering (cs.SE) Computer Science - Software Engineering Software 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cross company business |
| Zdroj: | 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP). |
| DOI: | 10.1109/icse-seip.2017.14 |
| Popis: | [Context] Defect Causal Analysis (DCA) represents an efficient practice to improve software processes. While knowledge on cause-effect relations is helpful to support DCA, collecting cause-effect data may require significant effort and time. [Goal] We propose and evaluate a new DCA approach that uses cross-company data to support the practical application of DCA. [Method] We collected cross-company data on causes of requirements engineering problems from 74 Brazilian organizations and built a Bayesian network. Our DCA approach uses the diagnostic inference of the Bayesian network to support DCA sessions. We evaluated our approach by applying a model for technology transfer to industry and conducted three consecutive evaluations: (i) in academia, (ii) with industry representatives of the Fraunhofer Project Center at UFBA, and (iii) in an industrial case study at the Brazilian National Development Bank (BNDES). [Results] We received positive feedback in all three evaluations and the cross-company data was considered helpful for determining main causes. [Conclusions] Our results strengthen our confidence in that supporting DCA with cross-company data is promising and should be further investigated. 10 pages, 8 figures, accepted for the 39th International Conference on Software Engineering (ICSE'17) |
| Databáze: | OpenAIRE |
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