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Comparison of Model Size Predictors in Practice
- Source :
- ICSE (Companion Volume)
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- The amount of software in modern vehicles is constantly growing. However, the risk for functional and quality deficiencies increases simultaneously with size. This results in industry for example in inevitable and unexpected refactorings of software models, which is slowing down development processes in turn. In this industrial case study, we evaluate model growth predictors applied to foresee critical model size developments. We present five approaches and systematically compare them regarding prediction accuracy.
- Subjects :
- Computer science
business.industry
media_common.quotation_subject
020207 software engineering
02 engineering and technology
Reliability engineering
Data modeling
Software
Risk analysis (engineering)
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Quality (business)
business
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C)
- Accession number :
- edsair.doi...........959aaec111cf628f35ce8f7566919a8b
- Full Text :
- https://doi.org/10.1109/icse-c.2017.66