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Validation of Model Metrics as Indicators on Model Quality

dc.contributor.advisorJamal Khrousheh
dc.contributor.authorOmar Ayoub
dc.date.accessioned2017-11-21T12:29:06Z
dc.date.available2017-11-21T12:29:06Z
dc.date.issued2012
dc.identifier.urihttps://hdl.handle.net/20.500.11888/11676
dc.description.abstractThis study is an empirical investigation of the relations between model measurements and model quality. The main objective of this study is to dene a set of model metrics which correlate strongly with failure reports and experts opinion. Then, to use these metrics as indicators on model quality and predictors of model failure. This study targets a group of `Simulink' models used in the development of embedded software within the automotive industry. Model Based Development has been a fundamental method in the development of embedded software in the automotive industry for the last two decades. Alongside empirical values, this study distinguish between all factors and variables which may efect the quality of a model as an inuence network. By identifying the inuential factors it will be possible to prevent negative development.en
dc.description.abstract This study is an empirical investigation of the relations between model measurements and model quality. The main objective of this study is to dene a set of model metrics which correlate strongly with failure reports and experts opinion. Then, to use these metrics as indicators on model quality and predictors of model failure. This study targets a group of `Simulink' models used in the development of embedded software within the automotive industry. Model Based Development has been a fundamental method in the development of embedded software in the automotive industry for the last two decades. Alongside empirical values, this study distinguish between all factors and variables which may efect the quality of a model as an inuence network. By identifying the inuential factors it will be possible to prevent negative development. ar
dc.titleValidation of Model Metrics as Indicators on Model Qualityen
dc.titleValidation of Model Metrics as Indicators on Model Qualityar
dc.typeGraduation Project


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