Software Metrics for Object-Relational Data Modeling
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Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to co...
Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling.
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