Abstract: Source code is analyzed to identify components. The components are each assigned a complexity score. Documentation for the source code is identified, related to the components, and given a score based on the quantity of the documentation for the component and the complexity score for the component. To determine semantic meaning of the documentation, vector embeddings for the documentation languages may be generated and aligned. Alignment causes the different machine learning models to generate similar vectors for semantically similar words in the different languages. Since the vectors of the words of the other languages are similar to the vectors of the words in a primary language with similar meanings, the vector representation of the documentation in the other languages will match the vector representation of the source code when the documentation is substantially on the same topic.

Abstract: Source code is analyzed to identify components. The components are each assigned a complexity score. Documentation for the source code is identified, related to the components, and given a score based on the quantity of the documentation for the component and the complexity score for the component. To determine semantic meaning of the documentation, vector embeddings for the documentation languages may be generated and aligned. Alignment causes the different machine learning models to generate similar vectors for semantically similar words in the different languages. Since the vectors of the words of the other languages are similar to the vectors of the words in a primary language with similar meanings, the vector representation of the documentation in the other languages will match the vector representation of the source code when the documentation is substantially on the same topic.

Abstract: The present disclosure involves systems, software, and computer implemented methods for automatic view generation based on annotations. One example method includes receiving a request to display a user interface view on a client device. Metadata that defines at least one entity included in at least one data source is received. Annotations that define user interface elements for displaying information for the at least one entity are received. A metamodel is generated using the received metadata and the received annotations. Native user interface elements are automatically generated using the metamodel. The native user interface elements are native to the client device. The native user interface elements in the user interface view on the client device.

Abstract: The present disclosure involves systems, software, and computer implemented methods for automatic view generation based on annotations. One example method includes receiving a request to display a user interface view on a client device. Metadata that defines at least one entity included in at least one data source is received. Annotations that define user interface elements for displaying information for the at least one entity are received. A metamodel is generated using the received metadata and the received annotations. Native user interface elements are automatically generated using the metamodel. The native user interface elements are native to the client device. The native user interface elements in the user interface view on the client device.