Database Schema Discovery for Unknown Result Structures
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Solution Overview
Problem
Developing software applications for communication devices is challenging due to limited resources and the complexity of accessing database data-sources with unknown result structures, as existing tools cannot facilitate communication with databases that have implicit result sets or weak cursors.
Innovation Solution
A method and tool, such as the data-source wizard, that identifies candidate subroutines, executes them, analyzes result sets, and supplements the schema metadata to describe the structure of exposed information, enabling the creation of proper application components even when result structures are unknown.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard exploration of data-source schema and metadata is used, then the development tool can create operations based on stored-procedures and user-functions, but it cannot handle implicit result sets or weak cursors that are not declared in the schema
Solution Approach 1:
The system performs preliminary exploration of the database by executing candidate subroutines and analyzing their result sets before application development. This advance action captures implicit result sets and weak cursors that are not declared in the schema, creating a comprehensive definition document that enables subsequent application development without encountering unknown result structures.
Solution Approach 2:
The system introduces an intermediary exploration process between the data-source schema and the application development tool. This intermediary executes subroutines, analyzes result sets, and supplements the schema metadata with discovered structures, acting as a mediator that bridges the gap between incomplete schema information and comprehensive application development requirements.
2Ease of manufacture
If applications are developed independently of the required interface to the backend server, then development flexibility is improved, but integration errors and compatibility issues increase
Solution Approach 1:
The system implements feedback by exploring the actual database interface and using the discovered result set structures to inform and constrain application development. The exploration process provides feedback about the true database interface, including implicit result sets, which guides developers to create applications that are both flexible and reliably integrated with the backend server.
Solution Approach 2:
The system performs preliminary exploration of the database interface before application development, capturing the actual structure including implicit result sets. This advance knowledge enables developers to create applications with proper integration from the outset, avoiding later compatibility issues while maintaining development flexibility.
3Ease of operation
If developers use a priori known result structures, then application development is simplified, but the system cannot handle databases with unknown or dynamic result sets
Solution Approach 1:
The system performs preliminary exploration of database subroutines to discover their actual result set structures before application development. This advance exploration captures implicit result sets and weak cursors, creating a comprehensive definition document that provides developers with complete structural information, enabling them to work with both known and previously unknown database interfaces with the same ease.
Solution Approach 2:
The system enables itself to automatically explore and discover database result set structures without requiring external documentation or manual configuration. The exploration process self-servicefully identifies candidate subroutines, executes them, analyzes result sets, and supplements the schema metadata, making the system adaptable to any database interface while maintaining developer ease of use.
Data Source
AI summary
A method is disclosed for facilitating development of an application having access to a database data-source. The method comprises the following steps. At least one subroutine that is a candidate for potentially including hidden information is identified. A definition document for the subroutine is generated using information available from its available schema metadata. The subroutine is executed via the database data-source. A result set of the executed subroutine is analysed for exposing any hidden information. The analysis is used to supplement the definition document with additional schema information to describe a structure of the exposed information. The definition document can then be used in developing the application. A development tool and computer readable medium configured to implement the method are also disclosed.


