Automated Server Response Validation via Expected Data Comparison
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Solution Overview
Problem
Existing manual validation methods for data values in responses from server systems are inadequate, especially when dealing with complex data types and large volumes, as they require extensive manual intervention and are inefficient.
Innovation Solution
A system that constructs an expected response by retrieving data values directly from a data source and comparing them with the actual response, using templates and placeholders to automate the validation process, facilitating the identification of differences and ensuring accuracy without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation methods are used for data values in responses, then validation can be performed for simple data types, but the process becomes inadequate and inefficient for complex data types and large volumes of data
Solution Approach 1:
The patent creates a copy of the data source and constructs an expected response from it, then compares this copied version with the actual response from the server system. This allows automated validation of complex data types without manual intervention, resolving the contradiction between validation reliability and processing efficiency.
Solution Approach 2:
The patent replaces manual validation mechanisms with an automated computational system that retrieves data, constructs expected responses, and performs comparisons programmatically. This substitution enables efficient handling of large volumes of complex data while maintaining high validation accuracy.
2Reliability
If manual validation is performed, then some level of validation can be achieved, but extensive manual intervention is required which reduces efficiency
Solution Approach 1:
The system performs self-validation by automatically retrieving data from the data source, constructing expected responses, and comparing them with actual responses without requiring manual intervention. This self-service approach maintains validation capability while eliminating time loss associated with manual processes.
Solution Approach 2:
The patent performs preliminary actions by retrieving data from the data source and constructing the expected response in advance, before the comparison with the actual response. This preliminary preparation enables rapid validation execution, reducing the time required for the validation process while maintaining comprehensive validation capability.
3Productivity
If automated validation is implemented, then efficiency improves, but system complexity increases due to template construction and data retrieval mechanisms
Solution Approach 1:
The patent implements a universal validation system that can handle multiple data types (simple and complex) and various response formats through a single automated mechanism using templates and placeholders. This multi-functional approach increases validation throughput while managing system complexity through standardization.
Solution Approach 2:
The system manages complexity by changing parameters in a controlled manner - using templates with placeholders that can be parameterized for different data types and response formats. This allows the automated validation system to adapt to various scenarios without requiring fundamentally different mechanisms, maintaining productivity while controlling system complexity.
Data Source
AI summary
An aspect of the present disclosure facilitates validation of responses received from server systems. In one embodiment, data values are maintained in a data source. Upon sending a request containing a query criteria to a server system, the server system retrieves data values satisfying the query criteria from the data source. A (actual) response is received from the server system, the actual response containing data values retrieved by the server system. Data values satisfying the query criteria are also retrieved directly from the data source and an expected response is constructed by incorporating the directly retrieved data values. The data values contained in the expected and the actual responses are then compared to determine a difference between the expected and actual responses as a basis for validating the actual response received from the server system for the request.