Graphical Test Application Generation for Cloud Environment Consistency
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Solution Overview
Problem
Manual testing of numerous applications in cloud computing-based customer environments for consistency and adherence to rules is tedious and inefficient, as it requires significant time and effort to ensure all applications meet the required standards.
Innovation Solution
A graphical programming system that allows users to create and execute test applications without coding, using a graphical programming generation system to generate applications and a graphical programming test generation system to create tests, which can be easily integrated into customer environments to ensure consistency and adherence to rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing is used to ensure consistency and adherence to rules across numerous applications, then testing thoroughness is improved, but time consumption and effort increase significantly
Solution Approach 1:
The patent creates virtual copies of applications through graphical modeling. Testers can instantiate multiple copies of the same application model to perform comprehensive testing without manually recreating each application instance, significantly reducing time consumption while maintaining thoroughness.
Solution Approach 2:
The patent enables preliminary definition of testing rules, consistency requirements, and application behaviors through graphical models before actual testing execution. This preliminary action allows automated testing frameworks to efficiently validate numerous applications against pre-established criteria, reducing both time and effort.
2Reliability
If comprehensive testing of multiple applications is performed manually, then quality assurance is improved, but operational complexity increases
Solution Approach 1:
The patent segments the testing process into distinct graphical components: application models, testing rules, consistency requirements, and validation logic. Each segment can be independently configured, validated, and reused across multiple applications, simplifying the overall operational complexity while maintaining comprehensive quality assurance.
Solution Approach 2:
The patent creates universal graphical modeling constructs that can represent multiple applications and testing scenarios. A single graphical model framework can test diverse applications against common consistency rules and adherence requirements, reducing operational complexity through multi-functionality.
3Measurement precision
If detailed manual testing procedures are implemented, then testing precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent introduces graphical modeling constructs as intermediaries between testers and the complex testing procedures. These visual models serve as mediators that encapsulate detailed testing logic, allowing users to achieve high testing precision through intuitive graphical interfaces rather than complex manual procedures.
Solution Approach 2:
The patent replaces manual mechanical testing procedures with automated validation mechanisms driven by graphical models. The system automatically executes precise consistency checks and adherence validations based on visually defined rules, maintaining high precision while dramatically improving ease of operation.
Data Source
AI summary
A graphical programming test generation system and method are provided. The system, for example, may include, but is not limited to a graphical programming test generator comprising a processor and a memory, the processor configured to generate a graphical programming test generator interface to generate an application, including, but not limited to, a canvas, a plurality of tools, each of the plurality of tools, when added to the canvas, generating a customizable node, wherein one of the plurality of tools is a test node, which when added to the canvas marks the application as a test application and defines a trigger event for executing the test application, wherein the processor is configured to generate the test application based upon one or more customizable nodes added to the canvas, monitor a customer environment for events, and execute the test application upon detection of the trigger event defined for the test application.