Automated Decision Metaphor Testing Framework
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Solution Overview
Problem
Existing decision systems face inefficiencies in configuring business strategies and ensuring accurate operational decision-making due to manual errors in configuring decision metaphors and the need for extensive unit testing, which is costly and time-consuming.
Innovation Solution
A decision metaphor model tool reads electronic documents containing requirement analysis and design artifacts to create intermediate models, generating table import and profile files for testing, and automating the generation of thousands of test cases to exhaustively test decision metaphors, including boundary and negative conditions, thereby reducing manual effort and improving configuration accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration of decision metaphors is performed, then flexibility in configuring business strategies is achieved, but human errors increase and configuration accuracy decreases
Solution Approach 1:
The system performs self-verification through automated testing frameworks that automatically generate test cases, execute them against the decision metaphor configuration, and identify configuration errors without human intervention. This self-service mechanism maintains configuration accuracy while preserving manual configuration flexibility.
Solution Approach 2:
The testing framework provides immediate feedback on configuration correctness by automatically comparing actual test results against expected outcomes. This feedback loop enables rapid detection and correction of configuration errors, maintaining high accuracy in manual configuration processes.
2Reliability
If extensive unit testing is performed to ensure configuration correctness, then decision-making reliability is improved, but time consumption and costs increase
Solution Approach 1:
The system performs preliminary generation of comprehensive test cases automatically based on the decision metaphor configuration. By preparing the testing framework and test data in advance, the system enables rapid execution of extensive testing without proportional increases in time consumption or costs.
Solution Approach 2:
The patent replaces manual mechanical testing processes with automated computer-based testing frameworks. This substitution eliminates the need for human testers to manually execute each test case, dramatically reducing time consumption and costs while maintaining comprehensive testing coverage for high reliability.
3Reliability
If comprehensive test data is generated manually, then testing coverage is improved, but manual effort and costs increase
Solution Approach 1:
The testing framework automatically generates comprehensive test data by analyzing the decision metaphor configuration and autonomously creating appropriate test cases, test data, and expected outcomes. This self-service capability achieves complete testing coverage without requiring manual effort or incurring additional costs.
Solution Approach 2:
The automated testing framework serves multiple functions simultaneously: it generates test data, creates test cases, executes tests, and validates results. This multi-functionality replaces multiple manual processes with a single automated system, achieving comprehensive coverage while eliminating manual effort.
Data Source
AI summary
A testing framework associated with a decision metaphor model tool reads table profile files to generate requests for a test of a decision metaphor. The testing framework sends the requests for the test to a decision engine and receives responses for the requests for comparison against expected values and possible errors. The testing framework also outputs an output file that includes a result of the test, where the output file is formatted in a computer-displayable and user-readable graphical format.