Automated Test Augmentation for Aviation Model Coverage Gaps
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Solution Overview
Problem
Current model-based development tools fail to support important coverage criteria like Modified Condition/Decision Coverage (MC/DC) and generate redundant test cases, while manual inspection of input sequences to drive internal variables to specific values is time-consuming, especially in large and complex aviation software systems.
Innovation Solution
An automated test case augmentation system that identifies and fills model test coverage gaps by translating coverage gap information into machine-readable mathematical test objectives, using test generators for model-checking and constraint solving, and applying conversion rules to generate test cases that satisfy strict test coverage criteria like MC/DC.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection is used to identify input sequences that drive internal variables to specific values, then test coverage requirements can be met, but the process becomes hard and time-consuming especially for large and complex aviation software systems
Solution Approach 1:
The patent replaces manual inspection (mechanical human effort) with automated analysis tools that use software agents to traverse design models, execute test cases, and generate coverage reports automatically. This substitution eliminates the time-consuming manual process while maintaining comprehensive test coverage requirements.
Solution Approach 2:
The system enables self-service by allowing the test generation process to automatically identify coverage gaps and generate additional test cases without human intervention. The automated analysis tools traverse the design model, execute tests, and augment the test suite based on coverage criteria, making the process self-sufficient and eliminating manual inspection requirements.
2Productivity
If conventional development tools are used to generate test cases, then basic coverage criteria can be satisfied, but important coverage criteria like MC/DC are not supported and redundant test cases are generated
Solution Approach 1:
The patent segments the test case generation process into distinct phases: initial test case generation, coverage analysis, gap identification, and automated augmentation. By dividing the process and applying different analysis techniques to each phase, the system can satisfy complex coverage criteria like MC/DC while eliminating redundant test cases through intelligent gap detection.
Solution Approach 2:
The system implements feedback loops where coverage analysis results are fed back into the test case generation process. The automated analysis tools continuously monitor coverage metrics and use this feedback to generate additional test cases that specifically target uncovered criteria, ensuring MC/DC and other important coverage requirements are met without redundancy.
3Measurement precision
If automated analysis tools are used to traverse design models and execute test cases, then comprehensive coverage analysis can be performed, but system complexity increases
Solution Approach 1:
The patent introduces automated analysis tools as intermediary components between the design model and the test case generation process. These tools act as mediators that automatically traverse the design model, execute test cases, and generate coverage reports, providing precise measurement of coverage while shielding users from the underlying system complexity through automated workflows and user-friendly interfaces.
Data Source
AI summary
A method for automated test case augmentation includes receiving, at an automated test augmentation system, a design model and model coverage gap information from a model-based development tool, translating the model coverage gap information into machine-readable mathematical test objective expressions, developing a set of test objective operators by translating the machine-readable mathematical test objective expressions, localizing target operators for the identified coverage gaps within the design model, attaching the test objective operators to target operators of the design model to create a test model, augmenting the test model by propagating test objectives at the target operators to a test node operator of the design model, and executing, by a test generator, the augmented test model to obtain the test cases to cover the coverage gaps and the causes for the model coverage gaps. A system for implementing the model-based design and a non-transitory computer readable medium are also disclosed.