Driving Control Scenario Testing for State Transition Coverage

The patent implements feedback mechanisms where the system monitors actual state transitions during testing and compares them against expected transitions from the state control diagram. Test results feed back into the testing process to identify uncovered transitions, which then become targets for generating new test scenarios. This closed-loop feedback ensures both automation efficiency and comprehensive coverage of all state transitions.

The testing system dynamically adapts its behavior based on test progress. It transitions from random fuzz testing to targeted scenario generation when specific state transitions are identified as uncovered. The system dynamically adjusts test scenario selection and generation strategies to optimize both efficiency and coverage throughout the testing process.

The patent introduces an intermediary automated testing system that acts as a bridge between manual test design and system execution. This intermediary layer includes automated scenario generation, state transition monitoring, and test result analysis components that reduce the need for manual analysis while maintaining comprehensive coverage. The system automatically generates test scenarios based on state control diagrams and iteratively refines them to cover all transitions.

The testing process is segmented into distinct automated phases: state control diagram analysis, initial scenario generation, test execution, result analysis, and iterative refinement. Each phase is handled by specialized automated components, breaking down the complex testing task into manageable segments that can be executed and monitored systematically without requiring continuous manual intervention.

The patent performs preliminary analysis of the state control diagram to identify all possible state transitions and their conditions before actual testing begins. Test scenarios are pre-generated to target specific state transitions, and the system prioritizes testing of critical or frequently occurring transitions. This preliminary preparation enables efficient vulnerability discovery without requiring exhaustive testing of all possible scenarios.

The testing system dynamically changes parameters such as scenario selection priorities, test depth, and scenario generation rates based on testing progress and identified vulnerabilities. When critical vulnerabilities are found in frequently traversed state transitions, the system intensifies testing in those areas while reducing effort in less critical paths, optimizing the balance between vulnerability discovery and testing time investment.