Dynamic Software Test Scenario Adaptation for Automotive Signal Processing
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Solution Overview
Problem
Testing software programs for signal processing in automobiles is time-consuming and prone to errors due to the difficulty in specifying signals similar to real-world scenarios, especially when internal signals need to be changed, leading to potential side effects if not properly removed.
Innovation Solution
A method and device for automated testing that allows dynamic adaptation of simulation scenarios based on the current system state, enabling interaction with the test platform to change stimulation signals and output values, using internal signals for reactive testing and recalculating criteria, with a domain-specific language for complex signal descriptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual specification of test signals is used to achieve realistic test scenarios, then test accuracy is improved, but time consumption and error probability increase
Solution Approach 1:
The test system automatically generates and adapts test signals based on the simulation model and current system state, eliminating the need for manual signal specification. The system serves itself by autonomously creating realistic test scenarios through automated signal generation algorithms that respond to simulated sensor inputs and system conditions.
Solution Approach 2:
The simulation model pre-defines realistic signal sequences and test scenarios before actual testing begins. By preparing test signal patterns and simulation environments in advance, the system eliminates time-consuming manual signal specification during the testing phase while maintaining test accuracy.
2Adaptability or versatility
If internal signals are changed during testing to achieve comprehensive coverage, then test completeness is improved, but side effects increase if changes are not properly removed
Solution Approach 1:
The system continuously monitors the current system state during testing and uses this feedback to dynamically adapt test signals and internal signal modifications. This closed-loop approach ensures that all signal changes are tracked and properly managed, allowing comprehensive test coverage while preventing unwanted side effects through automated state tracking and rollback capabilities.
Solution Approach 2:
The simulation model acts as an intermediary layer between the test controller and the software under test. This intermediary manages all signal modifications including internal signals, ensuring that changes are properly coordinated and removed after testing, thereby achieving comprehensive coverage without introducing side effects into the production code.
3Productivity
If automated testing is implemented to reduce time consumption, then productivity is improved, but adaptability to real-world scenarios decreases
Solution Approach 1:
The automated testing system dynamically adapts test signals and simulation parameters based on the current system state and simulated sensor inputs. This dynamic behavior allows the automated system to generate realistic, varied test scenarios that mirror real-world conditions, maintaining adaptability while preserving the efficiency benefits of automation.
Data Source
AI summary
The present disclosure relates to a method and a device for testing a software program. The method of the present disclosure simulates, in a simulation process, a predetermined scenario on a test platform in a test scenario. The test platform in this simulation process generates output values based on input stimuli, and a dynamic adaption of the test scenario takes place during the simulation process based on the current state of the simulation process.