Test Coverage Optimization for Mechatronic Systems

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Solution Overview

Problem

The increasing complexity of mechatronic systems and the growing number of possible test combinations in automotive development projects lead to time-consuming and costly test execution processes, with current methods struggling to efficiently manage test cases and environmental constellations, resulting in incomplete test coverage and resource inefficiencies.

Innovation Solution

A method that assigns test status values to each combination of test cases and configurations, determining relative test coverage and potential for increase, allowing for systematic selection and prioritization of test series to achieve maximum coverage, using predefined test status values and weighting parameters like path, speed, and effort to guide test planning and evaluation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If all test cases are executed with every possible environment configuration to ensure complete test coverage, then test completeness is improved, but testing time and costs increase enormously

Engineering Contradiction:
Improvetest coverage completenessVSAvoidtesting time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The system automatically determines the next optimal test configuration based on current test status and coverage metrics, eliminating the need for manual test planning and execution decisions. The test management system serves itself by autonomously selecting which test cases to execute next based on mathematical optimization of coverage metrics.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system dynamically changes test execution parameters by adjusting which test cases are selected based on current coverage status. Instead of executing all test cases statically, the system modifies the test execution plan in real-time based on calculated coverage metrics and optimization algorithms.

Inventive Principle:
Principle #35Parameter changes

2Productivity

If manual selection of test configurations is performed based on test manager experience, then testing speed is improved, but test coverage gaps increase

Engineering Contradiction:
Improvetest execution speedVSAvoidtest coverage completeness
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The system continuously monitors test execution status and coverage metrics, using this feedback to dynamically determine the next optimal test configuration. The feedback loop ensures that test selection is based on actual coverage data rather than subjective experience, systematically identifying and filling coverage gaps.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system pre-calculates the optimal test execution sequence by determining which test cases will provide the greatest coverage improvement. This preliminary determination of test priorities allows for systematic coverage optimization before execution begins, rather than relying on ad-hoc manual selection.

Inventive Principle:
Principle #10Preliminary action

3Reliability

If the number of test cases and environment configurations increases to cover more product variants, then test completeness is improved, but device complexity and management difficulty increase

Engineering Contradiction:
Improvetest coverage completenessVSAvoidtest management complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The test management system autonomously handles the complexity of managing numerous test cases and configurations by automatically determining optimal execution sequences. The system self-manages the complexity through algorithmic optimization rather than requiring manual coordination of increasing test elements.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system executes only the necessary subset of test cases required to achieve optimal coverage, rather than executing all possible test cases. By calculating and executing only the most impactful tests based on current coverage status, the system manages complexity while maintaining comprehensive coverage.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP3082000B1Method and system for testing a mechatronic system
Publication Date: 2020.06.10 DSPACE DIGITAL SIGNAL PROCESSING & CONTROL ENGINEERING GMBH
  • EP3082000B1 patent drawingFigure 1~2
  • EP3082000B1 patent drawing

AI summary

The invention relates to a computer-implemented method for testing a real and/or virtual part of a mechatronic automotive system (18) or another real and/or virtual mechatronic system (12) by means of a test using a test environment (16) that interacts with the real and/or virtual part of the mechatronic system (12), which comprises a test series with different test cases (TC1, TC2) of the test under different execution conditions, wherein these execution conditions are defined in test configurations (Conf1, Conf2).It is provided that each combination of test case (TC1, TC2) and test configuration (Conf1, Conf2) is assigned a test status value from a group of predefined test status values ​​(+, -, o) according to an evaluation of the function of the mechatronic system (12, 18) during the corresponding test. For further planning, execution, and/or evaluation of the test series, at least once a relative test coverage of at least one of the status values ​​(+, -, o) in the resulting test case-configuration matrix (TC1, TC2; Conf1, Conf2) is determined, and/or a relative potential for increasing the test coverage of at least one of the status values ​​(+, -, o) with respect to a test case (TC1, TC2) and/or with respect to a configuration (Conf1, Conf2) is determined. The invention further relates to a corresponding computer program product and a computer-based system for controlling corresponding tests.