Automated Test Equipment Concurrent Scenario Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
System level tests (SLT) for devices under test (DUT) often face challenges due to unrealistic test conditions, long runtimes, and difficulties in debugging, as they typically run only a small subset of possible user scenarios and environments, leading to inefficient fault detection and debugging processes.
Innovation Solution
The method involves generating and executing multiple test scenarios with non-conflicting test activities and resources using automated test equipment (ATE), allowing concurrent testing and incorporating machine learning to optimize test sequences and predict test results, thereby improving test performance and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple test scenarios are executed concurrently to improve test coverage, then scenario coverage is improved, but resource conflicts occur leading to test failures
Solution Approach 1:
The patent segments test scenarios into groups based on resource requirements and constraints. The constraint solver divides the overall test suite into multiple independent test groups that can be executed concurrently without resource conflicts, thereby maintaining both high scenario coverage and test reliability.
Solution Approach 2:
The patent performs preliminary analysis of resource conflicts and constraints before executing tests. The constraint solver pre-processes test scenarios to identify and resolve potential conflicts in advance, creating a valid test schedule that prevents resource conflicts during actual test execution.
2Measurement precision
If system level tests are run to ensure realistic user scenarios, then fault detection capability is improved, but test runtime becomes extremely long
Solution Approach 1:
The patent applies partial action by selecting and executing only the most critical and informative test scenarios rather than running all possible system level tests. The constraint solver identifies a subset of tests that provides maximum fault detection capability with minimum runtime, avoiding unnecessary test execution.
Solution Approach 2:
The patent segments the comprehensive system level test suite into smaller, independent test groups that can be executed in parallel. This segmentation reduces the sequential runtime while maintaining fault detection capability through concurrent execution of multiple test scenarios.
3Productivity
If a small subset of test scenarios is executed to reduce runtime, then test runtime is reduced, but scenario coverage is limited
Solution Approach 1:
The patent transitions from sequential test execution to parallel/concurrent execution by adding the time dimension. Multiple test scenarios that would traditionally run one after another are executed simultaneously across multiple resources, thereby reducing total runtime while maintaining or improving scenario coverage.
Solution Approach 2:
The constraint solver performs preliminary optimization to select the most valuable test scenarios that maximize coverage per unit time. By pre-analyzing which tests provide the best coverage-efficiency ratio, the system executes a optimized subset that achieves high scenario coverage without unnecessary runtime overhead.
4Device complexity
If conventional test scheduling is used to manage test activities, then resource allocation is simplified, but resource conflicts occur leading to test failures
Solution Approach 1:
The patent introduces a constraint solver as an intermediary between test scenario definition and test execution. This intermediary automatically analyzes resource constraints, identifies conflicts, and generates a valid test schedule, thereby maintaining simple test activity definitions while ensuring conflict-free execution and high test reliability.
Solution Approach 2:
The constraint solver performs self-service by automatically detecting and resolving its own resource conflicts without external intervention. The system autonomously analyzes the test scenario portfolio, identifies scheduling conflicts, and generates an optimized test schedule that eliminates resource conflicts while maintaining comprehensive coverage.
Data Source
AI summary
Systems and methods for performing device testing using automatic test equipment that can advantageously utilize relatively large numbers of test scenarios and activities including multiple test steps and resources and that prevents test parameters from conflicting or colliding to improve test performance and accuracy are disclosed herein. The test activities of a given test scenario can be configured to be executed concurrently. The test activities can be associated with one or more test parameters characterized by respective test parameter values and/or are associated with one or more constraints.