Operational System Test Method Using Dynamic Hooking
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Solution Overview
Problem
Current system test methods in IT fusion industries, such as healthcare and automotive, face challenges in identifying and locating faults in operational systems, especially in dynamic and real-time environments, with limited ability to detect latent faults that cause system downtime.
Innovation Solution
An operational system test method that defines a fault model, inserts a test agent, hooks a test location, collects test information, and removes the agent, utilizing profiling technology to minimize system overhead and detect faults in real-time, allowing for comprehensive testing of all processes during system operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system testing is performed in live operational environments with real data, then the ability to discover latent faults and system downtime causes is improved, but system overhead and complexity increase
Solution Approach 1:
The patent introduces a test agent as an intermediary component that mediates between the operational system and the testing framework. This agent intercepts API calls and injects test cases without requiring modifications to the core system code, thereby enabling comprehensive fault detection while maintaining system integrity and minimizing overhead.
Solution Approach 2:
The testing system is segmented into independent modular components including the test agent, fault model database, and result analysis module. This segmentation allows the testing functionality to be added without coupling it tightly to the operational system, reducing overall system complexity while enabling thorough testing.
2Measurement precision
If comprehensive testing of all processes is performed during system operation, then fault identification accuracy is improved, but processing time and system performance deteriorate
Solution Approach 1:
The system implements selective testing by allowing administrators to choose between comprehensive testing of all processes or targeted testing of specific modules based on risk assessment and operational criticality. This partial action approach maintains fault detection accuracy for critical functions while reducing overall processing overhead.
Solution Approach 2:
The testing framework employs periodic testing intervals and adaptive testing frequencies that adjust based on system state and fault severity. Critical system components are tested more frequently while less critical components undergo periodic testing, optimizing the balance between detection accuracy and processing speed.
3Loss of information
If test agents are inserted to intercept API calls and collect test information, then test information completeness is improved, but system resource consumption increases
Solution Approach 1:
The system performs preliminary analysis of API calls to determine which ones require detailed testing. By pre-identifying critical call patterns and using heuristics to filter obviously safe operations, the system collects comprehensive test information for only the necessary cases, reducing overall resource consumption while maintaining information completeness for fault detection.
Data Source
AI summary
The present invention features an operational system test method, comprising defining a fault model, inserting a test agent, hooking a test location, collecting test information, and removing the test agent. The invention also features an operational system test method, comprising defining a fault model, inserting a test agent, identifying a memory area according to a test location, hooking the identified memory area, collecting test information, and removing the test agent.