Message Sequence Testing for Data Processing Robustness
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Solution Overview
Problem
Existing data processing systems face challenges in ensuring robust and error-free operation due to the complexity and variety of error types and sources, making it difficult to identify and eliminate faults effectively.
Innovation Solution
A method involving the generation of varied message sequences using a genetic algorithm to identify and prioritize the most problematic sequences, which are then processed by a receiving device to generate error alerts, facilitating the identification and elimination of faults or weak points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data processing systems are used with standard error checking methods, then the system can operate with basic reliability, but the system cannot effectively identify and eliminate rare or difficult-to-reproduce faults due to system complexity and variety of error types
Solution Approach 1:
The patent applies preliminary action by generating test message sequences in advance that specifically target potential error conditions and fault scenarios. These pre-generated test sequences are designed to provoke specific error types before actual system operation, allowing proactive identification of weaknesses without requiring complex real-time analysis during normal operation.
Solution Approach 2:
The patent implements feedback mechanisms by systematically analyzing error alerts generated from processing test message sequences. The system feeds back this error information to identify patterns, prioritize faults, and guide further testing or system improvements, creating a closed-loop approach to robustness optimization that manages complexity through iterative learning.
2Reliability
If comprehensive error checking and diagnostic tests are executed to identify all possible faults, then system robustness can be improved, but the time and resources required for testing and analysis increase significantly
Solution Approach 1:
The patent applies parameter changes by systematically varying message sequence parameters (such as timing, content, source, destination) to generate diverse test scenarios. This allows comprehensive coverage of potential error conditions by changing key parameters rather than executing exhaustive tests of all possible system states, significantly reducing testing time while maintaining effectiveness.
Solution Approach 2:
The patent implements local quality by prioritizing analysis of error alerts based on their significance, frequency, and impact. Instead of treating all errors equally, the system focuses resources on analyzing and addressing the most critical error patterns first, optimizing the balance between thoroughness and efficiency in fault identification.
3Adaptability or versatility
If message sequences are processed through complex bus connections with multiple components and interfaces, then the system can handle diverse communication scenarios, but it becomes difficult to determine whether errors originate from message sequences or from bus connection components
Solution Approach 1:
The patent applies the extraction principle by isolating message sequence generation and error analysis from the complex bus connection infrastructure. Test message sequences are generated and analyzed in a controlled environment that separates the message content from the transmission medium, allowing clear identification of whether errors originate from message sequences themselves or from bus connection components.
Solution Approach 2:
The patent uses an intermediary approach by introducing a dedicated test environment and analysis system that mediates between message sequence generation and bus connection processing. This intermediary layer provides controlled testing conditions and systematic error tracking, enabling clear distinction between message-related errors and transmission-related errors without limiting communication flexibility in production systems.
Data Source
AI summary
A method and a support device for supporting robustness optimization for a data processing system and a corresponding continuous integration system are disclosed. In the method, different message sequences are generated and sent to a receiving device. For each message sequence, error alerts generated by the receiving device are then detected. Depending on the number of error alerts generated in each case, one of the message sequences is categorized as the most problematic message sequence and output as a basis for a corresponding error correction.