Memory Error Detection Through Application Data Flow Replay
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Solution Overview
Problem
Existing memory error detection methods have a low reproduction rate (40% average) and struggle to analyze errors in specific application scenarios, requiring expensive equipment like high-order logic analyzers and digital storage oscilloscopes, which are labor- and time-consuming.
Innovation Solution
Utilizing an application platform as a test engine, capturing data flows with a logic analyzer, and processing them as memory test vectors to reproduce memory errors accurately, employing a circular buffer to record error nodes and historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-order logic analyzer and digital storage oscilloscope are used to analyze memory errors, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a virtual copy of the memory testing environment by capturing data flows from the application platform and reconstructing them in a software-based test system. This virtual copy allows memory error analysis without requiring physical high-order logic analyzers or digital storage oscilloscopes, thereby maintaining measurement precision while reducing device complexity and cost
Solution Approach 2:
The patent replaces the mechanical/physical testing equipment (logic analyzers, oscilloscopes) with a software-based data flow capture and processing system. By substituting physical measurement devices with computational methods that process captured data flows, the system achieves equivalent or superior measurement precision without the complexity and cost of high-end hardware equipment
2Measurement precision
If high-order logic analyzer and digital storage oscilloscope are used to search for memory error nodes, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary action by capturing and storing data flows from the application platform before memory errors occur. This pre-captured data is then processed to identify error nodes, eliminating the need for time-consuming real-time analysis with high-order equipment. The system prepares the testing environment and data in advance, enabling rapid error localization when errors occur
Solution Approach 2:
By creating a virtual copy of the memory system and processing captured data flows computationally, the patent enables rapid error node identification without the time constraints of physical high-order equipment. The software-based system can process and analyze data much faster than manual or hardware-based analysis methods
3Device complexity
If traditional memory testing methods are used, then device complexity is reduced, but reliability of error detection decreases
Solution Approach 1:
The patent introduces an intermediary component - the data flow capture module - that bridges the application platform and the memory test device. This intermediary captures the actual data flows passing through the system and provides them for analysis, enabling reliable error detection without requiring complex testing equipment. The intermediary acts as a mediator that simplifies the overall system while improving detection reliability
Data Source
AI summary
Disclosed are a method and system for detecting a memory error, and a device. The method includes: taking an application platform as a test engine of a memory test device, the application platform being provided with a system memory; capturing, by the memory test device, a data flow of an actual application program of the application platform on a memory transmission line in a manner including a logic analyzer; and taking, by the memory test device, a processed data flow as a memory test vector to test a tested memory device, thereby reproducing a memory error of the application platform or the application program on the memory test device. The present disclosure can reproduce all tested memory devices with an error in the application platform, and improves a reproduction rate for the memory error.