Test Algorithm for Railway Computing Error Detection
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Solution Overview
Problem
Existing methods for ensuring error-free processing in safety-relevant computing environments, such as those in railway applications, are inadequate as they fail to comprehensively detect hardware errors that do not affect calculation results and require significant storage capacity for software updates, limiting parallel storage of software versions.
Innovation Solution
A method that combines data segments and configuration data for application programs into a data set, generates unique ID codes for hardware and software components, and uses a hash function and calculation functions to create a complementary code for error detection, allowing for comprehensive error checking with reasonable computing effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software redundancy is implemented for error detection, then reliability is improved, but storage capacity requirements increase
Solution Approach 1:
The patent creates a test algorithm that generates a test value by copying and processing configuration data through a standardized function. This test value serves as a redundant check without requiring full software copying, thus reducing storage requirements while maintaining error detection capability.
Solution Approach 2:
The patent transforms configuration data into a different representation form (test value) through a standardized function. This transformation allows error detection without storing multiple versions of the original data, effectively changing the 'color' or form of the data to achieve redundancy with minimal storage overhead.
2Reliability
If comprehensive error checking is implemented for all hardware and software components, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal test algorithm that can check multiple components (hardware identifiers, software configuration data, program parameters) through a single standardized function. This multi-functional approach comprehensively checks all components without requiring separate complex checking mechanisms for each, thus reducing overall system complexity.
Solution Approach 2:
The patent changes the parameter representation by creating a standardized function that processes different types of data (hardware IDs, software configurations, program parameters) in a unified manner. This parameter transformation simplifies the checking process while maintaining comprehensive error detection coverage.
3Reliability
If software updates are stored parallel for verification, then reliability is improved, but storage capacity requirements increase
Solution Approach 1:
Instead of storing full software copies for verification, the patent generates a compact test value by processing configuration data through a standardized function. This copied transformation provides verification capability with minimal storage requirements.
Solution Approach 2:
The patent performs preliminary processing of configuration data to generate test values before actual software execution. This preliminary action allows verification to be built into the system architecture without requiring additional storage space for backup software versions.
Data Source
AI summary
A method performs a computer-assisted creation of a test algorithm for processing applications in a computing environment for executing a large number of application programs, by taking into account configuration data for the application programs. For each application program, a data segment is formed and the configuration data referring to the relevant application program is combined as a data segment. The data segments are combined in a data set. A global ID code is assigned to the data set. Participating components of the computing environment are identified, and an ID code assigned to them. A hash function is applied to each of the data segments contained in the data set. A calculation function is applied to each data segment in that the ID codes, the hash value of the relevant data segment and the global ID code are linked together by computational operators.