Unified Data Extraction for Multi-Format System Settings
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Solution Overview
Problem
Existing techniques for managing information system settings require multiple analysis logic modules due to the variety of setting files and differences in file formats and description rules, leading to complex item value extraction processing.
Innovation Solution
An operation management apparatus that extracts data for each item from a collection file based on format information and delimiter character definitions, stores the data in a collected data table, and compares it with expected values in an expected value table to output comparison results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple analysis logic modules are used to handle different file formats and description rules, then the system can process various setting files, but the implementation of item value extraction processing becomes complicated
Solution Approach 1:
The patent applies universality by creating a single analysis logic module that can handle multiple file formats and description rules. The module uses a unified data structure with type identification to distinguish between different file types (CSV, TSV, XML, JSON) and applies format-specific parsing rules within the same module, eliminating the need for separate analysis logic for each file type while maintaining the ability to process various setting files.
Solution Approach 2:
The patent uses parameter changes by introducing a type identification field and format-specific parsing parameters within the unified analysis logic module. The module dynamically adjusts its behavior based on the detected file type and delimiter characteristics, changing its processing parameters rather than its fundamental structure, which allows it to adapt to different file formats without becoming complex.
2Measurement precision
If file-based difference comparison is performed, then comparison can be done for each file, but it is difficult to efficiently extract and compare item values across different file formats
Solution Approach 1:
The patent applies segmentation by dividing the comparison process into distinct stages: file type identification, format-specific parsing, extraction of item values into a unified structure, and then comparison. This segmentation allows each stage to be optimized independently - the unified data structure enables efficient comparison while the format-specific parsing stage handles the diversity of file formats, thereby improving both precision and efficiency.
Solution Approach 2:
The patent introduces a unified data structure as an intermediary between the diverse file formats and the comparison logic. This intermediary structure standardizes the representation of item values from different formats (CSV, TSV, XML, JSON) into a common format with type identification, enabling efficient and precise comparison without requiring the comparison logic to handle format-specific details directly.
Data Source
AI summary
An operation management apparatus includes an extraction unit that extracts data for each item from a collection file based on format information of the collection file collected from a component of an information system and definition information of a delimiter character between items defined by the component, a storage unit that stores the extracted data and the item in association with each other in a collected data table, and a comparison unit that compares data associated with an item common in an expected value table that stores an expected value of each item in the collection file and the collected data table, and outputs a comparison result.