Unified Regression Platform for Statutory Report Testing
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Solution Overview
Problem
Organizations face significant manual labor costs and inaccuracies in regression testing of statutory reports due to software updates, which can introduce undetected bugs, leading to errors and potential fines, especially given the complexity of various technical file formats like CSV, JSON, and XML.
Innovation Solution
An automated unified regression platform that uses reference inputs to generate reference outputs, which are then regenerated and compared after software updates to detect any issues, presenting comparison results via a user interface for easy identification of differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated regression testing is implemented, then productivity and accuracy are improved, but device complexity increases
Solution Approach 1:
The regression testing platform is segmented into distinct functional modules: a reference file management module that stores and manages reference inputs and outputs, a regression testing module that performs automated testing operations, and a comparison module that analyzes differences between reference and regenerated files. This segmentation allows each module to handle specific tasks independently, improving overall system efficiency while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary processing layer that automatically converts regenerated files into formats suitable for comparison with reference files. This intermediary module handles format normalization and data transformation, enabling accurate comparison across different file types (CSV, JSON, XML) without requiring complex manual processing logic in the main testing platform.
2Reliability
If manual regression testing is performed, then ease of operation is maintained, but reliability deteriorates due to human error
Solution Approach 1:
The regression testing platform is designed to perform self-service operations by automatically generating test cases from reference files, executing the testing process without human intervention, and producing comparison results. The system self-manages the entire regression testing workflow including file regeneration, format conversion, and difference analysis, thereby eliminating human error while maintaining operational simplicity through automated workflows.
Solution Approach 2:
The system implements feedback mechanisms where comparison results between reference files and regenerated files are automatically analyzed and presented to users. The platform provides detailed feedback on any discrepancies detected, including specific location and nature of differences, enabling users to quickly identify and address issues without manual review of entire files.
3Measurement precision
If comprehensive regression testing is performed on multiple file formats, then measurement precision is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The regression testing module is designed with universal capabilities to handle multiple file formats (CSV, JSON, XML, and other technical formats) through a unified interface. The system employs format-agnostic processing logic that automatically detects and adapts to the input file type, applying appropriate parsing and comparison rules for each format without requiring separate testing procedures, thereby maintaining high measurement precision across diverse formats while simplifying the detection process.
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for unified regression testing. A first set of inputs configured to test a first scenario and a second set of inputs configured to test a second scenario may be received from a user. The first set of inputs may be used to generate a first set of outputs, and the second set of inputs may be used to generate a second set of outputs. A software update may be received. The first set of outputs may be regenerated using the first set of inputs, and the second set of outputs may be regenerated using the second set of inputs. The regenerated first set of outputs may be compared against the first set of outputs, and the regenerated second set of outputs may be compared against the second set of outputs. The comparison results may then be displayed to the user.