Test Data File Creation via Parse Map Segmentation
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Solution Overview
Problem
Current methods for testing automated decisioning logic in financial institutions are inefficient and labor-intensive, as they rely on limited and changing test data files from credit bureaus, which fail to comprehensively test all aspects of the decisioning logic, leading to potential losses due to undetected errors in rare conditions.
Innovation Solution
A system and method for creating and modifying test data files using a parse map editor and test data file editor, which allows for the parsing, editing, and storage of data in native formats, enabling the creation of reusable test data files that can be translated across different providers and include expected results, facilitating automated regression testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If test data files are obtained from credit bureaus, then testing can be performed, but the test data files are limited and change formats, failing to comprehensively test all aspects of decisioning logic
Solution Approach 1:
The patent segments test data into multiple components including header information, transaction data, and trailer sections. Each segment can be independently created, modified, and validated, allowing comprehensive testing of decisioning logic across different data structures while maintaining adaptability to various formats.
Solution Approach 2:
The system allows dynamic modification of data parameters such as field lengths, delimiters, and data types through configuration files. This enables the same test data framework to adapt to different credit bureau formats and custom test scenarios, resolving the contradiction between comprehensive testing coverage and format adaptability.
2Reliability
If test data files are manually created and edited, then comprehensive test cases can be created, but the process is tedious, laborious, and time-consuming
Solution Approach 1:
The system provides templates and sample test data files that are pre-configured with common data structures and test scenarios. Users can start with these pre-prepared materials and make minimal modifications, significantly reducing the time and effort required to create comprehensive test cases while maintaining completeness.
Solution Approach 2:
The system allows users to copy existing test data files and segments, then modify them for different test scenarios. This reuse of proven test data structures ensures comprehensive testing coverage while eliminating the need to manually create every test case from scratch, reducing time and labor requirements.
3Productivity
If volume testing is used, then testing can be performed quickly, but certain conditions such as obscure or special test cases are missed
Solution Approach 1:
The system applies different testing strategies to different segments of test data. Common scenarios can be tested using automated volume testing for speed, while obscure or special test cases receive targeted manual verification and validation. This localized approach to quality assurance maintains both productivity and reliability by matching testing intensity to the specific needs of each test case category.
Data Source
AI summary
A system and method for creating and modifying test data files. The system comprises a parse map editor and a test data file editor, wherein parse maps are created and edited in the parse map editor, wherein the system parses incoming data files based on the parse maps that are created in the parse map editor, wherein each incoming data file is matched to a parse map, wherein the parsed data files are sent to the test data file editor, and wherein the test data file editor allows a user to view and edit the parsed data files. The method comprises parsing an incoming data file with a parse map, creating and/or editing the parse map in a parse map editor, and viewing and/or editing the parsed data file in a test data file editor.