Regression Test Reconstruction via Production Event Analysis
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Solution Overview
Problem
Current regression testing methods are inefficient and fail to accurately reflect real-world user activities, leading to manual effort inefficiencies and a mismatch between test cases and actual user interactions in production environments.
Innovation Solution
A system and method for reconstructing regression test cases using post-production events, which involves a test case reconstruction engine that extracts and compares pre-production and post-production identifiable elements to determine similarity and reconstruct test cases that align with actual user activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual test case creation based on best guess scenarios is used, then testing coverage can be achieved, but manual effort increases and test cases do not reflect actual user activities
Solution Approach 1:
The patent copies actual user activities from the production environment to create regression test cases. Post-production tools capture real user interactions, and these captured activities are automatically transformed into test cases, eliminating manual creation while ensuring high accuracy in reflecting actual user behavior.
Solution Approach 2:
The system enables self-service by automatically generating test cases from production user activities without requiring manual intervention. The post-production tools continuously capture user behaviors and automatically convert them into executable regression test cases, making the testing process autonomous and efficient.
2Reliability
If regression test cases are manually identified by subject matter experts, then relevant test cases can be selected, but testing efficiency decreases due to manual involvement
Solution Approach 1:
Instead of manual identification by experts, the system copies actual user activities from production to automatically determine which test cases are relevant. This automated copying process maintains high reliability by basing test selection on real user behavior while dramatically improving productivity by eliminating manual expert involvement.
Solution Approach 2:
The system implements feedback by continuously monitoring production user activities and using this information to dynamically adjust and update regression test cases. This closed-loop feedback mechanism ensures test cases remain relevant to actual user behavior while automating the selection process to improve efficiency.
3Reliability
If traditional regression testing is performed, then existing functionalities can be verified, but test cases become stagnant and fail to handle relevant user input and behavior
Solution Approach 1:
The patent transforms static, stagnant test cases into dynamic ones by continuously updating them with fresh user activities captured from production. Test cases are no longer fixed but evolve over time to reflect current user behavior patterns, maintaining both reliability for verifying existing functionalities and adaptability to handle relevant user input.
Solution Approach 2:
The system ensures continuity by continuously capturing user activities from production and continuously updating regression test cases. This ongoing process prevents test cases from becoming stagnant, ensuring they remain current and relevant to actual user behavior while maintaining continuous verification of existing functionalities.
4Measurement precision
If post-production tools are used to capture user activities, then real user behavior can be tracked, but the captured activities do not correspond to regression test cases in the testing environment
Solution Approach 1:
The system copies user activities from the production environment and automatically adapts them to the testing environment. By transforming real user interactions into standardized test case formats, it bridges the gap between production and testing, maintaining measurement precision while reducing environmental complexity mismatch.
Solution Approach 2:
The patent applies parameter changes by transforming production user activity data into testing environment-compatible formats. It adjusts parameters such as activity representation, timing, and context to match testing requirements, enabling accurate tracking of real user behavior while ensuring compatibility with the testing environment.
Data Source
AI summary
The present invention provides for a system and a method for reconstructing regression test cases using post production events. The present invention provides for a test case reconstruction engine configured to extract post-production identifiable elements associated with a post-production event and pre-production identifiable elements associated with a pre-production event. The present invention provides for a system and a method for determining similarity between the pre-production event and the post-production event based on a comparison of one or more pre-production parent identifiable elements and one or more pre-production child identifiable elements of a subject identifiable element, with the post-production identifiable elements. The present invention provides for a system and a method for reconstructing a regression test case based on a comparison of functions of the extracted pre-production identifiable elements and the post-production identifiable elements after the determination of similarity between the pre-production event and the post-production event.