Automated Testing Framework for Distributed CI Regression Isolation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing continuous integration (CI) toolsets are inadequate for supporting end-to-end testing in distributed computing environments, making it difficult to integrate and manage automated testing for applications that rely on such testing methodologies.
Innovation Solution
A system and method for continuous integration automated testing in a distributed computing environment that involves receiving data from a production database, executing baseline and new test runs, comparing results, and generating reports, with the ability to identify and disable commits causing regressions, and iteratively repeat tests to identify the root cause of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing open-source CI toolsets are used for coarse-grained job-level builds, then integration with TDD projects is improved, but support for end-to-end testing is insufficient
Solution Approach 1:
The patent introduces an intermediary testing framework that bridges the gap between existing CI toolsets and end-to-end testing requirements. This framework acts as a mediator layer that translates coarse-grained job-level builds into fine-grained test scenarios, enabling end-to-end testing without requiring fundamental changes to existing CI infrastructure.
Solution Approach 2:
The patent segments the monolithic end-to-end testing process into fine-grained, manageable test scenarios that can be executed within the constraints of existing CI toolsets. By breaking down complex end-to-end tests into smaller, modular scenarios, the system achieves both comprehensive testing coverage and compatibility with current CI infrastructure.
2Reliability
If fine-grained test scenarios are implemented, then test coverage is improved, but integration difficulty with existing CI frameworks increases
Solution Approach 1:
The patent designs a universal testing framework that can operate within existing open-source CI toolsets while supporting fine-grained test scenarios. The framework is built to be multi-functional, accommodating both unit tests and end-to-end tests, and can integrate with various CI platforms without requiring platform-specific implementations.
Solution Approach 2:
The patent changes the parameters of test execution by introducing configurable test scenario granularity, data set selection, and resource allocation parameters. These parameter changes enable fine-grained testing while maintaining compatibility with existing CI frameworks through standardized configuration interfaces and adaptive execution models.
3Measurement precision
If automated regression identification is implemented, then defect detection capability is improved, but computational resources increase
Solution Approach 1:
The patent implements partial regression identification by selectively analyzing only the portions of test results that are likely to contain regressions, rather than performing exhaustive analysis on all test data. This approach uses heuristics and historical data to focus computational resources on high-probability defect areas, achieving high detection precision with reduced resource consumption.
Solution Approach 2:
The patent incorporates feedback mechanisms where previous regression analysis results inform subsequent testing strategies. The system learns from historical defect patterns and adjusts its analysis focus dynamically, feeding back into the testing process to optimize resource allocation and improve detection efficiency over time.
Data Source
AI summary
In one embodiment, a method for continuous integration automated testing in a distributed computing environment may include receiving data for a computer application into an automated testing schema; at least one computer processor executing a baseline test run and storing baseline test run results; receiving new code for the computer application at a test environment; the at least one computer processor executing a test run and storing test run results; the at least one computer processor comparing the test run results to the baseline test run results; and the at least one computer processor generating at least one report based on the comparing.