Intelligent Automation Test Workflow for Software
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Solution Overview
Problem
Large enterprises face challenges in efficiently testing software products due to the vast and constantly changing codebase, leading to lengthy test execution times and resource-intensive testing processes.
Innovation Solution
A system that generates metadata mapping test cases to programmatic flows and artifacts, allowing for the selection of a reduced test case set based on modified artifacts, thereby focusing testing on specific programmatic flows and corresponding tests, reducing the overall testing time and resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire accumulated test set is executed for quality control, then testing thoroughness is improved, but testing time and resource consumption increase significantly
Solution Approach 1:
The patent segments the large accumulated test set into smaller subsets based on programmatic flow groupings. By organizing test cases into groups associated with specific programmatic flows, the system can selectively execute only the relevant subsets of tests corresponding to modified artifacts, rather than running the entire test set. This segmentation enables efficient test selection while maintaining coverage of affected functionality.
Solution Approach 2:
The patent extracts and identifies only the necessary subset of test cases that are relevant to the current code changes. By analyzing the relationship between modified artifacts and programmatic flows, the system extracts the minimal required test set from the large accumulated test suite, eliminating unnecessary tests and reducing execution time while preserving testing effectiveness for changed areas.
2Reliability
If the entire accumulated test set is executed for quality control, then testing thoroughness is improved, but resource consumption increases significantly
Solution Approach 1:
The patent segments the large accumulated test set into smaller subsets based on programmatic flow groupings. By organizing test cases into groups associated with specific programmatic flows, the system can selectively execute only the relevant subsets of tests corresponding to modified artifacts, rather than running the entire test set. This segmentation enables efficient test selection while maintaining coverage of affected functionality.
Solution Approach 2:
The patent extracts and identifies only the necessary subset of test cases that are relevant to the current code changes. By analyzing the relationship between modified artifacts and programmatic flows, the system extracts the minimal required test set from the large accumulated test suite, eliminating unnecessary tests and reducing execution time while preserving testing effectiveness for changed areas.
3Productivity
If a reduced test case set is selected based on modified artifacts, then testing time and resource requirements are reduced, but testing coverage may be compromised
Solution Approach 1:
The patent performs preliminary analysis to establish metadata mappings between test cases, programmatic flows, and artifacts before the actual testing process. By pre-organizing test cases into groups associated with specific programmatic flows and documenting their relationships with artifacts, the system enables rapid identification of relevant tests when changes occur, ensuring that the reduced test set maintains appropriate coverage without requiring full test execution.
Data Source
AI summary
Techniques are included for intelligently testing a software product using a limited number of test cases that are configured to test portions of the software product that have changed since a prior testing. To determine which test cases are best used for testing the implemented changes, a test case-to-programmatic flow mapping may be generated that relates each test case available for testing the software product with each programmatic flow that is tested by the test case. In addition, a programmatic flow-to-artifact mapping may be created that relates each programmatic flow discovered in the software product to each artifact that is accessed, created, changed, or dependent on the programmatic flow. Using these mappings, specific test cases may be determined for testing only those portions of the software product that have changed since the prior testing.


