Workflow Impact Analysis Using Execution Trees for Targeted Testing
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Solution Overview
Problem
Current software testing methodologies for workflows are inefficient, incomplete, and computationally expensive, failing to identify all potential impacts and anticipate comprehensive testing scenarios, particularly in identifying affected nodes and branches, and do not consider simulating realistic execution scenarios or monitoring code changes.
Innovation Solution
An automated impact analysis system that monitors code repositories for changes, simulates workflows in a virtual sandbox environment, constructs execution trees, and identifies potentially affected nodes and branches to recommend targeted test cases for execution, using a knowledge base to map relationships between test cases and execution trees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive software testing is performed to identify all potential impacts of code changes, then testing completeness is improved, but computational cost and time consumption increase significantly
Solution Approach 1:
The patent segments the workflow into discrete nodes and branches, allowing impact analysis to focus only on affected segments rather than the entire workflow. This segmentation enables the system to identify and analyze only the portions of the workflow that may be impacted by code changes, reducing computational overhead while maintaining testing completeness for relevant areas.
Solution Approach 2:
The patent performs preliminary construction of execution trees and test case mappings before actual impact analysis occurs. By pre-establishing the relationships between workflow nodes, branches, and test cases, the system can quickly query and identify affected areas without performing comprehensive analysis during the testing phase, thus reducing computational time while ensuring thorough testing of impacted components.
2Reliability
If traditional impact analysis methodologies are used to identify affected workflow components, then potential risks are identified, but the process remains computationally expensive and inefficient
Solution Approach 1:
The patent replaces traditional mechanical impact analysis methodologies with an automated system that uses execution trees and pre-established mappings. Instead of manually or computationally intensive analysis of code dependencies, the system substitutes this with a structured approach using pre-built execution trees that map workflow nodes to test cases, dramatically improving analysis efficiency while maintaining accurate risk identification.
Solution Approach 2:
The patent creates a virtual representation (execution tree) of the workflow that copies and structures the actual workflow relationships. This copied structure allows for efficient analysis and query operations without directly manipulating the actual workflow or performing expensive computations on the real system, thereby improving productivity while preserving the accuracy of risk identification.
3Reliability
If all test cases are executed to ensure thorough testing, then testing coverage is improved, but resource consumption and execution time increase
Solution Approach 1:
The patent segments the test case execution set based on identified impacted workflow nodes and branches. By dividing the full test suite into relevant and irrelevant portions, the system executes only those test cases that correspond to affected areas, maintaining comprehensive coverage of impacted functionality while reducing overall resource consumption by excluding unnecessary test executions.
Solution Approach 2:
The patent applies partial action by executing only the necessary subset of test cases rather than the complete test suite. By identifying and executing only those test cases that are relevant to the code changes and impacted workflow areas, the system achieves sufficient testing coverage for the changes made without the excessive resource consumption of running all possible test cases.
Data Source
AI summary
An embodiment monitors a code repository for changes made to source code. The embodiment detects a change made to the source code, and upon detecting the change made to the source code, identifies a potentially impacted workflow node of a workflow based on the change made to the source code. The embodiment identifies an execution tree of the workflow that contains the potentially impacted workflow node. The embodiment identifies a set of test cases corresponding to the execution tree. The embodiment generates a test case recommendation based on the set of test cases identified. The embodiment transmits the test case recommendation to a user device.