Data-Driven Performance Testing for Configuration Coverage
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Solution Overview
Problem
The fast-paced nature of software development often results in incomplete testing of software versions due to the large number of configurations, and relying on human oversight during weekends and holidays leads to inefficiencies and potential repetition of tests.
Innovation Solution
A computer-implemented method identifies an idle computing device and executes a candidate test based on a testing profile that includes a matrix of weights for various test configurations, ensuring comprehensive test coverage and minimizing machine idle time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive testing of all configurations is performed, then test coverage is improved, but testing time and resources are excessively consumed
Solution Approach 1:
The system performs partial testing by selecting and executing only the most critical and high-risk test configurations rather than all possible configurations. The test selection module uses risk assessment algorithms to identify which subset of tests provides the most value, thereby reducing overall testing time while maintaining adequate coverage of essential functionality.
Solution Approach 2:
The system dynamically adjusts testing parameters such as test selection criteria, priority levels, and resource allocation based on software version characteristics, risk profiles, and available resources. By changing these parameters adaptively, the system optimizes the balance between test coverage and testing time for different software releases.
2Ease of operation
If manual tracking of test configurations is used, then flexibility in test selection is maintained, but human error and inefficiency increase
Solution Approach 1:
The system automatically performs test configuration tracking, selection, and execution without requiring manual human intervention. The test selection module autonomously analyzes software versions, identifies relevant test configurations, and schedules tests based on predefined criteria and risk assessments, thereby eliminating human errors while maintaining operational flexibility through configurable parameters.
Solution Approach 2:
The system implements automated feedback loops where test results are continuously analyzed and used to refine future test selections. The system learns from previous test outcomes, identifies patterns in failing configurations, and adjusts test selection strategies accordingly, improving both efficiency and accuracy over time without additional human effort.
3Measurement precision
If more test configurations are executed, then test accuracy is improved, but machine idle time increases
Solution Approach 1:
The system maintains continuous productive operation by immediately queueing and executing the next relevant test configuration as soon as one completes. The test selection module ensures that computing resources are continuously utilized with high-priority tests, eliminating idle time while focusing on configurations that provide the most measurement accuracy and value.
Solution Approach 2:
The system dynamically adjusts the number and type of test configurations executed based on real-time conditions, software version characteristics, and risk assessments. Rather than statically determining all tests in advance, the system adapts its test selection criteria and priority levels during the testing process, optimizing both accuracy and resource utilization.
Data Source
AI summary
A method, computer program product, and computing system for identifying a computing device from a plurality of computing devices for executing a new test. Testing results associated with the identified computing device are processed from a database of testing results. A candidate test is identified from a plurality of tests to execute on the identified computing device by processing a testing profile associated with the identified computing device and the testing results associated with the identified computing device. The candidate test is executed on the identified computing device.