Cloud-Assisted Behavioral Automated Testing for Dynamic User Scenarios
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Solution Overview
Problem
As computing systems become more complex, existing automated testing methods struggle to effectively handle dynamic user behavior and input, leading to stagnant test cases that fail to replicate real-world scenarios, making it difficult to identify and fix bugs without introducing new errors.
Innovation Solution
A cloud-assisted behavioral automated testing system that aggregates behavioral data from multiple sources, updates test cases based on usage patterns, and executes them in a controlled environment to simulate real-world user interactions, incorporating application, usage, and threat data to create a more realistic testing scenario.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional automated testing methods are used, then testing can be performed in controlled environments, but test cases become stagnant and fail to handle relevant user input and behavior
Solution Approach 1:
The system collects behavioral data from real user interactions with the product and feeds it back into the automated testing framework. This feedback loop enables test cases to be continuously updated with actual user input patterns, ensuring tests remain relevant and adaptive to real-world usage while maintaining reliable bug validation.
Solution Approach 2:
The automated testing system self-updates by automatically collecting behavioral data from production environments and using this data to generate and refine test cases without manual intervention. This self-service capability allows the system to maintain both reliability and adaptability simultaneously.
2Measurement precision
If test cases are developed manually, then they can be tailored to specific scenarios, but the process is difficult to create and tedious to execute
Solution Approach 1:
The system replaces manual test case creation and execution with an automated framework that uses behavioral data to generate test cases. This substitution maintains high measurement precision through data-driven scenario accuracy while dramatically improving productivity by eliminating manual intervention in test execution.
Solution Approach 2:
The system creates copies of real user behavior patterns from production data and uses these copies as test cases. This approach preserves the accuracy of real-world scenarios while enabling automated execution at scale, replacing manual test creation with data-driven replication.
3Stability of the object's composition
If testing is performed in controlled environments, then systems can be soaked and regression tested, but test cases fail to replicate real-world user input and behavior
Solution Approach 1:
The system introduces behavioral data as an intermediary between the controlled testing environment and real-world user behavior. This intermediary bridges the gap by injecting authentic user input patterns into the controlled environment, allowing regression and soak testing to maintain stability while preserving real-world behavior characteristics.
Data Source
AI summary
A computer readable storage medium, system and method for improving automated testing systems to include a first and second behavioral data. The first behavioral data is collected periodically and the second behavioral data is collected in real time. The receipt of the first behavioral data and a second behavioral data are followed by the receipt of a system configuration template. A test case is updated based on the first and second behavioral data, and an automated test environment is reconfigured based on the first behavioral data, second behavioral data, and the system configuration template. The test executes in the automated test environment producing a test result.