Automated Script Correlation for Dynamic Data Replay
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Solution Overview
Problem
Current automated testing utilities face challenges in efficiently replaying transaction scripts with dynamic data items, as they require manual iteration to find correct correlation values, leading to time-consuming and error-prone processes.
Innovation Solution
A method and system for generating a replayable testing script that compares multiple recorded scripts to identify dynamic data items, replacing static values with variable parameters to obtain current correlation values, reducing manual intervention and automating the correlation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual iteration is used to find correct correlation values for dynamic data items, then the testing script can be replayed, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system performs preliminary comparison of multiple recorded scripts to identify dynamic data items and their correlation values before the actual replay process. By pre-determining which data items are dynamic and extracting their correct correlation values from the recorded scripts, the system eliminates the need for manual iteration during replay, thus resolving the contradiction between reliable replay and time consumption
Solution Approach 2:
The testing utility automatically identifies dynamic data items and determines correlation values without requiring manual intervention. The system self-services by comparing recorded scripts, detecting changes in data items, and autonomously extracting correct correlation values, thereby eliminating time-consuming manual iteration while maintaining replay reliability
2Measurement precision
If manual correlation of dynamic data items is performed, then accurate replay can be achieved, but the process becomes complex and error-prone
Solution Approach 1:
The patent replaces the manual mechanical process of correlating dynamic data items with an automated computer-based system. The system automatically compares multiple recorded scripts, identifies dynamic data items through algorithmic detection, and extracts correlation values without human intervention. This substitution eliminates the complexity and error-proneness of manual correlation while maintaining high accuracy
Solution Approach 2:
The system changes the approach from manual parameter correlation to automated parameter extraction. By transforming the correlation process into an automated algorithmic operation that processes data items as parameters, the system reduces complexity while maintaining precision. The automated system handles parameter identification and extraction consistently, eliminating human error
3Extent of automation
If multiple recorded scripts are compared to identify dynamic data items, then automated correlation is achieved, but the initial processing requires computational resources
Solution Approach 1:
The system compares multiple recorded scripts to identify dynamic data items, which may involve processing more data than strictly necessary for a single test case. By analyzing multiple recorded scripts upfront, the system builds a comprehensive understanding of dynamic data patterns that can be reused across multiple test executions, amortizing the initial computational cost over multiple useful operations
Data Source
AI summary
A method for generating a replayable testing script for iterative use by an automated testing utility may include recording a plurality of scripts, each script relating to a separate iteration of a transaction between a user and a tested application performed by an operator. The method may also include comparing the recorded scripts to identify a location of a data item by finding different values in a pair of corresponding locations in the recorded scripts, indicative of a dynamic data item. The method may further include generating the replayable testing script comprising one of the recorded scripts and having a variable parameter at the identified location of the dynamic data item.