Automated Application Failure Detection via Transaction Data Analysis
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Solution Overview
Problem
Existing solutions for monitoring and testing computer applications are inefficient, requiring significant effort and resources, failing to simulate real customer transactions, and unable to test applications in production after environmental or code changes, leading to high costs and disruptive impacts on businesses and customers.
Innovation Solution
A system that includes a non-transitory computer-readable medium and a processor to perform operations such as receiving monitoring requests, selecting automation scripts, performing tests, requesting analytic data, comparing it with a comparison model to detect failures, and generating reports, thereby automating the testing process and reducing manual effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing methods are used to identify and review failures, then testing coverage can be achieved, but significant effort and resources are required
Solution Approach 1:
The system enables self-service testing by automatically generating test scripts from customer transaction data and autonomously executing tests without requiring manual intervention from quality assurance teams. The system self-manages the entire testing workflow including script generation, execution, and result analysis.
Solution Approach 2:
The patent replaces manual mechanical testing processes with an automated computational system that uses algorithms to generate test scripts and execute tests, substituting human effort with machine-based automation.
2Adaptability or versatility
If traditional testing solutions are implemented, then testing can be performed, but they fail to simulate real customer transactions
Solution Approach 1:
The system performs preliminary action by collecting and analyzing actual customer transaction data before generating test scripts. This real data is used to create accurate test scenarios that reflect actual customer behavior and transaction patterns, ensuring tests simulate real-world conditions.
Solution Approach 2:
The patent applies parameter changes by using real customer transaction parameters (such as transaction amounts, frequencies, and patterns) to generate test scripts, rather than using static or hypothetical parameters. This dynamic parameter approach ensures tests accurately reflect real-world variations.
3Reliability
If existing testing solutions are used, then testing can be conducted, but they require significant effort to update and maintain program codes and testing data when applications change
Solution Approach 1:
The system applies dynamics by continuously adapting test scripts based on changes in the application under test. When the application changes, the system automatically updates test scripts to reflect new functionality, maintaining testing relevance without manual intervention and reducing maintenance complexity.
Solution Approach 2:
The patent implements universality by creating a multi-functional system that can test various application changes automatically. The same automated framework handles different types of application modifications (new features, bug fixes, configuration changes) without requiring separate maintenance processes for each scenario.
4Reliability
If manual testing approaches are employed, then testing can be performed, but costs are high and disruptions occur to business providers and customers
Solution Approach 1:
The system acts as an intermediary by running automated tests in isolated environments using synthetic customer data, rather than directly impacting production systems. This intermediary approach enables continuous testing without disrupting actual customer transactions or business operations.
Solution Approach 2:
The patent applies copying by creating synthetic copies of customer transaction data for testing purposes. These copied datasets replicate real customer behavior patterns without using actual customer information, enabling realistic testing without affecting real customers or business continuity.
Data Source
AI summary
Methods and systems for testing of at least one computer application include receiving from a user a monitoring request; selecting a script; performing at least one automation test with at least one automation application; requesting analytic data from at least one computer application; receiving analytic data associated with the at least one computer application; determining response data of the at least one computer application by inputting the analytic data to a comparison model determined based on an analysis technique configured to detect a failure by the at least one computer application; and generating a report based on an output of the analysis technique if the failure by the at least one computer application is detected.