Intelligent Automation Simulator for RPA Bot Validation
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Solution Overview
Problem
Robotic process automation (RPA) platforms face challenges in handling post-deployment problems, quality issues, and stabilization duration, requiring extensive human intervention and manual addressing of unexpected downtime, unknown popup windows, and data anomalies, which limits their efficiency and scope.
Innovation Solution
An intelligent automation simulator is introduced to automate testing and validation of robotic processes, utilizing scenario libraries, continuous learning, and AI-driven validation to detect functionalities, simulate scenarios, and generate execution plans, thereby reducing development and testing efforts and improving bot performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive human intervention is used to handle events and exceptions in RPA bots, then the bot can be reprogrammed to address specific events, but the scope and volume of use are limited due to manual reprogramming requirements
Solution Approach 1:
The system enables self-service through automated self-healing mechanisms. When events or exceptions occur during bot execution, the system automatically detects these issues, generates appropriate remediation actions, and applies fixes without requiring manual human intervention. This transforms the traditional model where humans must reprogram bots to handle exceptions into a system where the bot autonomously resolves its own issues, thereby expanding scope and volume of use while maintaining reliability
Solution Approach 2:
The system performs preliminary action by proactively generating and testing potential remediation scenarios before actual failures occur. The event simulation framework pre-generates various event scenarios and tests bot responses in advance, allowing the system to prepare automated responses that can be immediately applied when real events occur during production, eliminating the need for reactive manual reprogramming
2Manufacturing precision
If manual testing and validation methods are used for RPA bots, then development and testing efforts are extensive, but the stabilization duration and deployment time are increased
Solution Approach 1:
The system uses copying by creating virtual replicas of bot execution environments and event scenarios. Instead of manually testing each bot configuration in production-like settings, the system generates copies of bot instances and simulates various event scenarios in these copied environments. This allows comprehensive testing to be performed rapidly on copies rather than requiring extensive manual validation of the actual production bot, thereby maintaining testing thoroughness while reducing deployment time
Solution Approach 2:
The system performs preliminary action by conducting automated validation and testing before deployment. The event simulation framework pre-tests bot configurations against various event scenarios in a virtualized environment, identifying and resolving issues before the bot is deployed to production. This preliminary validation eliminates the need for extensive post-deployment manual testing and stabilization, significantly reducing deployment time while maintaining high testing standards
Data Source
AI summary
In an embodiment, a method includes receiving information identifying an input bot for testing. The method also includes detecting a functionality performed by the input bot. The method also includes creating a plurality of inputs for simulation of the functionality of the input bot. The method also includes executing the input bot a plurality of times using a same sample of actions. The method also includes checking for consistency of at least one of behavior and output for the same sample of actions. The method also includes executing the input bot a plurality of times using different samples of actions. The method also includes generating an execution plan for the input bot. The method also includes automatically validating the input bot, where the validation results in an automated determination of whether the input bot is defective.