RPA Exception Handling Bot for Automated Test Error Analysis

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Solution Overview

Problem

End-to-end application testing faces challenges with automated test scripts failing due to application environment and data integrity issues, requiring increased human intervention for error analysis and resolution.

Innovation Solution

A system utilizing robotic process automation (RPA) for automated error analysis, which includes receiving exceptions from test scripts, determining exception types, and initiating exception handling bots to execute pre-configured or ad-hoc routines from a knowledge management database to resolve issues, with the option to update the database and employ machine learning for classification and user interface interaction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated test scripts are used to validate end-to-end application flows, then testing efficiency is improved, but the scripts fail due to application environment and data integrity issues requiring increased human intervention

Engineering Contradiction:

Improvetesting efficiencyVSAvoidtest script reliability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements self-service by automatically analyzing exceptions from test scripts and executing appropriate handling routines without human intervention. The exception handling bot autonomously retrieves handling routines from the knowledge management database and executes them to resolve test failures, enabling the system to service itself rather than requiring manual intervention for each failure.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system employs feedback mechanisms by continuously monitoring test script execution, capturing exceptions, analyzing their types, and using this information to automatically trigger appropriate handling routines. The feedback loop ensures that test failures are not merely recorded but actively addressed through automated exception handling, improving both reliability and productivity.

Inventive Principle:

Principle #23Feedback

2Reliability

If human intervention is increased for error analysis and resolution, then test script reliability is improved, but productivity decreases due to manual intervention requirements

Engineering Contradiction:

Improvetest script reliabilityVSAvoidtesting throughput

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system replaces manual human intervention with automated self-service capabilities. The exception handling bot automatically analyzes test failures, determines exception types, retrieves appropriate handling routines from the knowledge management database, and executes them without human involvement, thereby maintaining reliability while significantly improving productivity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent substitutes the mechanical system of manual human intervention with an automated robotic process automation system. The exception handling bot performs the same functions previously requiring human analysts to manually review and resolve test failures, but executes them automatically through programmed logic and AI-driven decision-making.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If exception handling routines are manually created and stored in knowledge management database, then adaptability to different exception types is improved, but device complexity increases

Engineering Contradiction:

Improveexception handling adaptabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements preliminary action by pre-creating and storing exception handling routines in the knowledge management database before actual test failures occur. These pre-configured routines are categorized by exception type and ready for immediate execution, allowing the system to adapt to various exception scenarios without requiring complex real-time decision-making logic.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The knowledge management database serves as a universal repository that stores multiple exception handling routines for different exception types in a single system. This multi-functional approach allows one database structure to handle diverse exception scenarios, improving adaptability while avoiding the complexity of separate specialized systems for each exception type.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20210109847A1System for automated error analysis in an application testing environment using robotic process automation

Publication Date: 2021.04.15 BANK OF AMERICA CORP

AI summary

Systems, computer program products, and methods are described herein for automated error analysis in an application testing environment using robotic process automation. The present invention is configured to electronically receive one or more exceptions from one or more automated test scripts; determine one or more exception types associated with the one or more exceptions; and initiate an exception handling bot configured to handle the one or more exceptions based on at least the one or more exception types.