Blockchain Script Management with AI Validation
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Solution Overview
Problem
In software development, managing scripts and coordinating between multiple teams for regression testing is cumbersome due to the lack of efficient tools, leading to difficulties in determining impacted modules and updating test scripts, especially in large projects where manual approaches like emails or central databases are inefficient.
Innovation Solution
A decentralized peer-to-peer system utilizing blockchain technology for storing and validating scripts, combined with AI for generating and updating test scripts, ensures that changes are recorded immutably and approved across teams without a single trusted intermediary, automating the detection of impacted components and test script modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual approaches (emails or central databases) are used for script management and coordination, then ease of operation is maintained, but productivity and reliability deteriorate due to inefficiency and lack of automation in large projects
Solution Approach 1:
The patent introduces a blockchain-based intermediary system that acts as a decentralized mediator for script management. Instead of relying on manual coordination or centralized databases, the blockchain serves as a trusted intermediary that automatically records, validates, and manages script changes across multiple teams and systems, thereby improving productivity without requiring complex manual processes
Solution Approach 2:
The system enables self-service automation where the blockchain network automatically performs script validation, impact analysis, and coordination tasks without human intervention. The decentralized system allows participants to independently interact with the blockchain to submit, validate, and track script changes, eliminating the need for manual coordination while maintaining simplicity in operation
2Reliability
If decentralized blockchain validation is implemented across multiple nodes, then reliability and security improve, but speed and time consumption worsen due to consensus requirements
Solution Approach 1:
The patent segments the validation process into distinct phases: local validation at individual nodes, endorsement collection from authorized participants, and final consensus at the ordering server. This segmentation allows parallel processing of validation tasks across multiple nodes simultaneously, maintaining high reliability through distributed verification while improving overall validation speed by avoiding sequential consensus requirements
Solution Approach 2:
The system performs preliminary validation actions at each node before final consensus is required. Nodes independently validate scripts against local copies of the world state and endorsement policies in advance, so that when consensus is needed, only final approval is required rather than complete validation, thereby maintaining reliability while significantly reducing the time consumed by consensus operations
3Reliability
If complete regression testing is performed across all software modules, then reliability improves, but loss of time and productivity worsen especially after minimal functionality changes
Solution Approach 1:
The patent implements a feedback mechanism where the AI engine continuously monitors blockchain records of script changes, analyzes impact patterns, and provides feedback to automatically determine which test scripts need updating. This feedback loop enables the system to learn from previous changes and progressively improve its ability to identify impacted modules, maintaining comprehensive regression testing coverage while significantly reducing the time required by eliminating unnecessary test executions
Solution Approach 2:
The system performs partial regression testing by selectively executing only the test scripts identified as necessary based on AI analysis of change impacts. Rather than running complete regression suites for all modules, the system performs targeted testing on specifically impacted areas, which maintains reliability by testing all necessary changes while reducing time loss by avoiding redundant testing of unaffected functionality
4Productivity
If AI automation is introduced for test script generation and impact analysis, then productivity and accuracy improve, but device complexity and difficulty of operation worsen
Solution Approach 1:
The AI engine operates autonomously by directly interfacing with the blockchain to retrieve change information, perform impact analysis, generate test scripts, and update the world state without requiring manual configuration or complex system integration. The self-service nature of the AI automation simplifies operation while maintaining high productivity, as users only need to interact with standard blockchain interfaces rather than complex AI systems
Data Source
AI summary
Aspects of this disclosure relate to a blockchain system for management of scripts associated with software applications. The blockchain system may be supplemented by an artificial intelligence (AI)-based system for generation of test scripts. The blockchain system may employ smart contracts for submission and validation of scripts by different nodes of a peer-to-peer (P2P) network.