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#046: Continuous Intelligent Validation (cIV)
Agentic Validation is here!
Nagesh Nama
February 19, 2025 • Estimated Reading Time: 6 minutes
Table of Contents
1.0. What is cIV?
cIV (Continuous Intelligent Validation) represents a groundbreaking advancement in software validation, utilizing Large Language Models (LLMs) and intelligent agents to achieve complete validation automation.
In contrast to conventional techniques reliant on substantial manual effort and pre-programmed code, cIV offers autonomous capabilities to:
Decipher and analyze requirements from diverse inputs such as user guides and existing test suites
Create test scenarios using natural language
Perform tests dynamically, adjusting to real-time modifications
Generate thorough, GxP-compliant documentation.
2.0. Why cIV?
The moment for cIV has arrived. Recent breakthroughs in LLM technology empower us to unlock its transformative capabilities for software testing and validation. cIV delivers remarkable advantages, including:
Improved Efficiency: cIV achieves at least a tenfold increase in speed and efficiency compared to conventional approaches.
Superior Accuracy: By utilizing AI and machine learning, cIV reduces human error and guarantees more dependable validation outcomes.
Exceptional Adaptability: cIV readily adjusts to evolving requirements and application behaviors, making it perfectly suited for today's rapidly changing software development landscapes.
3.0. How Does cIV Work?
cIV leverages an intelligent agent that draws upon a rich knowledge base, compiled from sources like user manuals, manual test cases, and knowledge graphs. This agent is specifically trained to comprehend and execute workflows in a step-by-step manner.
The cIV process encompasses:
Agent Training: The agent is initially trained on the target workflow. A recording tool developed by xLM tracks user actions, converting them into easily understandable natural language commands.
Autonomous Execution: The agent then uses natural language input to independently execute the test case, eliminating the need for pre-written code. It interacts with websites, identifies elements through computer vision and LLMs, and performs necessary actions.
Detailed Reporting: cIV generates a GxP-compliant PDF report, providing a thorough audit trail of the entire validation procedure.
4.0. cIV Architecture
The cIV system's structure comprises a training recorder, a contextual knowledge base, and an intelligent execution agent. This agent interprets instructions, utilizes the knowledge base, carries out tests, and produces a GxP-compliant execution protocol.
4.1. Beyond Test Execution: URS and Test Case Generation
cIV's capabilities extend beyond simple test execution, automating vital tasks such as User Requirements Specification (URS) and test case creation.
URS Generation: By defining the URS scope for the bot, cIV can automatically produce a draft document in Word format, ready for editing and refinement.
Test Case Generation: Leveraging its software understanding, the agent can automatically generate test cases using the xLM recorder, offering a strong foundation for the validation process.
5.0. Conclusion: The Future of Validation is Here
cIV signifies a revolutionary change in software validation, leveraging AI and smart automation to deliver unparalleled efficiency, precision, and flexibility. cIV can assist organizations aiming to optimize and improve their validation procedures, guarantee superior software results, and uphold rigorous compliance with changing regulatory standards. By leveraging automation and intelligent technologies, cIV offers a proactive approach to identifying and mitigating potential risks, optimizing resource allocation, and ultimately strengthening an organization's overall security posture and compliance
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