AI-Assisted Test Automation Framework (Data Labeling AI Training)
Integrated LLM tools such as Claude Code and Cursor to automatically generate and validate complex test cases for software systems. Automated black-box and functional testing workflows were developed, leveraging AI to augment manual efforts and improve test diversity. The system produced high-quality test data used to benchmark and score internal software tools for robustness and performance.
• Utilized AI models to generate edge-case code scenarios for functional validation
• Improved test coverage and reduced manual workload for development teams
• Enabled continuous integration of AI-assisted test data in internal pipelines
• Focused on generating, labeling, and validating programming code for test coverage purposes
Integrated LLM tools such as Claude Code and Cursor to automatically generate and validate complex test cases for software systems. Automated black-box and functional testing workflows were developed, leveraging AI to augment manual efforts and improve test diversity. The system produced high-quality test data used to benchmark and score internal software tools for robustness and performance. • Utilized AI models to generate edge-case code scenarios for functional validation • Improved test coverage and reduced manual workload for development teams • Enabled continuous integration of AI-assisted test data in internal pipelines • Focused on generating, labeling, and validating programming code for test coverage purposes
2022 - Present