Sharukash N @sharukashn

TestFlow AI is a secure, controlled Python testing and validation assistant designed to make software testing safer, clearer, and easier to understand. The project focuses on executing a predefined synthetic calculator test project through a controlled pytest workflow rather than exposing arbitrary command execution or unrestricted project paths. The system validates the project boundary before execution, performs static inspection without executing inspected code, applies security checks such as path containment and symlink restrictions, controls the execution environment, enforces timeouts, and bounds captured output. Test execution results are then normalized into structured evidence and deterministically classified into meaningful validation states. A Streamlit interface provides a simple workflow for running the controlled validation, viewing the resulting evidence and classification, and receiving advisory next steps when the evidence indicates an actionable problem. Advisory guidance is intentionally separated from the test evidence and does not claim a confirmed root cause. The project is built with Python and pytest and includes automated regression and security-boundary tests covering the core execution, evidence, reporting, integration, and interface behavior. The demonstration uses synthetic calculator-project data and is designed to show how a testing assistant can combine safety controls, deterministic evidence handling, and understandable validation results.

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