Revolutionizing Test Automation: Gemini LLM + BDD (Cucumber) Dynamic Locator Framework An AI-powered test automation framework that solves locator fragility by combining Google’s Gemini LLM with BDD (Cucumber). Ideal for React/Angular apps, it dynamically adapts XPath/CSS selectors, reducing maintenance and improving test stability.

QA-Auto is an automated QA testing framework powered by LLMs and browser automation. It reads BDD-style feature files, executes all scenarios, and generates Cucumber-style HTML reports.

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BDD Test Automation-LLM-AI-Self-Auto-healing

Mega Prompts for QA Strategy: Project demonstrating a 50-70% time reduction in Test Strategy and Test Case creation by applying 15 years of expertise to guide LLMs. Focuses on RBT, NFRs, and BDD structure.

An intelligent, context-aware test automation framework that auto-generates and executes deterministic Playwright (TypeScript) tests from BDD Gherkin features using LLMs and dynamic DOM scraping.

A stochastic BDD framework for Python designed to test non-deterministic systems (e.g., LLMs) by evaluating statistical distributions rather than binary outcomes

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AI-powered testing tool that converts plain English requirements into automated Playwright tests via Gherkin. Built with Ollama (Deepseek-v3.1), handles SauceDemo login flows, generates JSON reports. 10x faster test creation for ML engineers.

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LLM-driven BDD testing framework with automated scenario generation and validation

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LLM-assisted BDD functional testing using pytest-bdd and Playwright

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LLM Assisted BDD Functional Testing Framework using Groq, Behave and Playwright

An LLM-assisted BDD testing framework that converts business requirements into validated Gherkin scenarios, requires manual approval, and automatically executes happy-path tests using Behave.

LLM‑Assisted BDD Functional Testing for a Sample Web Application

LLM-assisted BDD functional testing with manual approval and dashboard visualization

Policy-driven, risk-aware LLM-assisted BDD functional testing framework with human-in-the-loop governance

Generate BDD-style Gherkin scenarios using a local LLM and run them as real functional tests with Behave and Playwright.

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This project demonstrates how to use a Large Language Model (LLM) to generate BDD-style test scenarios, validate them, select the “happy path” scenario, and automatically execute it using Behave + Playwright automation. It also includes a sample web application (Flask) with a modern UI for login and dashboard pages.

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LLM-powered BDD test generation and execution pipeline with local model inference and human-in-the-loop approval.

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LLM-Assisted BDD Functional Testing Prototype