Commit 4584c3

2025-10-09 10:11:05 Switi Patel: updated description
Projects/OptiQA.md ..
@@ 17,11 17,49 @@
QA engineers spend too much time on repetitive tasks (regression, log reviews, bug reporting).
Companies face higher costs and risks due to human error and inefficient QA cycles.
+ **Our AI Solution **
+ OptiQA is an AI-powered Quality Assurance automation platform designed to simplify and accelerate the testing process for web applications.
+ Its purpose is to:
+ -Reduce manual testing effort.
+ -Automatically generate, execute, and validate test cases using AI.
+ -Enable QA engineers and developers to test faster, smarter, and more efficiently.
+ -Provide detailed, real-time test results and maintain prompt/test history for traceability.
+
+
+ **Key Capabilities **
+ - AI-driven Test Generation: Users can input natural language prompts; AI converts them into executable test cases.
+ - Automated Execution: Playwright executes the generated test scripts automatically.
+ - Result Visualization: Users can view detailed results for each test run — including pass/fail status, screenshots, and logs.
+ - Prompt History Management: All user prompts and corresponding results are stored and retrievable.
+ - User Authentication: Secure login/signup using JWT-based authentication.
+
+ **Technology Stack **
+
+ Frontend
+ React.js, Tailwind CSS
+
+ Backend
+ Node.js, Express.js
+
+ Database
+ PostgreSQL
+
+ AI/ML
+ OpenAI GPT-4o-mini
+ Test Execution
+ Playwright
+
+ Authentication
+ JWT (JSON Web Tokens)
+
+ Hosting (optional)
+ AWS / Render / Vercel
+
+
**HLD - High Level Design Diagram**
![](./image-1760004148086.png)
- **Our AI Solution **
- OptiQA automates software quality assurance by: Generating test cases from user stories and requirements. Running automated regression tests. Parsing execution logs, screenshots, and crash reports. Producing intelligent QA reports with results, failures, and insights.
+
**Technology Stack**
AI/ML Models: AI Core (Python Services) NLP models (spaCy/Transformers) for test case generation from requirements. Log parsing and anomaly detection via ML classifiers. Rule-based system for mapping failures to probable causes.
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9