QA Engineer | Automation | Performance | AI/LLM Testing

Welcome! This repository showcases my hands-on work in Software Quality Assurance, including automation scripts, test cases, bug reports, test plans, and exploratory testing charters.

💡 Recruiters & Hiring Managers: Explore this repo to see real examples of my QA skills in action, including Cypress automation, Katalon frameworks, API & performance testing, and structured QA documentation.

🔗 Key highlights:

• End-to-end Automation Scripts (Cypress & Katalon)
• Test Plans, Charters & RTM for live projects
• Bug Reports & Test Cases

These are sample automation scripts I’ve created using Cypress, an end-to-end testing framework. The scripts cover various test scenarios for web applications, ensuring that the functionality and user flows work as expected. You can explore the code to understand my approach to automation testing, how I structure my test cases, and how I leverage Cypress for robust testing.

• Cypress Sample Test Cases – A repository containing my automation scripts created using Cypress for end-to-end testing.

This section includes a variety of test cases, reported bugs, and API testing bugs. It demonstrates my approach to documenting and tracking defects, as well as my attention to detail in testing across multiple layers of an application.

• Test Cases - Omni Channel – This Google Sheet includes 200+ test cases for various modules of the Omni Channel Project, covering functional, integration, and API testing.

• Khudi Chat (iOS) – Test Cases – This Google Sheet includes 400+ test cases for the Khudi Chat iOS app (similar to WhatsApp), covering messaging, media sharing, calls, notifications, authentication, security, UI/UX, performance, and API testing.

• Bugs Report - EPE – This Google Sheet includes bugs reporting for Engineering Practice Examination Portal.

• Test Cases, Bugs, and API Testing Bugs Spreadsheet – This Google Sheet includes a variety of test cases, reported bugs, and API testing bugs.

Test plans are crucial for outlining the testing scope, objectives, and deliverables. These documents highlight how I approach the planning phase of a QA project and provide a roadmap for testing activities. Here are two test plans I’ve worked on:

• Test Plan 1: AXI Customer Care Chatbot – A comprehensive test plan outlining the approach for testing an AI-based customer care chatbot, focusing on functionality, user interaction, and error handling.
• Test Plan 2: HR CV Screening Bot – A test plan for evaluating an AI-powered CV screening tool, including scenarios for accurate document parsing and classification.
• Test Plan 3: Safe City Project - This test plan defines the quality assurance strategy for the Safe City Project, a centralized surveillance and monitoring platform supporting public safety operations.Testing will focus on validating map-based monitoring, real-time alerts, live video streams, facial recognition outputs, analytics dashboards, and camera management using experience-based and exploratory testing aligned with real-world operational scenarios.

Test charters define the scope and focus of exploratory testing sessions. Below are a couple of test charters that I’ve used to guide testing activities in exploratory testing and regression testing:

• Test Charter 1: NTS Regression Scenarios – A charter designed for exploratory regression testing, ensuring that recent changes don’t negatively affect existing functionality.
• Test Charter 2: AXI Customer Care Chatbot – A test charter focused on exploratory testing of the AXI Customer Care Chatbot, evaluating its adaptability to various user inputs and its response accuracy.

These include comprehensive QA deliverables for robust quality assurance across software projects.

• 📋 Requirements Traceability Matrix (RTM) : OMNI Channel – This RTM professionally maps 16 derived requirements to 200+ test cases across Omni-Channel modules per ISTQB standards, achieving 98% coverage with execution status and defect tracking.

• 🤖 AI Chatbot Testing Report & LLM Evaluation Framework – This project presents a structured evaluation of an AI-powered chatbot using a metrics-driven approach. It includes test cases designed to assess accuracy, relevance, completeness, hallucination, safety, and context retention, along with a 1–5 scoring system to measure response quality and identify improvement areas.

• 🧪 Test Data Sets : HR CV Screening Bot – This includes key test data I prepared to execute different testing scenarios for the HR CV screening bot, covering multiple data sets designed to validate functionality, accuracy, edge cases, and real-world usage conditions.

Note: The files and links above represent a few examples of my work, showcasing my structure, process, and attention to detail in QA. I'll be continuously adding more artifacts, so stay tuned for updates!