https://github.com/alisson-t-bucchi/alisson-t-bucchi
GitHub profile configuration repo.
https://github.com/alisson-t-bucchi/alisson-t-bucchi
github profile-readme
Last synced: about 1 month ago
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GitHub profile configuration repo.
- Host: GitHub
- URL: https://github.com/alisson-t-bucchi/alisson-t-bucchi
- Owner: alisson-t-bucchi
- Created: 2024-03-10T20:38:29.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-05-16T22:30:33.000Z (about 1 month ago)
- Last Synced: 2026-05-17T00:32:55.680Z (about 1 month ago)
- Topics: github, profile-readme
- Homepage: https://github.com/alisson-t-bucchi
- Size: 261 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README

## π§ About Me

> π‘ *βThe only way to do great work is to love what you do.β* β Steve Jobs
---
## π₯ Featured Projects
### π§ͺ QA Automation Framework (AmbevTech Challenge)
- π§ Stack: Cypress + JavaScript + Cucumber (BDD)
- π§© Architecture: Page Object Model (POM)
- π UI and API testing (REST)
- π§ͺ E2E scenarios covering login, registration and product flows
- π Emphasis on test structure, reusability and documentation
- π [View Repository](https://github.com/alisson-t-bucchi/qa-skill-test-ambevtech)
---
### π€ Cost of Living AI/ML Predictor
- π§ Built with Python, Pandas and Scikit-learn
- π Predicts cost of living using real-world datasets
- π Includes data preprocessing and model training pipeline
- π Focus on regression models and data analysis
- π [View Repository](https://github.com/alisson-t-bucchi/cost-of-living-ai-ml)
---
### π Hotel Booking Frontend (React)
- βοΈ Built with React (component-based architecture)
- π§© Simulates a hotel booking interface
- π Focus on UI structure and user experience
- π§ͺ Suitable for E2E testing with Cypress or Selenium
- π [View Repository](https://github.com/alisson-t-bucchi/hotel-booking-react-js)
---
## π QA Metrics & Impact
- β
50+ automated test cases implemented
- π Reduced manual regression effort
- β‘ Improved test execution workflow
- π Early bug detection through automation
- π Consistent test structure and coverage practices
---
## π€ AI + QA (In Progress)
- π§ Studying Machine Learning applications in QA
- π Working with datasets for test analysis
- π Exploring anomaly detection in test results
- π― Goal:
β Transform QA into a **data-driven engineering discipline**
---
## π GitHub Stats
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## π» Programming Languages
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## π οΈ Tools & Frameworks
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## π Connect with Me