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https://github.com/yjbae-sqa/quality-engineering-portfolio

Quality Engineer with experience in web, mobile, and AI platforms, specializing in test automation and system validation.
https://github.com/yjbae-sqa/quality-engineering-portfolio

2026 quality-engineering

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Quality Engineer with experience in web, mobile, and AI platforms, specializing in test automation and system validation.

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README

          

# Quality Engineering Portfolio

Quality Engineer with experience in **AI platforms, distributed systems, and automation-driven quality validation**.

This repository demonstrates how product quality issues can be analyzed, validated, and managed through engineering-driven QA practices.

The focus is on **Quality Engineering**, including:

* system validation
* test automation
* CI/CD pipeline verification
* quality metrics and release validation

Sensitive implementation details and internal architectures are intentionally omitted.

---

# Repository Overview

This repository is organized into four main areas.

| Area | Purpose |
| ------------------- | ---------------------------------------- |
| Case Studies | real-world quality validation examples |
| Automation | test automation approaches and tools |
| Domains | product domains and system types |
| Quality Engineering | testing strategies and quality practices |

---

# Validation Approach

The validation approach used across projects typically follows this workflow:

```mermaid
flowchart TD
A[System Change]
B[Risk Identification]
C[Test Strategy Definition]
D[Test Execution & Validation
#40;Automation / Smoke / API#41;]
E[CI/CD Test Execution
#40;Docker / Pipeline#41;]
F[Quality Metrics Review
#40;Coverage / Failure Rate#41;]
G[Release Decision]

A --> B --> C --> D --> E --> F --> G
```

This approach helps ensure that testing activities focus on **high-risk areas and critical system behaviors**.

---

# Case Studies

Simplified case studies based on real-world quality engineering work.

| Case Study | Description |
| ------------------------------------ | -------------------------------------------------- |
| AI/MLOps Model Deployment Validation | validating model deployment and inference services |
| API Regression Testing Strategy | designing regression testing for high-risk APIs |
| Test Automation Framework Design | building maintainable UI/API automation frameworks |
| CI/CD Pipeline Validation | validating container-based deployment pipelines |

Each case study explains:

* problem context
* validation scope
* engineering approach
* key testing scenarios

📌 **Start here if you want to understand how quality problems were analyzed and validated.**

---

# Test Automation

Automation practices used to validate system behavior and support regression testing.

### Web UI Automation

* Selenium
* Playwright
* cross-browser testing
* user workflow validation

### Mobile Automation

* Appium
* Android UI testing
* mobile UI regression testing
* device-based validation

### API Automation

* Postman / Newman
* API regression testing
* service integration validation

### CI/CD Testing

* pipeline validation
* automated test execution
* container-based test environments

### Performance Testing

* Newman-based lightweight performance validation
* JMeter basic load testing

---

# Engineering Domains

Experience across multiple product and technology domains.

### AI / MLOps Platforms

* AI inference API validation
* data pipeline verification
* containerized model deployment validation
* Kubernetes-based model serving verification

### Computer Vision & 3D Applications

* image processing pipeline validation
* 3D rendering validation
* sensor and device interaction testing
* performance validation for real-time graphics
* Unity-based AR/VR application environments

### Video Streaming Platforms

* streaming pipeline validation
* playback stability testing
* encoding / decoding verification
* network condition testing

### E-Commerce Platforms

* checkout workflow validation
* payment API testing
* regression testing for release cycles

---

# Quality Engineering

Quality engineering practices used to reduce release risk and maintain product reliability.

### Test Strategy

* risk-based testing
* regression test planning
* release validation strategy

### Release Quality Gate

* validation coverage review
* automated test result analysis
* critical workflow verification

### Quality Metrics

* validation coverage metrics
* automated test pass rate
* regression execution status
* release readiness indicators

### Test Design Techniques

* boundary value analysis
* equivalence partitioning
* state transition testing

---

# Repository Structure

```
qa-engineering-portfolio
│
├─ README.md
│
├─ case-studies
│ ├─ ai-mlops-model-deployment-validation
│ ├─ api-regression-testing-strategy
│ ├─ test-automation-framework-design
│ └─ ci-cd-pipeline-validation
│
├─ automation
│ ├─ ui-test-automation
│ ├─ mobile-test-automation
│ ├─ api-test-automation
│ ├─ ci-cd-testing
│ ├─ performance-testing
│ └─ test-frameworks
│
├─ domains
│ ├─ ai-mlops
│ ├─ computer-vision-3d
│ ├─ video-streaming
│ └─ ecommerce
│
└─ quality-engineering
├─ test-strategy
├─ risk-based-testing
├─ regression-testing
├─ release-quality-gate
├─ quality-metrics
└─ test-design-techniques
```

---

# Notes

This repository focuses on **engineering approaches to quality validation** rather than specific internal implementations.

Examples are simplified to highlight testing strategies, validation flows, and quality engineering practices.