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Yang Yang

PROFILE

Yang Yang

Worked on the linkedin/datahub-gma repository to enhance backend reliability and data modeling flexibility using Java and API development skills. Addressed asset retrieval by introducing pre-fetch existence checks, ensuring that requests for non-existent assets return accurate 404 responses and reducing misleading API outputs. This involved implementing robust error handling and comprehensive test coverage to validate the new behavior. Additionally, broadened relationship schema validation by removing a restrictive rule, allowing a wider range of primitive types in relationship fields. These changes improved downstream data integration and reduced schema friction, demonstrating a focus on backend robustness, data validation, and maintainable engineering practices.

Overall Statistics

Feature vs Bugs

50%Features

Repository Contributions

2Total
Bugs
1
Commits
2
Features
1
Lines of code
25
Activity Months2

Your Network

102 people

Shared Repositories

13

Work History

May 2025

1 Commits • 1 Features

May 1, 2025

May 2025: Delivered a targeted enhancement in linkedin/datahub-gma to broaden relationship schema validation, enabling a wider set of primitive types in relationship fields by removing a restrictive validation rule. This reduces schema friction for downstream consumers and accelerates data modeling workflows. The change is implemented via commit b03c43dd5615d112e27f45d78e3cd913799946c2 (remove relationship field type validation (#532)).

November 2024

1 Commits

Nov 1, 2024

November 2024 focused on improving asset retrieval reliability in linkedin/datahub-gma. Delivered robust 404 handling for non-existent assets by pre-checking asset existence before fetching aspects, and added tests to validate behavior. The change is captured in commit 6623691041147ebcb1c121fa6a4669d33d5a08de with message 'throw 404 exception when get non-existing asset (#480)'. This reduces misleading responses, decreases support overhead, and improves API correctness. Demonstrated backend robustness, test coverage, and strong attention to edge cases.

Activity

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Quality Metrics

Correctness80.0%
Maintainability90.0%
Architecture70.0%
Performance80.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

Java

Technical Skills

API DevelopmentBackend DevelopmentData ValidationError Handling

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

linkedin/datahub-gma

Nov 2024 May 2025
2 Months active

Languages Used

Java

Technical Skills

API DevelopmentBackend DevelopmentError HandlingData Validation