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Wang Jiahua

PROFILE

Wang Jiahua

Worked on the source-academy/frontend repository to enhance the CSE Machine’s user interface and performance, focusing on interactive arrow highlighting, improved selection logic, and persistent visual states. Leveraged React, Konva, and TypeScript to refactor arrow state management, introduce color-coding for better visibility, and implement origin-based arrow filtering with dedicated UI controls. Addressed performance by removing redundant draw calls, reducing render cycles, and updating test automation and linting for code quality. Enhanced function value tooltips and layout for clearer presentation, while collaborating on co-authored commits. The work resulted in a faster, more maintainable, and accessible front end for algorithm visualization.

Overall Statistics

Feature vs Bugs

67%Features

Repository Contributions

5Total
Bugs
1
Commits
5
Features
2
Lines of code
1,547
Activity Months2

Work History

April 2026

4 Commits • 1 Features

Apr 1, 2026

April 2026 monthly summary focusing on business value and technical achievements for source-academy/frontend. Key features delivered include the CSE Machine UI/UX enhancements with improved arrow rendering, filtering, and tooltips; a performance optimization removing a redundant draw call in CseMachine; and related tests and code quality improvements. Major bugs fixed include reduced render cycles and more reliable UI behavior. Overall impact: faster UI, clearer function value presentation, and more maintainable codebase; technologies demonstrated include React, Konva, UI/UX design, performance profiling, linting, and test automation.

February 2026

1 Commits • 1 Features

Feb 1, 2026

February 2026 monthly summary for source-academy/frontend: Implemented interactive arrow highlighting and improved selection in the CSE Machine, with a refactor to arrow state management, enabling highlighted arrows to persist and improving performance. Introduced color-coding for visibility and completed code quality improvements (linting, test snapshots). This work enhances visualization UX for algorithm education and reduces maintenance overhead by simplifying selection logic.

Activity

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Quality Metrics

Correctness84.0%
Maintainability84.0%
Architecture84.0%
Performance84.0%
AI Usage44.0%

Skills & Technologies

Programming Languages

JavaScriptTypeScript

Technical Skills

KonvaReactReduxTypeScriptfront end development

Repositories Contributed To

1 repo

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

source-academy/frontend

Feb 2026 Apr 2026
2 Months active

Languages Used

JavaScriptTypeScript

Technical Skills

ReactTypeScriptfront end developmentKonvaRedux