powsybl/powsybl-core
Jun 2025 – Jun 2025
1 Month active
Languages Used
Java
Technical Skills
Backend DevelopmentData ParsingError HandlingJavaTime Series Data HandlingUnit Testing
Arthur Chan
PROFILE
Arthur Chan
Worked on enhancing reliability and data integrity in the powsybl-core repository, focusing on backend improvements for data import and time-series processing. Addressed two critical bugs by implementing null-safe deserialization and guarded CSV parsing to prevent runtime errors during PSS/E imports. Introduced a MAX_DAYS limit and added range and spacing validations to mitigate time-series overflow issues, ensuring robust handling of large datasets. Employed Java for defensive coding and comprehensive unit testing, verifying new error handling scenarios. These updates improved the stability of data imports and downstream analyses, demonstrating strong skills in backend development, error handling, and time-series data management.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
0
Lines of code
77
Activity Months1
Your Network
38 peopleWork History
June 2025
3 Commits
Jun 1, 2025June 2025 monthly summary for powsybl-core focusing on reliability and data integrity improvements in data import and time-series processing. Implemented null-safe deserialization and guarded CSV parsing to prevent runtime errors in PSS/E import. Introduced a MAX_DAYS limit and range/spacing validations for time-series to prevent overflow, with accompanying unit tests. These changes reduce runtime errors, improve data quality for imports, and enhance overall stability for downstream analyses. Demonstrated Java defensive coding, unit testing discipline, and CSV/time-series processing skills.
3 Commits
Jun 1, 2025June 2025 monthly summary for powsybl-core focusing on reliability and data integrity improvements in data import and time-series processing. Implemented null-safe deserialization and guarded CSV parsing to prevent runtime errors in PSS/E import. Introduced a MAX_DAYS limit and range/spacing validations for time-series to prevent overflow, with accompanying unit tests. These changes reduce runtime errors, improve data quality for imports, and enhance overall stability for downstream analyses. Demonstrated Java defensive coding, unit testing discipline, and CSV/time-series processing skills.
June 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability80.0%
Architecture73.4%
Performance66.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Backend DevelopmentData ParsingError HandlingJavaTime Series Data HandlingUnit Testing
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