Data-structures-and-algorithms-2025/DSA_courses_for_teamwork
Mar 2025 – Mar 2025
1 Month active
Languages Used
CCMake
Technical Skills
Algorithm DevelopmentAlgorithm OptimizationArray ManipulationBuild SystemsC ProgrammingData Structures
MezofiTihamer
PROFILE
Mezofitihamer
During March 2025, Mihály Tihamér Szabó enhanced the Data-structures-and-algorithms-2025/DSA_courses_for_teamwork repository by developing core data handling features and refining build processes. He implemented and later streamlined utilities for array printing and primality testing in C, focusing on maintainability and reducing unnecessary surface area. His work included robust input parsing for product details, addressing edge cases such as spaces in string fields, and clarifying API design by renaming fields for better readability. Leveraging skills in C, CMake, and algorithm optimization, Mihály delivered features that improved validation speed, reliability, and team-wide code reuse while maintaining a clean codebase.
Overall Statistics
Feature vs Bugs
63%Features
Repository Contributions
11Total
Bugs
3
Commits
11
Features
5
Lines of code
124
Activity Months1
Your Network
13 people
Work History
March 2025
11 Commits • 5 Features
Mar 1, 2025March 2025 performance summary for Data-structures-and-algorithms-2025/DSA_courses_for_teamwork. Focused on delivering core data handling capabilities, debugging support, and build/maintenance improvements. Delivered features that enable richer product data workflows, robust input parsing, and clearer field naming, while also improving the build configuration. Several items were refined or deprecated to reduce surface area and maintenance burden. Business value includes faster validation, more reliable product data handling, and cleaner APIs for team-wide reuse.
11 Commits • 5 Features
Mar 1, 2025March 2025 performance summary for Data-structures-and-algorithms-2025/DSA_courses_for_teamwork. Focused on delivering core data handling capabilities, debugging support, and build/maintenance improvements. Delivered features that enable richer product data workflows, robust input parsing, and clearer field naming, while also improving the build configuration. Several items were refined or deprecated to reduce surface area and maintenance burden. Business value includes faster validation, more reliable product data handling, and cleaner APIs for team-wide reuse.
March 2025
Activity
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Quality Metrics
Correctness85.4%
Maintainability87.2%
Architecture74.6%
Performance91.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CCMake
Technical Skills
Algorithm DevelopmentAlgorithm OptimizationArray ManipulationBuild SystemsC ProgrammingData StructuresPrimality TestUtility Functions
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