peshe/FMI-SDP-2024
Nov 2024 – Jan 2025
3 Months active
Languages Used
C++MarkdownStringText
Technical Skills
Algorithm AnalysisAlgorithm ImplementationAlgorithmic ThinkingAlgorithmsC++C++ Development
Miro7543
PROFILE
Miro7543
Over a three-month period, this developer contributed to the peshe/FMI-SDP-2024 repository by designing and implementing a range of educational features focused on data structures, algorithms, and graph theory. They developed practical exercises and seminar materials covering topics such as binary trees, heaps, and graph algorithms, using C++ and Markdown for both code and documentation. Their work included building AI-driven game tasks, implementing core structures like tries and matrices, and creating graph processing utilities. Emphasizing code quality and maintainability, they enhanced technical documentation and ensured curriculum alignment, supporting student learning and cross-team collaboration without introducing critical defects or regressions.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
26Total
Bugs
0
Commits
26
Features
13
Lines of code
8,974
Activity Months3
Your Network
9 peopleShared Repositories
9
Work History
January 2025
6 Commits • 6 Features
Jan 1, 2025January 2025 (2025-01) monthly summary for peshe/FMI-SDP-2024. Focused on delivering learning resources and practical graph theory content, with targeted materials for KN Group 1 and routine CS practice problems. No critical bugs reported; primary work centered on feature delivery, documentation, and code improvements that directly support education and capability building.
6 Commits • 6 Features
Jan 1, 2025January 2025 (2025-01) monthly summary for peshe/FMI-SDP-2024. Focused on delivering learning resources and practical graph theory content, with targeted materials for KN Group 1 and routine CS practice problems. No critical bugs reported; primary work centered on feature delivery, documentation, and code improvements that directly support education and capability building.
January 2025
December 2024
5 Commits • 5 Features
Dec 1, 2024Concise monthly performance summary for December 2024 (peshe/FMI-SDP-2024). Focused on delivering practical AI and data-structure content, expanding hands-on labs, and improving documentation to support student learning and course assessments.
December 2024
5 Commits • 5 Features
Dec 1, 2024Concise monthly performance summary for December 2024 (peshe/FMI-SDP-2024). Focused on delivering practical AI and data-structure content, expanding hands-on labs, and improving documentation to support student learning and course assessments.
November 2024
15 Commits • 2 Features
Nov 1, 2024Month: 2024-11 | peshe/FMI-SDP-2024. Key deliverables: 1) Educational materials and solutions for seminars and KN groups (Group A) across weeks 4–7, including Seminar 5, Seminar 8, Week 4/5 tasks, Week 6 practicals, and Week 7 Group A exercises; added explanations for Week 6 KN Group 1; Week 7 KN practicum materials. 2) Core data structure implementations and improvements (Trie, BST, matrix via doubly linked list) with code quality enhancements and related seminar contributions for weeks 7–9. Major bugs fixed: No critical defects reported; addressed minor refactors and clarifications in core data structures and seminar materials. Overall impact and accomplishments: Accelerated learning resources for KN groups, strengthened data-structure foundations, and improved maintainability; assets ready for upcoming sprints. Technologies/skills demonstrated: data structures (Trie, BST), algorithms, code quality improvements, documentation and explanations, commit discipline, and cross-team collaboration.
15 Commits • 2 Features
Nov 1, 2024Month: 2024-11 | peshe/FMI-SDP-2024. Key deliverables: 1) Educational materials and solutions for seminars and KN groups (Group A) across weeks 4–7, including Seminar 5, Seminar 8, Week 4/5 tasks, Week 6 practicals, and Week 7 Group A exercises; added explanations for Week 6 KN Group 1; Week 7 KN practicum materials. 2) Core data structure implementations and improvements (Trie, BST, matrix via doubly linked list) with code quality enhancements and related seminar contributions for weeks 7–9. Major bugs fixed: No critical defects reported; addressed minor refactors and clarifications in core data structures and seminar materials. Overall impact and accomplishments: Accelerated learning resources for KN groups, strengthened data-structure foundations, and improved maintainability; assets ready for upcoming sprints. Technologies/skills demonstrated: data structures (Trie, BST), algorithms, code quality improvements, documentation and explanations, commit discipline, and cross-team collaboration.
November 2024
Activity
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Quality Metrics
Correctness91.2%
Maintainability89.6%
Architecture88.8%
Performance88.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++MarkdownStringText
Technical Skills
Algorithm AnalysisAlgorithm DesignAlgorithm ImplementationAlgorithmic ThinkingAlgorithmsBalanced Binary Search TreesBinary TreesC++C++ DevelopmentC++ ProgrammingComputer ScienceComputer Science EducationComputer Science FundamentalsConst CorrectnessData Structures
Repositories Contributed To
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