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
Miroslav Mihaylov developed a suite of educational and practical programming resources in the peshe/FMI-SDP-2024 repository, focusing on data structures, algorithms, and graph theory. Over three months, he delivered features such as Trie and BST implementations, Tic-Tac-Toe AI, and graph processing tools, all written in C++ with supporting Markdown documentation. His work emphasized algorithmic thinking and code quality, providing hands-on labs and seminar materials that addressed both theoretical and applied computer science concepts. By integrating file I/O, dynamic programming, and technical documentation, Miroslav ensured the materials were robust, maintainable, and directly aligned with student learning objectives.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
26Total
Bugs
0
Commits
26
Features
13
Lines of code
8,974
Activity Months3
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
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