
Nikolay Gostev developed core data structure modules and educational resources for the peshe/FMI-SDP-2024 repository, focusing on practical C++ implementations of AVL trees, binary heaps, linked lists, and graph algorithms. He designed reusable components such as a generic linked list, custom queue, and LRU cache, emphasizing maintainability through header-based organization and thorough documentation in Markdown. His work included solutions for tasks like Hamming number generation, tree traversals, and stream medians, supporting both correctness and teaching value. By refactoring code and fixing critical bugs, Nikolay enabled faster onboarding and experimentation, demonstrating depth in algorithm design and computer science education.

January 2025 (2025-01) monthly summary for peshe/FMI-SDP-2024. Delivered two core features and enhanced coursework modules that strengthen practical data-structure capabilities and teaching resources. Key contributions include a robust C++ Binary Heap with insert, delete, key updates, heap-merge, and utilities for kth-smallest element and medians in a stream, plus Week 12 documentation and solutions. In addition, the Data Structures Coursework module delivered implementations for Dictionary, Set, and LRUCache, covering hash tables, dictionaries, sets, histograms, intersections, and LRU caches, with refactoring of linked lists and Week 13 tasks and solutions. The work is accompanied by thorough documentation to support learning and reuse, and commits reflect iterative development and code quality improvements.
January 2025 (2025-01) monthly summary for peshe/FMI-SDP-2024. Delivered two core features and enhanced coursework modules that strengthen practical data-structure capabilities and teaching resources. Key contributions include a robust C++ Binary Heap with insert, delete, key updates, heap-merge, and utilities for kth-smallest element and medians in a stream, plus Week 12 documentation and solutions. In addition, the Data Structures Coursework module delivered implementations for Dictionary, Set, and LRUCache, covering hash tables, dictionaries, sets, histograms, intersections, and LRU caches, with refactoring of linked lists and Week 13 tasks and solutions. The work is accompanied by thorough documentation to support learning and reuse, and commits reflect iterative development and code quality improvements.
December 2024 focused on delivering core data-structure implementations and student-facing educational materials in the FMI-SDP-2024 project, with emphasis on correctness, reusability, and practical applicability to real-world workloads. Key contributions include robust AVL and BST-related components, a generic C++ linked list, and a graph data-structure suite, complemented by Week 09–11 tasks and solutions that reinforce balanced trees and graph algorithms. A critical bug fix corrected the Eulerian graph example in the README to reflect the correct is_eulerian outcome and expanded the graph demonstration to illustrate valid Eulerian graphs.
December 2024 focused on delivering core data-structure implementations and student-facing educational materials in the FMI-SDP-2024 project, with emphasis on correctness, reusability, and practical applicability to real-world workloads. Key contributions include robust AVL and BST-related components, a generic C++ linked list, and a graph data-structure suite, complemented by Week 09–11 tasks and solutions that reinforce balanced trees and graph algorithms. A critical bug fix corrected the Eulerian graph example in the README to reflect the correct is_eulerian outcome and expanded the graph demonstration to illustrate valid Eulerian graphs.
Monthly summary for 2024-11 covering peshe/FMI-SDP-2024. Key features delivered include a Hamming Number Generator implemented with a queue and refactored queue code into headers to improve maintainability; completion of a complete solution (commit c145ca5ef9910e952463f9c0a6a34a280d47531d). Week 05 LinkedList Data Structure: tasks outlined and API implemented with educational content and operations (commits c0cae8ce6db9b01c59bbcf5d6acdb6a2a48a13d0 and edc00db0fdbd0c4d4f49056280663e687dd62cfc). Tree data structures and BSTs: implementation and traversal (Tree, BinaryTree, BinarySearchTree) with DFS/BFS, search, and depth-level retrieval; iterator refactor into header (commits including 1df0ccf47462dc76c04481e12b516a85ab3074cb, d7d65609aebd0337253c0a380d9cd6ef615ab74b, d778ade90bb1a8bc9b8ed864e4047b70ba920114, 52a173c9bf13e997b41769005cdcf46c11e34bd0, 40eac9d6b79bf8fabe1e0c35d3a213a7cbe82787, c45d0b952ca6a9aa2ac9f849d518f9b67c6659b9, a142bb349874e2a7c1050dbd745b8b7c3ee494a8, 899bebf12fadf87a341061b6ae575b0cf16d4c7e). Advanced data structures implementations (circular/doubly/skip lists) and Josephus: commit a4dcddb4388230d77fea6462c9c612f500eb3c2d (Add solutions for week 06). No explicit bugs reported; focus on feature delivery and code quality improvements. Overall impact includes accelerated learning path for data structures, reusable components, and improved code organization supporting future work. Technologies demonstrated include queue-based algorithms, header-based code organization, iterator patterns, and traversal/graph concepts.
Monthly summary for 2024-11 covering peshe/FMI-SDP-2024. Key features delivered include a Hamming Number Generator implemented with a queue and refactored queue code into headers to improve maintainability; completion of a complete solution (commit c145ca5ef9910e952463f9c0a6a34a280d47531d). Week 05 LinkedList Data Structure: tasks outlined and API implemented with educational content and operations (commits c0cae8ce6db9b01c59bbcf5d6acdb6a2a48a13d0 and edc00db0fdbd0c4d4f49056280663e687dd62cfc). Tree data structures and BSTs: implementation and traversal (Tree, BinaryTree, BinarySearchTree) with DFS/BFS, search, and depth-level retrieval; iterator refactor into header (commits including 1df0ccf47462dc76c04481e12b516a85ab3074cb, d7d65609aebd0337253c0a380d9cd6ef615ab74b, d778ade90bb1a8bc9b8ed864e4047b70ba920114, 52a173c9bf13e997b41769005cdcf46c11e34bd0, 40eac9d6b79bf8fabe1e0c35d3a213a7cbe82787, c45d0b952ca6a9aa2ac9f849d518f9b67c6659b9, a142bb349874e2a7c1050dbd745b8b7c3ee494a8, 899bebf12fadf87a341061b6ae575b0cf16d4c7e). Advanced data structures implementations (circular/doubly/skip lists) and Josephus: commit a4dcddb4388230d77fea6462c9c612f500eb3c2d (Add solutions for week 06). No explicit bugs reported; focus on feature delivery and code quality improvements. Overall impact includes accelerated learning path for data structures, reusable components, and improved code organization supporting future work. Technologies demonstrated include queue-based algorithms, header-based code organization, iterator patterns, and traversal/graph concepts.
October 2024 monthly summary focusing on delivering Week 04 queue task documentation and solutions for peshe/FMI-SDP-2024, establishing a reusable knowledge artifact and practical implementations. Key outcomes include a markdown doc detailing Week 04 queue concepts, static-array and linked-list queue implementations, performance comparisons, and concrete solutions (generating binary numbers, Hamming numbers, maze shortest path, queue via two stacks, and first negative in a fixed-size subarray/window) powered by a custom LinkedQueue. Code commits captured: 0b68cc199d751d0543c5eacd7c0366b4b2d82349 (Add tasks for week 04) and 2dd6710a0eb1695631312815f84b32d35a05dbcd (Add solutions for week 04).
October 2024 monthly summary focusing on delivering Week 04 queue task documentation and solutions for peshe/FMI-SDP-2024, establishing a reusable knowledge artifact and practical implementations. Key outcomes include a markdown doc detailing Week 04 queue concepts, static-array and linked-list queue implementations, performance comparisons, and concrete solutions (generating binary numbers, Hamming numbers, maze shortest path, queue via two stacks, and first negative in a fixed-size subarray/window) powered by a custom LinkedQueue. Code commits captured: 0b68cc199d751d0543c5eacd7c0366b4b2d82349 (Add tasks for week 04) and 2dd6710a0eb1695631312815f84b32d35a05dbcd (Add solutions for week 04).
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