
Boris Vassilev developed core data structure and algorithmic components for the peshe/FMI-SDP-2024 repository, focusing on reusable C++ libraries for graphs, tries, hashmaps, and particle systems. He implemented abstract interfaces, memory-safe containers using smart pointers, and serialization patterns to enable persistence and robust state management. Boris enhanced reliability through custom allocators, leak detection, and comprehensive test harnesses, while also improving onboarding with detailed documentation. His work included command-line tooling, expression evaluators, and editor integration, leveraging C++, Rust, and the Language Server Protocol. The solutions demonstrated depth in algorithm design, memory management, and maintainable code organization for long-term project scalability.

March 2025 (2025-03) monthly summary for zed-industries/zed focusing on enhancing C++ editor completion accuracy and clangd compatibility. Delivered a targeted bug fix to ensure function parameters appear in completion items after clangd JSON changes, improving code correctness and developer productivity.
March 2025 (2025-03) monthly summary for zed-industries/zed focusing on enhancing C++ editor completion accuracy and clangd compatibility. Delivered a targeted bug fix to ensure function parameters appear in completion items after clangd JSON changes, improving code correctness and developer productivity.
January 2025 performance summary for peshe/FMI-SDP-2024: Key features delivered include a reusable Graph library with an abstract Graph interface, DFS/BFS, and a MatrixGraph implementation with an example main; Trie enhancements with memory management, destructor, and robust remove for prefix cases plus DOT visualization; and a custom hashmap with unique_ptr-based node management plus a dynamic command interpreter supporting commands with varying arguments. Addressed stability improvements and edge-case bugs in Trie deletion and memory handling. These deliverables establish foundational data-structure components, enabling faster feature work and improved debugging, with business value in reliability and reusability. Technologies demonstrated include C++, graph algorithms, memory management with smart pointers and destructors, DOT visualization, and dynamic command interpreter design.
January 2025 performance summary for peshe/FMI-SDP-2024: Key features delivered include a reusable Graph library with an abstract Graph interface, DFS/BFS, and a MatrixGraph implementation with an example main; Trie enhancements with memory management, destructor, and robust remove for prefix cases plus DOT visualization; and a custom hashmap with unique_ptr-based node management plus a dynamic command interpreter supporting commands with varying arguments. Addressed stability improvements and edge-case bugs in Trie deletion and memory handling. These deliverables establish foundational data-structure components, enabling faster feature work and improved debugging, with business value in reliability and reusability. Technologies demonstrated include C++, graph algorithms, memory management with smart pointers and destructors, DOT visualization, and dynamic command interpreter design.
Month: 2024-12. Focused on delivering high-value features, stabilizing core testing harnesses, and strengthening the data-structures library and tooling reliability. The work advances business value by improving test coverage, reliability, and performance, enabling faster iteration and safer refactoring.
Month: 2024-12. Focused on delivering high-value features, stabilizing core testing harnesses, and strengthening the data-structures library and tooling reliability. The work advances business value by improving test coverage, reliability, and performance, enabling faster iteration and safer refactoring.
Month: 2024-11 | Repository: peshe/FMI-SDP-2024 Overview: Delivered core capabilities across data structures, algorithms, and documentation to strengthen persistence, reliability, and reuse. The month focused on feature delivery for, and reliability improvements in, core components, plus documentation to boost onboarding and cross-team understanding. These efforts improve business value by enabling persistent particle systems, memory-safe linked lists, and a reusable algorithm library for expression evaluation. Key features delivered: - ParticleSystem API enhancements and serialization: added serialization/deserialization support for ParticleSystem; introduced a Point struct for 3D coordinates; Serializable interface; API improvements including size, capacity accessors, bounds-checked access, and a robust iterator. - LinkedList reliability: memory allocator and bug fixes: introduced a custom memory allocator for linked list nodes with leak detection; added a LinkedList class that uses the allocator; fixed append tail pointer and filter last-element processing to ensure correct memory cleanup. - Algorithm library refactor and data structures: refactored Shunting-yard implementation into a header for reuse; added an arithmetic expression tree with exponentiation optimizations; basic tool hierarchy for demonstrating composition. - Documentation updates for weeks 6-8: updates to Week 6 README with linked list problems; typo fixes in FMI-SDP-2024 README; Week 8 README covering tree data structures and AST creation for infix expressions. Major bugs fixed: - Fixed append tail pointer bug and filter last-element processing in LinkedList, preventing memory leaks and incorrect cleanup. - Introduced and refined a memory allocator (leak detection) to catch regressions early. - Resolved minor serialization/documentation inconsistencies across weeks 5-8. Overall impact and accomplishments: - Increased reliability and reusability of core data structures and APIs, enabling persistent particle systems and robust chain data structures. - Established a reusable algorithm library and header-first design, reducing duplication and enabling faster feature deployment. - Improved developer onboarding and cross-team collaboration through refreshed documentation and clear examples. Technologies/skills demonstrated: - C++ data structures and memory management (custom allocators, LinkedList). - Serialization/deserialization patterns and interface design (Serializable, Point type). - Algorithm design and refactoring (Shunting-yard, expression trees, exponentiation pruning). - Header-only library organization and documentation hygiene.
Month: 2024-11 | Repository: peshe/FMI-SDP-2024 Overview: Delivered core capabilities across data structures, algorithms, and documentation to strengthen persistence, reliability, and reuse. The month focused on feature delivery for, and reliability improvements in, core components, plus documentation to boost onboarding and cross-team understanding. These efforts improve business value by enabling persistent particle systems, memory-safe linked lists, and a reusable algorithm library for expression evaluation. Key features delivered: - ParticleSystem API enhancements and serialization: added serialization/deserialization support for ParticleSystem; introduced a Point struct for 3D coordinates; Serializable interface; API improvements including size, capacity accessors, bounds-checked access, and a robust iterator. - LinkedList reliability: memory allocator and bug fixes: introduced a custom memory allocator for linked list nodes with leak detection; added a LinkedList class that uses the allocator; fixed append tail pointer and filter last-element processing to ensure correct memory cleanup. - Algorithm library refactor and data structures: refactored Shunting-yard implementation into a header for reuse; added an arithmetic expression tree with exponentiation optimizations; basic tool hierarchy for demonstrating composition. - Documentation updates for weeks 6-8: updates to Week 6 README with linked list problems; typo fixes in FMI-SDP-2024 README; Week 8 README covering tree data structures and AST creation for infix expressions. Major bugs fixed: - Fixed append tail pointer bug and filter last-element processing in LinkedList, preventing memory leaks and incorrect cleanup. - Introduced and refined a memory allocator (leak detection) to catch regressions early. - Resolved minor serialization/documentation inconsistencies across weeks 5-8. Overall impact and accomplishments: - Increased reliability and reusability of core data structures and APIs, enabling persistent particle systems and robust chain data structures. - Established a reusable algorithm library and header-first design, reducing duplication and enabling faster feature deployment. - Improved developer onboarding and cross-team collaboration through refreshed documentation and clear examples. Technologies/skills demonstrated: - C++ data structures and memory management (custom allocators, LinkedList). - Serialization/deserialization patterns and interface design (Serializable, Point type). - Algorithm design and refactoring (Shunting-yard, expression trees, exponentiation pruning). - Header-only library organization and documentation hygiene.
October 2024 performance summary for peshe/FMI-SDP-2024 with a focus on Week 5 data-structure tasks and particle system development. Implemented and documented queues using stacks, stacks using queues, and a particle system with core operations and optional serialization capabilities. Explored serializable variants for Point and ParticleSystem to enable persistence and state capture.
October 2024 performance summary for peshe/FMI-SDP-2024 with a focus on Week 5 data-structure tasks and particle system development. Implemented and documented queues using stacks, stacks using queues, and a particle system with core operations and optional serialization capabilities. Explored serializable variants for Point and ParticleSystem to enable persistence and state capture.
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