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COOP
Mentored by: Mobileye
Macro-based OOP framework for C with classes, inheritance, virtual functions, iterators and extensive data-structure library.
C
MISRA
Cppcheck
Data Structures
Iterator Model
Memory Management
Image Processing
Description
Implements a full OOP system in C including classes, inheritance, iterators, pure_virtual macro, MISRA-based static analysis, and optimized data structures (List, Queue, Binary Tree). Includes performance benchmarks vs GObject, OOC and pure-C, image-processing add-ons, robust iterator model, ref-count mechanism, and configurable memory management.
Team Members
Cohort: Embedded Systems Bootcamp 2025 (Embedded)
Responsibilities:
āŖ Designed and implemented data structure (linked list) , fixing bugs and created unit tests
Performing comprehensive performance benchmarking tests in the WSL environment against the gObject library
Ensured high code quality and safety compliance following MISRA-C standards
Developed the GrayImage class, featuring a reference counting mechanism and Image View/ROI support for highly efficient memory management.
Implemented a full suite of image operators for pixel-wise arithmetic (add, subabs) and advanced linear algebra operations like matrix multiplication (mulmat).
Designed a polymorphic ImageProcessor pipeline in C-OOP to chain specialized modules (GaussianProcessor, SobelProcessor), implementing the complete Canny Edge Detection algorithm.
...and more contributions not listed here
M
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Responsibilities:
Designed and implemented a new data structure (Vector, Queue, Iterator), and created unit tests.
Ensuring Code Quality: Conducting comprehensive MISRA-C testing and adapting the library for full compliance with the strict coding rules required in an Embedded environment.
Built a benchmarking and testing environment in WSL for performance comparison against an OOC implementation.
Demonstrated the library's capabilities by implementing a generic, class-based Image Processing workflow , including image display and four functions for the Canny edge detection algorithm, all structured using the custom OOP architecture
E
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Responsibilities:
Task 1: Backend Development
Developed RESTful APIs using Node.js and Express
- Implemented authentication middleware
- Created database models with Prisma
Task 2: Frontend Work
Built React components with TypeScript
- Created reusable UI components
- Implemented state management
Task 3: Database Design
Designed PostgreSQL schema
- Created tables with proper relationships
- Optimized queries for performance
Task 4: DevOps & Deployment
- Set up CI/CD pipeline
- Configured Docker containers
- Deployed to AWS
Task 5: Testing
Wrote unit tests with Jest
- Achieved 80% code coverage
- Implemented integration tests
Task 6: Documentation
Created API documentation using Swagger
- Documented all endpoints
- Added code examples
Task 7: Code Review
Reviewed team members' code
- Provided constructive feedback
- Ensured code quality standards
Task 8: Performance Optimization
# Optimized database queries query = db.query.filter(...)Improved response time by 50%
Task 9: Security
- Implemented JWT authentication
- Added input validation
- Protected against SQL injection
Task 10: Final Integration
Integrated all components
- Tested end-to-end workflows
- Fixed critical bugs
...and more contributions not listed here
R
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Responsibilities:
Designed and implemented a new data structure (Binary Tree), and created unit tests.
Ensuring Code Quality: Conducting comprehensive MISRA-C testing and adapting the library for full compliance with the strict coding rules required in an Embedded environment.
Built a benchmarking and testing environment in WSL for performance comparison against a Pure C implementation.
Demonstrated the library's capabilities by implementing a generic, class-based Image Processing workflow. Implemented logic for image instantiation from file paths and developed arithmetic member functions (Add, Sub, Mul) to simulate operator behavior. Additionally, integrated the full Canny edge detection algorithm pipeline.