Projects

Reliable Data Transport Protocol Implementation

link: https://github.com/jironoor8903/TCP (opens in a new tab)

Developed a reliable data transport protocol for computer networks. Designed and implemented mechanisms to ensure data packets are delivered accurately and in order, including handling packet loss, duplication, and reordering. This project involved creating algorithms for error detection, flow control, and congestion control to maintain efficient and reliable data transmission across networked systems.

Reliable Data Transport Protocol Implementation

link: https://github.com/jironoor8903/traceroute (opens in a new tab)

Developed a traceroute tool in a Computer Networks course to analyze network paths and diagnose network issues. The project involved sending probe packets with incrementing time-to-live (TTL) values and recording the routers they traversed, measuring round-trip times, and handling ICMP responses. This implementation provided insights into the structure and performance of network routes, aiding in network diagnostics and performance analysis. The project demonstrated proficiency in network programming and understanding of internet protocols.

PINTOS Operating System

link: https://cs162.org/static/proj/pintos-docs/ (opens in a new tab)

Kernel-Level Dynamic Memory Allocation

link: https://github.com/jironoor8903/Kernel-Level-Dynamic-Memory-Allocation (opens in a new tab)

Enhanced the Pintos operating system by implementing dynamic memory allocation for user processes. Developed key functionalities for malloc, realloc, and free, enabling user programs to efficiently manage memory. This involved updating the kernel to support dynamic memory requests, significantly improving the operating system's memory management capabilities.

BazingAI

News App for kids with AI Summarization and Chatbot powered by Google GEMINI coded in Swift.

BazingAI

SQL Database Seeder

link: https://github.com/jironoor8903/sql-database-seeder (opens in a new tab)

Developed a comprehensive SQL database seeder tool to automate the population of databases with test data. The project includes features for generating realistic and randomized data, supporting various SQL databases, and enabling custom data schemas. This tool enhances testing and development processes by providing a reliable method to populate databases efficiently, ensuring consistent and accurate data for testing scenarios.

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