This repository serves as a comprehensive archive of my Data Structures and Algorithms (DSA) rigorous practices and code logs completed during my 3rd semester. Every module inside this workspace strictly aligns with the official Higher Education Commission (HEC) Pakistan computer science curriculum outlines.
Rather than high-level abstractions, this space tracks my journey of building, manipulating, and optimizing fundamental memory structures and search/sort algorithms from scratch to master computational complexity and engineering logic.
The codebase documents thorough programmatic implementations across key algorithmic domains:
- Arrays & Matrices: Multi-dimensional tracking, indexing optimization, memory allocation, and vector operations.
- Linked Lists: Single, Double, and Circular Linked Lists—focusing on runtime memory allocation, pointer manipulation, and node routing.
- Stacks & Queues: First-In-Last-Out (FILO) and First-In-First-Out (FIFO) logic queues, including circular queues and overflow tracking.
- Trees & Graphs: Binary Trees, Binary Search Trees (BST), tree traversals (In-order, Pre-order, Post-order), and node balancing configurations.
- Search Optimization: Binary Search and Linear Search mechanisms over sorted/unsorted arrays.
- Sorting Efficiency: Algorithmic logic implementation including Bubble Sort, Insertion Sort, Selection Sort, Merge Sort, and Quick Sort pipelines.
Writing these practice scripts from the ground up demonstrates operational capability in:
- Memory Management: Efficient memory utilization, pointer references, and structure cleanup.
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Time & Space Complexity: Analyzing execution loops through Big-O notation (
$\mathcal{O}(n)$ ,$\mathcal{O}(n \log n)$ , $\mathcal{O}(n^2)$) to optimize execution bottlenecks. - Defensive Boundary Validations: Implementing edge-case checks (e.g., Stack Underflow, Queue Overflow, Null Pointer exceptions) to ensure crash-free execution.
To compile or review any specific DSA structural implementation code locally:
- Clone the Academic Lab Repository:
git clone [https://github.com/mhassan619/3rd-Semester-.git](https://github.com/mhassan619/3rd-Semester-.git)
cd 3rd-Semester-
- Run individual practice files: Browse the target structure directory and run your code utilizing your configured local C++/Python environment compiler.
"Not perfect, just improving every single day."
This repository stands as a solid testament to my technical foundational depth. Mastering these low-level algorithmic logic blocks during the 3rd semester is what now enables me to design optimized object-oriented architectures, scale smart data pipelines, and deploy high-performance Machine Learning and AI Automation applications smoothly.