# SORTIFY: C++ Sorting Algorithm Performance Analysis
> A comparative study of Bubble, Selection, Insertion, Merge, Quick, and Counting Sort in C++ with execution time and swap count analysis.

Tags: sorting-algorithms, cpp-programming, algorithm-analysis, computer-science, coding-project, performance-metrics
## Slide 1: SORTIFY | Sorting Algorithm Analyzer
- A comparative study of six sorting algorithms in C++.
- Developed by: Bhumik Singh Dhami, Kushagra Singhal, Aditya Gupta, and Priyanshu Tiwari.

## Slide 2: Project Abstract
- Real performance depends on time, memory, and system behavior, not just Big-O notation.
- Compares Bubble, Selection, Insertion, Merge, Quick, and Counting Sort.
- Uses the `<chrono>` library for high-precision timing.
- Tests random, sorted, and nearly sorted array inputs.

## Slide 3: Meet the Team
- Student project team details with contact information and GitHub repository links.

## Slide 4: System Architecture
- Visual diagram showing the flow from Input Handler to Data Generator, Analyzer Core, Sorting Algorithms, and final Output Display.

## Slide 5: Project Approach
- Seven-step methodology: Algorithm Selection, Implementation, Time Measurement, Swap Counting, Testing, Analysis, and reporting.

## Slide 6: Key Features Implemented
- Built with C++17, STL, and `<iomanip>`.
- High-precision timing and swap counter integration.
- Modular architecture and color-coded terminal output for better readability.

## Slide 7: Task Distribution
- Detailed breakdown of module ownership among team members, covering architecture, data generators, specific algorithms, and UI formatting.

## Slide 8: Challenges & Solutions
- **Precise Timing:** Used `high_resolution_clock` to measure microsecond-fast runs.
- **Swap Counting:** Used pass-by-reference in recursive calls for Merge and Quick Sort.
- **Negative Numbers:** Implemented offset-based indexing for Counting Sort.
- **Memory:** Used a copy-on-test approach for large datasets.

## Slide 9: Project Outcomes & Deliverables
- Multi-algorithm support and multi-dataset testing results.
- Structured tabular result display side-by-side for comparison.

## Slide 10: Progress Overview
- Project status as of April 2026: 100% completion of all phases including algorithm implementation, timer modules, and data generators.
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