COP3530 Project 3 - CrashGuard

Our project explores the performance of hashmaps and heaps by comparing how effectively each data structure can retrieve the top k elements.

• Language: C++ 20
• Compiler: GCC 13.2

Group Documentation and Video:

Project Report

Overview - YouTube

Project Directory:

• resources
  • US_Accidents_March23.csv: contains the dataset from Kaggle
• src
  • AttributeData.h: contains a struct that is used by both data structures
  • DataNode.h: contains a struct that is used to contain a single crash and all its data when parsing
  • HashMap.cpp
  • HashMap.h : a hashmap template class implemented from scratch with hashing and separate-chaining collision resolution
  • Heap.cpp
  • Heap.h: a heap template class implemented from scratch using comparators and function pointers
  • main.cpp: menu-driven program allowing users to learn about US accidents and compares data structures

Instructions for Running:

Clone Repository

cd [where you want to download]
git clone https://github.com/raglandconnor/CrashGuard

Place Dataset in Directory

1. Download US vehicle crash dataset
2. Place inside resources folder

Create Compiled Program

g++ -std=c++17 -c src/main.cpp -o main.o && g++ -std=c++17 -c src/HashMap.cpp -o HashMap.o && g++ -std=c++17 -c src/Heap.cpp -o Heap.o && g++ -std=c++17 main.o HashMap.o Heap.o -o CrashGuard

Execute

./CrashGuard

References:

• US Accidents (2016 - 2023) Dataset
  • Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, and Rajiv Ramnath. “A Countrywide Traffic Accident Dataset.”, 2019.
  • Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, Radu Teodorescu, and Rajiv Ramnath. "Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights." In proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, 2019.