How CodingZap helped Deoraya with his Dijkstra’s Algorithm Assignment in C++

We are here again with another case study of a student named Deoraya from USA who was struggling with Dijkstra’s algorithm project in C++. Read on.

Introduction: Deoraya’s Challenge

Deoraya, a freshman computer science student at a Midwest university, had recently started learning object-oriented programming languages like C++ in his early coursework. He was assigned a project to implement Dijkstra’s Algorithm in C++, which required building a program to find the shortest path between nodes in a graph—a fundamental concept in data structures and algorithms.

While Deoraya understood the theory and concept behind the algorithm, coding was not his strong suit, as he was new to programming and lacked practical skills. He faced challenges with graph representation, debugging logical errors, and optimizing his code. With a tight deadline approaching, he reached out to us for assistance.

The Problem: Coding Challenges while working on C++ task

When Deoraya approached us with his assignment, we assigned our best C++ expert, Mr. Khizer, to handle his work. After gathering the initial requirements and having a quick chat, we identified the issues he was facing. He had written some initial code, but it contained several logical errors and lacked proper implementation. Below, we have listed the issues faced by Deoraya:

Graph Representation in C++:
- Deoraya had difficulty choosing the right data structure to represent the graph, which is key for implementing Dijkstra’s Algorithm efficiently.
Priority Queue Integration:
- He was unfamiliar with using STL’s priority_queue, essential for efficiently selecting the next node in the shortest path.
Logic Bugs:
- His initial implementation produced incorrect results, as his algorithm didn’t properly update the distances of neighboring nodes.
Optimizing Runtime:
- Deoraya’s program ran slower than expected for large graphs, making it unsuitable for his professor’s test cases.

Once all issues were identified, our team started the work in order to meet his deadline.

The Solution: How CodingZap Helped Deoraya Succeed

Mr. Khizer and team worked on the coding part carefully keeping Mickey in the loop about the step by step progress of the project.

Step 1: Choosing the Right Data Structure

Our first step was guiding Deoraya to represent the graph as an adjacency list using C++ vectors, which is memory-efficient and suitable for sparse graphs.

We also explained how each vector stores pairs representing a neighboring node and the edge weight, ensuring Deoraya understood how this structure aligns with Dijkstra’s Algorithm.

You take a look at the sample code below to make you understand the concept.

				
					#include <vector>
#include <utility> // For std::pair

using namespace std;

// Adjacency list representation
vector<pair<int, int>> graph[100]; // Array of vectors for 100 nodes

Step 2: Implementing the Priority Queue

Next, we introduced Deoraya to the priority_queue from C++’s Standard Template Library (STL).

We taught him how to use a min-heap to prioritize nodes with the smallest distance and after that also explained how greater< pair <int, int>> ensures the smallest distance is processed first.

Please look at the code snippet below for the better understanding.

				
					#include <queue>
#include <vector>

priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;
pq.push({0, source}); // Push initial source node with distance 0

Step 3: Debugging the Algorithm

Deoraya’s original implementation had errors in how distances to neighboring nodes were updated.

Our expert rewrote the critical logic and added comments to clarify each step. We also provided tips on using debugging tools in Visual Studio IDEs to trace variable values and pinpoint issues.

				
					for (auto neighbor : graph[u]) {
    int v = neighbor.first; // Neighbor node
    int weight = neighbor.second; // Edge weight
    if (distance[u] + weight < distance[v]) {
        distance[v] = distance[u] + weight;
        pq.push({distance[v], v}); // Push updated distance
    }
}

Step 4: Optimizing code and Performance metrics

Finally, we optimized the program to handle large graphs by ensuring efficient edge traversal and avoiding unnecessary calculations.

Our expert had a meeting with Deoraya and gave him some feedback on his initial code and helped rewrite critical sections for better runtime.

Results: Deoraya’s Academic Success

Deoraya submitted a working program that correctly calculated the shortest path for all test cases and also learned how to represent graphs, use STL’s priority_queue, and debug complex algorithms.

Testimonial :

“I was ready to give up on my C++ project, but CodingZap saved the day. They made the toughest parts of Dijkstra’s Algorithm easy to understand, and I couldn’t be happier with my grade! Kudos to Mr. Khizer and team.” – Deoraya, USA

Conclusion :

You can see how a student was struggling with his C++ project, and our expert not only saved him from failing the assignment but also helped him learn a new concept with ease.

At CodingZap, we understand how challenging data structures and algorithms can be. Whether you’re stuck on Dijkstra’s Algorithm, debugging code, or optimizing runtime, we’re here to help you succeed.

If you’re struggling with your C++ projects, let us be your partner in achieving academic excellence.