Data Structures & Algorithms
Bellman-Ford Algorithm
Prepare for your coding interviews by mastering the Bellman-Ford algorithm. Our guide explains how to handle negative edge weights, detect negative cycles, and provides AI-powered practice.
Bellman-Ford Algorithm Implementation
Here is a Python implementation of the Bellman-Ford algorithm. This version also includes logic to detect negative cycles.
def bellman_ford(graph, start):
# graph is a list of edges in the format (u, v, w)
num_vertices = len(set(u for u, v, w in graph) | set(v for u, v, w in graph))
distances = {i: float('Infinity') for i in range(num_vertices)}
distances[start] = 0
for _ in range(num_vertices - 1):
for u, v, w in graph:
if distances[u] != float('Infinity') and distances[u] + w < distances[v]:
distances[v] = distances[u] + w
# Check for negative weight cycles
for u, v, w in graph:
if distances[u] != float('Infinity') and distances[u] + w < distances[v]:
return "Graph contains a negative weight cycle"
return distances
AI Coach Tip: The Bellman-Ford algorithm is slower than Dijkstra's (O(VE) vs O(E log V)), but its ability to handle negative weights makes it essential for certain problems. Always remember the two main phases: V-1 iterations of relaxation, followed by one final iteration to check for negative cycles.
Related Algorithm Guides
Explore more algorithm interview guides powered by AI coaching
Floyd Warshall Algorithm Interview Questions
AI-powered interview preparation guide
Topological Sort For Directed Acyclic Graphs Dags
AI-powered interview preparation guide
Quickselect Algorithm For Finding Kth Smallest Element
AI-powered interview preparation guide
Online Interview Etiquette And Preparation
AI-powered interview preparation guide
Related Algorithm Resources
All Interview Solutions
Browse our complete collection of AI-powered interview preparation guides.
GeeksforGeeks Algorithms
Comprehensive algorithm tutorials and practice problems.
LeetCode Practice
Algorithm coding challenges and interview preparation.
Algorithm Visualizations
Interactive visualizations for understanding algorithms.