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Testing Kruskal's Minimum Spanning Tree Algorithm Implementation in TheAlgorithms/Python

This test suite validates the Kruskal’s Minimum Spanning Tree algorithm implementation in Python. It focuses on verifying the correct generation of minimum spanning trees from weighted graph inputs, ensuring optimal path selection and edge weight calculations.

Test Coverage Overview

The test coverage focuses on validating Kruskal’s algorithm functionality with a specific graph structure containing 9 nodes and 14 edges. Key areas tested include:

Edge weight calculations and sorting
Minimum spanning tree path verification
Expected output structure validation
Graph connectivity verification

Implementation Analysis

The testing approach implements a comprehensive validation of the algorithm’s core functionality through a predefined graph structure. The test utilizes Python’s assert statement to compare the sorted expected and actual results, ensuring consistent output regardless of edge order.

Direct function call testing pattern
Sorted array comparison methodology
Edge case handling for weighted paths

Technical Details

Testing implementation details:

Python’s built-in testing framework
Array-based graph representation
Edge weight validation through nested lists
Assertion-based result verification

Best Practices Demonstrated

The test demonstrates several testing best practices for graph algorithms:

Clear test case structure with input setup
Explicit expected vs actual result comparison
Comprehensive edge coverage
Deterministic output validation
Well-organized test data separation

thealgorithms/python

graphs/tests/test_min_spanning_tree_kruskal.py

            
from graphs.minimum_spanning_tree_kruskal import kruskal


def test_kruskal_successful_result():
    num_nodes = 9
    edges = [
        [0, 1, 4],
        [0, 7, 8],
        [1, 2, 8],
        [7, 8, 7],
        [7, 6, 1],
        [2, 8, 2],
        [8, 6, 6],
        [2, 3, 7],
        [2, 5, 4],
        [6, 5, 2],
        [3, 5, 14],
        [3, 4, 9],
        [5, 4, 10],
        [1, 7, 11],
    ]

    result = kruskal(num_nodes, edges)

    expected = [
        [7, 6, 1],
        [2, 8, 2],
        [6, 5, 2],
        [0, 1, 4],
        [2, 5, 4],
        [2, 3, 7],
        [0, 7, 8],
        [3, 4, 9],
    ]

    assert sorted(expected) == sorted(result)