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Testing Fractional Knapsack Algorithm Implementation in hello-algo

This test suite validates the fractional knapsack algorithm implementation in Go, examining how items with different weights and values are optimally selected to maximize value within capacity constraints. The test verifies the greedy approach for solving the fractional knapsack problem.

Test Coverage Overview

The test suite provides coverage for the fractional knapsack algorithm implementation.

Key areas tested include:

Input validation with predefined weights and values arrays
Capacity constraint handling
Maximum value calculation within weight limits
Verification of greedy selection strategy

Implementation Analysis

The testing approach utilizes Go’s native testing framework to validate the fractional knapsack algorithm’s core functionality. The test implements a straightforward case with five items of varying weights and values, testing against a fixed capacity of 50 units.

Technical patterns include:

Direct function invocation testing
Output verification through fmt.Println
Slice handling for weights and values

Technical Details

Testing infrastructure includes:

Go testing package (testing)
Standard fmt package for output formatting
Integer slice operations
Single test function structure

Best Practices Demonstrated

The test implementation showcases several testing best practices in Go.

Notable practices include:

Clear test function naming convention
Organized input data preparation
Focused test scope
Readable variable naming
Proper package organization

krahets/hello-algo

codes/go/chapter_greedy/fractional_knapsack_test.go

            
// File: fractional_knapsack_test.go
// Created Time: 2023-07-23
// Author: Reanon ([email protected])

package chapter_greedy

import (
	"fmt"
	"testing"
)

func TestFractionalKnapsack(t *testing.T) {
	wgt := []int{10, 20, 30, 40, 50}
	val := []int{50, 120, 150, 210, 240}
	capacity := 50

	// 贪心算法
	res := fractionalKnapsack(wgt, val, capacity)
	fmt.Println("不超过背包容量的最大物品价值为", res)
}