solution-template.go

package main

import (
	"fmt"
)

func main() {
	// Test cases
	testCases := []struct {
		nums []int
		name string
	}{
		{[]int{10, 9, 2, 5, 3, 7, 101, 18}, "Example 1"},
		{[]int{0, 1, 0, 3, 2, 3}, "Example 2"},
		{[]int{7, 7, 7, 7, 7, 7, 7}, "All same numbers"},
		{[]int{4, 10, 4, 3, 8, 9}, "Non-trivial example"},
		{[]int{}, "Empty array"},
		{[]int{5}, "Single element"},
		{[]int{5, 4, 3, 2, 1}, "Decreasing order"},
		{[]int{1, 2, 3, 4, 5}, "Increasing order"},
	}

	// Test each approach
	for _, tc := range testCases {
		fmt.Printf("Test Case: %s\n", tc.name)
		fmt.Printf("Input: %v\n", tc.nums)

		// Standard dynamic programming approach
		dpLength := DPLongestIncreasingSubsequence(tc.nums)
		fmt.Printf("DP Solution - LIS Length: %d\n", dpLength)

		// Optimized approach
		optLength := OptimizedLIS(tc.nums)
		fmt.Printf("Optimized Solution - LIS Length: %d\n", optLength)

		// Get the actual elements
		lisElements := GetLISElements(tc.nums)
		fmt.Printf("LIS Elements: %v\n", lisElements)
		fmt.Println("-----------------------------------")
	}
}

// DPLongestIncreasingSubsequence finds the length of the longest increasing subsequence
// using a standard dynamic programming approach with O(n²) time complexity.
func DPLongestIncreasingSubsequence(nums []int) int {
	// TODO: Implement this function
	return 0
}

// OptimizedLIS finds the length of the longest increasing subsequence
// using an optimized approach with O(n log n) time complexity.
func OptimizedLIS(nums []int) int {
	// TODO: Implement this function
	return 0
}

// GetLISElements returns one possible longest increasing subsequence
// (not just the length, but the actual elements).
func GetLISElements(nums []int) []int {
	// TODO: Implement this function
	return nil
}