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DSA Goprogramming~10 mins

Why Graphs Exist and What Trees Cannot Model in DSA Go - Test Your Knowledge

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to create a graph node with a label.

DSA Go
type Node struct {
	label string
	neighbors []*Node
}

func NewNode(label string) *Node {
	return &Node{label: [1], neighbors: []*Node{}}
}
Drag options to blanks, or click blank then click option'
Alabel
B"label"
Cneighbors
Dnil
Attempts:
3 left
💡 Hint
Common Mistakes
Using "label" (a string literal) instead of the variable label.
Assigning neighbors instead of label.
2fill in blank
medium

Complete the code to add an edge from one node to another in an undirected graph.

DSA Go
func AddEdge(n1, n2 *Node) {
	n1.neighbors = append(n1.neighbors, [1])
	n2.neighbors = append(n2.neighbors, n1)
}
Drag options to blanks, or click blank then click option'
An2
Bnil
Cneighbors
Dn1
Attempts:
3 left
💡 Hint
Common Mistakes
Appending n1 to its own neighbors.
Appending neighbors instead of a node.
3fill in blank
hard

Fix the error in the function that checks if a graph contains a cycle using DFS.

DSA Go
func hasCycle(node *Node, visited map[*Node]bool, parent *Node) bool {
	visited[node] = true
	for _, neighbor := range node.neighbors {
		if !visited[[1]] {
			if hasCycle(neighbor, visited, node) {
				return true
			}
		} else if neighbor != parent {
			return true
		}
	}
	return false
}
Drag options to blanks, or click blank then click option'
Aparent
Bneighbor
Cnode
Dvisited
Attempts:
3 left
💡 Hint
Common Mistakes
Checking visited[node] instead of visited[neighbor].
Using parent or visited as index incorrectly.
4fill in blank
hard

Fill both blanks to create a map of node labels to their neighbors' labels.

DSA Go
func LabelNeighbors(nodes []*Node) map[string][]string {
	result := make(map[string][]string)
	for _, node := range nodes {
		neighbors := []string{}
		for _, neighbor := range node.[1] {
			neighbors = append(neighbors, neighbor.[2])
		}
		result[node.label] = neighbors
	}
	return result
}
Drag options to blanks, or click blank then click option'
Aneighbors
Blabel
Attempts:
3 left
💡 Hint
Common Mistakes
Using node.label instead of node.neighbors in the first blank.
Using neighbor.neighbors instead of neighbor.label in the second blank.
5fill in blank
hard

Fill all three blanks to implement a BFS traversal that returns node labels in visit order.

DSA Go
func BFS(start *Node) []string {
	visited := make(map[*Node]bool)
	queue := []*Node{start}
	visited[start] = true
	order := []string{}
	for len(queue) > 0 {
		current := queue[[1]]
		queue = queue[[2]:]
		order = append(order, current.[3])
		for _, neighbor := range current.neighbors {
			if !visited[neighbor] {
				visited[neighbor] = true
				queue = append(queue, neighbor)
			}
		}
	}
	return order
}
Drag options to blanks, or click blank then click option'
A0
B1
Clabel
Dlen(queue)
Attempts:
3 left
💡 Hint
Common Mistakes
Using len(queue) or 1 as index instead of 0.
Appending current instead of current.label.

Practice

(1/5)
1. Why do we need graphs when we already have trees in data structures?
easy
A. Because graphs can represent connections between nodes in any pattern, including cycles and multiple parents.
B. Because trees are faster to traverse than graphs.
C. Because trees can only store numbers, but graphs can store any data.
D. Because graphs use less memory than trees.

Solution

  1. Step 1: Understand tree limitations

    Trees have a strict hierarchy where each node has only one parent and no cycles.
  2. Step 2: Understand graph capabilities

    Graphs allow nodes to connect in any way, including cycles and multiple parents, which trees cannot model.
  3. Final Answer:

    Because graphs can represent connections between nodes in any pattern, including cycles and multiple parents. -> Option A
  4. Quick Check:

    Graphs model complex connections [OK]
Hint: Graphs allow cycles and multiple parents; trees do not [OK]
Common Mistakes:
  • Thinking trees can have cycles
  • Confusing data types stored with structure capabilities
  • Assuming graphs always use less memory
2. Which of the following is the correct way to declare an adjacency list for a graph in Go?
easy
A. var graph [][]int = make(map[int][]int)
B. var graph []int = make([]int, 10)
C. var graph map[int]int = make(map[int]int)
D. var graph map[int][]int = make(map[int][]int)

Solution

  1. Step 1: Understand adjacency list structure

    An adjacency list maps each node (int) to a list of connected nodes ([]int).
  2. Step 2: Match Go syntax

    map[int][]int is the correct type, and make(map[int][]int) initializes it properly.
  3. Final Answer:

    var graph map[int][]int = make(map[int][]int) -> Option D
  4. Quick Check:

    Adjacency list = map[int][]int [OK]
Hint: Adjacency list is map from node to slice of nodes [OK]
Common Mistakes:
  • Using slice instead of map for adjacency list
  • Wrong map value type (int instead of []int)
  • Incorrect initialization syntax
3. What will be the output of the following Go code snippet modeling a graph with cycles?
package main
import "fmt"
func main() {
    graph := map[int][]int{
        1: {2, 3},
        2: {3},
        3: {1},
    }
    visited := make(map[int]bool)
    dfs := func(node int) {}
    var dfsFunc func(int)
    dfsFunc = func(node int) {
        if visited[node] {
            return
        }
        visited[node] = true
        fmt.Print(node, " ")
        for _, neighbor := range graph[node] {
            dfsFunc(neighbor)
        }
    }
    dfsFunc(1)
}
medium
A. 1 2 3
B. 1 3 2
C. 1 2 3 1 3 2 (infinite loop)
D. Compilation error

Solution

  1. Step 1: Trace DFS starting at node 1

    Visit 1, mark visited. Then visit neighbors 2 and 3 recursively, skipping visited nodes.
  2. Step 2: Check visited to avoid cycles

    Node 3 points back to 1, but 1 is visited, so recursion stops, preventing infinite loop.
  3. Final Answer:

    1 2 3 -> Option A
  4. Quick Check:

    DFS with visited avoids cycles = 1 2 3 [OK]
Hint: Visited map prevents revisiting nodes in DFS [OK]
Common Mistakes:
  • Ignoring visited check causing infinite recursion
  • Confusing order of traversal
  • Assuming compilation error due to recursion
4. Identify the bug in this Go code snippet that tries to build a graph adjacency list:
graph := make(map[int][]int)
graph[1] = append(graph[1], 2)
graph[2] = append(graph[2], 3)
graph[3] = append(graph[3], 1)
medium
A. The map is not initialized before use.
B. Appending to a nil slice in map causes runtime error.
C. No bug; code correctly builds the graph adjacency list.
D. Keys must be strings, not integers.

Solution

  1. Step 1: Check map initialization

    map[int][]int is initialized with make, so it's ready for use.
  2. Step 2: Understand append behavior on nil slices

    Appending to a nil slice returns a new slice; map entries get updated correctly.
  3. Final Answer:

    No bug; code correctly builds the graph adjacency list. -> Option C
  4. Quick Check:

    Appending to nil slice in map is safe [OK]
Hint: Appending to nil slice in map is safe in Go [OK]
Common Mistakes:
  • Thinking map must be pre-filled with empty slices
  • Assuming append on nil slice causes error
  • Believing map keys must be strings
5. You want to model a social network where users can follow multiple users and cycles exist (e.g., A follows B, B follows C, C follows A). Why is a graph a better choice than a tree, and how would you represent this in Go?
hard
A. Because trees allow cycles; use a tree structure with parent pointers.
B. Because trees cannot represent cycles or multiple parents; use a map[int][]int adjacency list to represent followers.
C. Because trees are faster; use a slice of structs to represent users.
D. Because graphs use less memory; use a map[int]int to store followers.

Solution

  1. Step 1: Understand why trees are insufficient

    Trees do not allow cycles or multiple parents, which are common in social networks.
  2. Step 2: Choose graph representation in Go

    An adjacency list using map[int][]int maps each user to the list of users they follow, allowing cycles and multiple connections.
  3. Final Answer:

    Because trees cannot represent cycles or multiple parents; use a map[int][]int adjacency list to represent followers. -> Option B
  4. Quick Check:

    Graphs model cycles and multiple parents [OK]
Hint: Use graph adjacency list for cycles and multiple parents [OK]
Common Mistakes:
  • Choosing tree despite cycles in data
  • Using map[int]int which can't store multiple followers
  • Assuming trees allow cycles
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10 questions~5 mineasy hard