Why Climbing Stairs Problem in DSA C#?

The Big Idea

What if you could instantly know all the ways to climb any staircase without listing them one by one?

The Scenario

Imagine you want to climb a staircase with many steps, but you can only take one or two steps at a time. Counting all the different ways to reach the top by hand is like trying to list every possible path without missing any.

The Problem

Doing this manually is slow and confusing because the number of ways grows quickly as the steps increase. You might forget some combinations or repeat others, making it error-prone and frustrating.

The Solution

The Climbing Stairs Problem uses a simple rule: the ways to reach a step equals the sum of ways to reach the two previous steps. This breaks the big problem into smaller, easy parts, letting a computer quickly find the answer without missing any possibilities.

Before vs After

✗ Before

int countWays(int steps) {
  // Try to list all paths manually
  // Very complex and slow
  return -1; // placeholder
}

✓ After

int countWays(int steps) {
  if (steps <= 2) return steps;
  int first = 1, second = 2;
  for (int i = 3; i <= steps; i++) {
    int current = first + second;
    first = second;
    second = current;
  }
  return second;
}

What It Enables

This concept lets you quickly find how many ways to climb any number of steps, even very large staircases, without missing or repeating any path.

Real Life Example

Think about planning different routes to climb a mountain trail where you can take one or two steps at a time. Knowing all possible ways helps hikers choose their path safely and efficiently.

Key Takeaways

Manual counting is slow and error-prone for many steps.

Breaking the problem into smaller parts simplifies counting.

Using this approach, computers solve the problem quickly and accurately.

Practice

1. What does the Climbing Stairs problem ask you to find?
Given n steps, how many distinct ways can you climb to the top if you can take 1 or 2 steps at a time?

easy

A. The minimum number of steps to reach the top

B. The number of distinct ways to reach the top

C. The maximum number of steps you can climb at once

D. The total number of steps climbed

Solution

1. Step 1: Understand the problem statement

   The problem asks for the count of different ways to climb n steps taking 1 or 2 steps at a time.

2. Step 2: Identify what is being counted

   We count distinct sequences of 1-step and 2-step moves that sum to n.

3. Final Answer:

   The number of distinct ways to reach the top -> Option B

4. Quick Check:

   Counting ways = number of sequences [OK]

Hint: Count sequences of 1 or 2 steps summing to n [OK]

Common Mistakes:

• Confusing number of ways with minimum steps
• Thinking about maximum steps instead of counting ways
• Counting total steps instead of sequences

2. Which of the following C# method signatures correctly represents a function to solve the Climbing Stairs problem for an integer n?

easy

A. public int ClimbStairs(int n)

B. int climb_stairs(string n)

C. void ClimbStairs(int n)

D. public string ClimbStairs(int n)

Solution

1. Step 1: Check method return type and parameters

   The function should return an integer count and take an integer n as input.

2. Step 2: Validate method signature syntax

   public int ClimbStairs(int n) uses public access, returns int, and takes int n, which is correct C# syntax.

3. Final Answer:

   public int ClimbStairs(int n) -> Option A

4. Quick Check:

   Correct return type and parameter [OK]

Hint: Return int, input int n, use public int method [OK]

Common Mistakes:

• Using void return type instead of int
• Using string parameter instead of int
• Returning string instead of int

3. What is the output of the following C# code for n = 4?

public int ClimbStairs(int n) {
    if (n <= 2) return n;
    int a = 1, b = 2, c = 0;
    for (int i = 3; i <= n; i++) {
        c = a + b;
        a = b;
        b = c;
    }
    return c;
}

Console.WriteLine(ClimbStairs(4));

medium

A. 5

B. 6

C. 7

D. 4

Solution

1. Step 1: Trace the loop for n=4

   Start with a=1, b=2. For i=3: c=1+2=3, a=2, b=3. For i=4: c=2+3=5, a=3, b=5.

2. Step 2: Return value after loop

   After loop ends, c=5 is returned and printed.

3. Final Answer:

   5 -> Option A

4. Quick Check:

   Ways for 4 steps = 5 [OK]

Hint: Use Fibonacci-like addition for steps count [OK]

Common Mistakes:

• Returning b instead of c
• Starting loop from wrong index
• Incorrect initial values for a and b

4. Identify the error in this C# code snippet for climbing stairs:

public int ClimbStairs(int n) {
    if (n == 1) return 1;
    int[] dp = new int[n];
    dp[0] = 1;
    dp[1] = 2;
    for (int i = 2; i <= n; i++) {
        dp[i] = dp[i-1] + dp[i-2];
    }
    return dp[n];
}

medium

A. Loop should start from i = 1

B. Incorrect base case for n == 1

C. Wrong return statement should be dp[n-1]

D. Array index out of bounds error due to dp size

Solution

1. Step 1: Check array size and indexing

   Array dp has size n, valid indices 0 to n-1. Loop runs i to n inclusive, accessing dp[n] which is out of bounds.

2. Step 2: Identify cause of error

   Accessing dp[n] causes runtime error. Loop should run to i < n, and return dp[n-1].

3. Final Answer:

   Array index out of bounds error due to dp size -> Option D

4. Quick Check:

   dp array size mismatch causes error [OK]

Hint: Array size n means last index n-1, not n [OK]

Common Mistakes:

• Loop running to i <= n instead of i < n
• Returning dp[n] instead of dp[n-1]
• Not initializing dp array correctly

5. You want to find the number of ways to climb 10 steps but now you can take 1, 2, or 3 steps at a time. Which approach correctly adapts the Climbing Stairs problem?

hard

A. Use dp[i] = dp[i-1] * dp[i-2] * dp[i-3] with base cases dp[0]=0, dp[1]=1, dp[2]=1

B. Use dp[i] = dp[i-1] + dp[i-2] with base cases dp[0]=1, dp[1]=1

C. Use dp[i] = dp[i-1] + dp[i-2] + dp[i-3] with base cases dp[0]=1, dp[1]=1, dp[2]=2

D. Use recursion without memoization for all steps

Solution

1. Step 1: Understand the new step options

   Now steps can be 1, 2, or 3 at a time, so ways to reach i depend on previous 3 dp values.

2. Step 2: Formulate dp relation and base cases

   dp[i] = dp[i-1] + dp[i-2] + dp[i-3]. Base cases: dp[0]=1 (one way to stand still), dp[1]=1, dp[2]=2.

3. Final Answer:

   Use dp[i] = dp[i-1] + dp[i-2] + dp[i-3] with base cases dp[0]=1, dp[1]=1, dp[2]=2 -> Option C

4. Quick Check:

   Sum of last 3 dp values for each step [OK]

Hint: Add last 3 dp values for steps 1,2,3 [OK]

Common Mistakes:

• Multiplying dp values instead of adding
• Using only last 2 dp values
• Not setting correct base cases