Who Won the Election? TCS Interview Question

Imagine a lively election influence algorithm where two candidates, A and B, are locked in a close contest. In this coding challenge, each candidate has dedicated supporters, but the crucial swing lies with neutral voters. These undecided individuals, just like in real elections, have the power to shift the balance, and understanding how to determine the election winner in coding can make all the difference.

In this article, we’ll dive into a TCS coding interview question that explores how to calculate the impact of A and B supporters on neutral voters, using both a brute force vs optimized solution approach. By the end, you’ll gain insights into coding techniques that can efficiently decide the winner in an election scenario, based on neutral voters influence coding challenge principles. This guide offers practical steps and examples to build your coding skills for similar problem-solving tasks.

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Introduction: Understanding the Election Scenario

Imagine a lively election where two candidates, A and B, are competing closely for the win. Just like in any real-world election, some people are strong supporters of one candidate, while others back the opponent. But there’s also a group of undecided or neutral voters whose choice could ultimately decide the outcome. These neutral voters are just like the undecided people in a real election – their votes could swing the result in favour of one candidate or the other.

In this article, we’ll explore a coding approach to determine the winner based on the influence of these voters. We’ll break down the scenario into simple steps, making it easier to follow and understand how each voter’s choice impacts the final result.

Problem Breakdown: Setting Up the Election Queue

To understand this election, let’s take a closer look at the lineup of voters. Imagine a long, crowded queue where each person represents a different kind of voter. Some are cheering for candidate A, some are rooting for candidate B, and others are neutral, still deciding which side to support.

In this queue:

The letter ‘A’ represents a supporter of candidate A.
The letter ‘B’ represents a supporter of candidate B.
The ‘-’ symbol represents a neutral voter who hasn’t chosen a side yet.
It’s as if each person in line is holding up a sign that shows their stance. The neutral voters are key here because, as they’re swayed, they could tip the balance and determine who wins the election.

The Rules of Movement: How Supporters Try to Win Votes

In this election scenario, both supporters of A and B have a chance to win over the neutral voters. However, there are specific rules for how they can move to influence these undecided votes.

• Supporters of A can only move to the left.
• Supporters of B can only move to the right.
• Both groups of supporters move simultaneously to reach any neutral voters in their path.
• If a supporter of A reaches a neutral voter before a supporter of B, that voter will be influenced to support A. If a supporter of B reaches a neutral voter first, they will sway that voter to support B.
• If both A and B supporters reach a neutral voter at the same time, that voter remains neutral.

Let’s look at a simple example to make this clearer. Imagine the queue looks like this: B–A-. Here’s how the movement works:

• The B supporter moves right, while the A supporter moves left, both trying to reach the neutral voters (-).
• Since B can get to the first two neutral voters on the left side first, those voters are influenced to support B.
• A manages to reach the last neutral voter on the right side, swaying them to support A.

By following these rules, each side tries to sway as many neutral voters as possible to help their candidate win the election.

Objective of the Problem: Deciding the Winner

The goal of this problem is to determine the winner based on how many voters each candidate ends up with after all neutral voters are influenced. Here’s how it works:

If candidate A has more votes after all the neutral voters are influenced, then A wins.
If candidate B ends up with more votes, then B wins.
However, if both A and B have the same number of votes, it’s a “Coalition”, meaning neither candidate wins outright.
For example, in the queue B–A-:

By the end of the process, B has successfully gained 3 supporters, while A has 2.
Since B has more votes, B wins in this scenario.
This simple check helps us conclude who won based on the influence each candidate had over the neutral voters.

Brute Force Solution: A Step-by-Step Approach

One way to solve this problem is with a straightforward, step-by-step method known as the Brute Force Approach. Here, we look at each neutral voter (-) individually to determine which candidate is closest and can influence them.

Here’s how it works:

1. Initial Count: Start by counting how many votes each candidate, A and B, already has.
2. Influence Check: For each neutral voter, look at the nearest supporters of A and B on either side.
   • If a supporter of A is closer, that neutral voter is influenced to support A.
   • If a supporter of B is closer, the neutral voter switches to B.
   • If they are equally distant, the voter remains neutral.
3. Adjusting Votes: Based on the proximity of supporters, adjust the vote count for A or B.

This approach is simple to understand and follow. However, because it involves checking each neutral voter against both A and B supporters in a nested loop, it can be quite slow for larger queues. The complexity is O(N²), which means that for very long queues, this method may take a lot of time to complete.

Election Influence Algorithm in C#: Solve TCS Coding Interview Question Efficiently

using System;

public class Election
{
    public static string DetermineWinner(string queue)
    {
        int aVotes = 0, bVotes = 0;
        int[] leftA = new int[queue.Length];
        int[] rightB = new int[queue.Length];
        
        // Initialize distances for leftA and rightB
        int lastA = -1, lastB = -1;

        for (int i = 0; i < queue.Length; i++)
        {
            leftA[i] = lastA == -1 ? int.MaxValue : i - lastA;
            if (queue[i] == 'A') lastA = i;
        }

        for (int i = queue.Length - 1; i >= 0; i--)
        {
            rightB[i] = lastB == -1 ? int.MaxValue : lastB - i;
            if (queue[i] == 'B') lastB = i;
        }

        // Count initial votes and influence neutral voters
        foreach (char c in queue)
        {
            if (c == 'A') aVotes++;
            else if (c == 'B') bVotes++;
        }

        for (int i = 0; i < queue.Length; i++)
        {
            if (queue[i] == '-')
            {
                if (leftA[i] < rightB[i]) aVotes++;
                else if (rightB[i] < leftA[i]) bVotes++;
            }
        }

        return aVotes > bVotes ? "A wins" : bVotes > aVotes ? "B wins" : "Coalition";
    }

    public static void Main()
    {
        string queue = "14--AB--AB---A--";
        Console.WriteLine(DetermineWinner(queue));
    }
}

Election Influence Algorithm in C++: Brute Force vs Optimized Solution Explained

#include <iostream>
#include <vector>
#include <string>
#include <climits>

std::string determineWinner(const std::string& queue) {
    int aVotes = 0, bVotes = 0;
    std::vector<int> leftA(queue.size(), INT_MAX);
    std::vector<int> rightB(queue.size(), INT_MAX);

    // Fill distances for leftA and rightB
    int lastA = -1, lastB = -1;

    for (int i = 0; i < queue.size(); i++) {
        if (lastA != -1) leftA[i] = i - lastA;
        if (queue[i] == 'A') lastA = i;
    }

    for (int i = queue.size() - 1; i >= 0; i--) {
        if (lastB != -1) rightB[i] = lastB - i;
        if (queue[i] == 'B') lastB = i;
    }

    // Count initial votes and influence neutral voters
    for (char c : queue) {
        if (c == 'A') aVotes++;
        else if (c == 'B') bVotes++;
    }

    for (int i = 0; i < queue.size(); i++) {
        if (queue[i] == '-') {
            if (leftA[i] < rightB[i]) aVotes++;
            else if (rightB[i] < leftA[i]) bVotes++;
        }
    }

    if (aVotes > bVotes) return "A wins";
    else if (bVotes > aVotes) return "B wins";
    else return "Coalition";
}

int main() {
    std::string queue = "14--AB--AB---A--";
    std::cout << determineWinner(queue) << std::endl;
    return 0;
}

Optimized Approach: Counting Influence Efficiently

To make the process of deciding influence faster, we can use an Optimized Approach by pre-computing distances. Instead of checking each neutral voter repeatedly, we’ll calculate distances in advance, allowing us to determine influence with a single scan.

Here’s the idea:

1. Distance Arrays: We create two arrays:
   • One array records the distances from each position to the nearest A supporter moving left.
   • The other array stores distances from each position to the nearest B supporter moving right.
2. Steps to Solve Efficiently:
   • First, go through the queue from left to right and fill in distances for A supporters.
   • Then, move from right to left to record distances for B supporters.
3. Quick Influence Check: Now, for each neutral voter, we can simply check the values in our pre-computed arrays to see which supporter is closest. This lets us determine influence without recalculating distances, saving time.

Complexity Insight: By using this pre-computed information, we avoid the nested loops of the Brute Force Approach. This solution has a time complexity of O(N), making it much faster for long queues and more practical for large inputs.

Comparing Approaches: When to Use Which Solution

When solving this problem, it’s helpful to understand the strengths of each approach and when to use them:

1. Brute Force Approach: This method is best for smaller queues where performance isn’t a major concern. It’s also helpful for understanding the basic logic of how supporters influence neutral voters one by one.
2. Optimized Solution: For longer queues or larger data sets, the optimized approach is the way to go. By pre-computing distances, it cuts down computation time significantly, making it much more efficient for big inputs.

Interview Insight: Knowing both approaches shows flexibility in problem-solving, which is highly valued in interviews. Demonstrating that you can use a basic method to build understanding and then improve efficiency with an optimized solution reflects strong analytical and practical skills.

Sample Test Cases and Expected Outcomes

Let’s walk through an example to see how each approach works in practice.

• Example Walkthrough: Consider the queue “14–AB–AB—A–“.
  • Using the Brute Force Approach, we’d examine each neutral voter (-) to find the nearest A or B supporter, adjusting votes one by one based on proximity.
  • With the Optimized Solution, we’d first compute the distance arrays, allowing us to quickly determine influence for each neutral voter based on pre-calculated distances.
• Expected Output: By the end of this process:
  • For each neutral voter, we can see if they are influenced by A, B, or remain neutral.
  • This results in a final count that determines whether A, B, or a Coalition wins.

These examples help illustrate how each approach works and lead to clear, predictable outcomes based on the rules and proximity calculations.

Conclusion and Key Takeaways

In this challenge, we explored how proximity and influence play a crucial role in determining the outcome, helping to strengthen our understanding of coding patterns for similar problems.

1. Recap of Key Concepts: Remember, proximity influence is an essential concept in many coding challenges. Understanding how to calculate and optimize this influence helps in solving a variety of similar problems efficiently.
2. Final Tips for Candidates: Practice both the Brute Force and Optimized approaches. Being comfortable with both will prepare you for variations of this problem, where efficiency or simplicity might be needed depending on the scenario.
3. Motivational Note: Tackling challenges like these builds strong foundational skills in programming logic and algorithm optimization. Each step you take in mastering these concepts brings you closer to becoming a more skilled and versatile problem solver. Keep practicing, and enjoy the journey of growth!