Algorithm Solving Problems On Platforms Like Leetcode Hackerrank Codeforces Complete Guide

Introduction to Algorithm Problem Solving on Platforms

Algorithm-solving platforms like LeetCode, HackerRank, and Codeforces provide a vast array of problems ranging from simple to complex to help you improve your coding and problem-solving skills. Here, we cover the basics and guide you through solving your first algorithm problem step by step.

Step 1: Choose Your Language

Select the programming language you are most comfortable with or want to improve. Most platforms support multiple languages including C++, Java, Python, JavaScript, etc.

Step 2: Understand the Problem Statement

Each problem will come with a detailed description. Spend some time understanding what the problem is asking for. Identify the input and expected output and any constraints.

Step 3: Plan Your Solution

Before you start coding, think about how to solve the problem. This could involve brainstorming multiple approaches and choosing the most efficient one based on the constraints.

Step 4: Write Code

Implement your solution in the code editor provided by the platform.

Step 5: Test Your Code

Run your code with the sample input provided in the problem statement to see if it produces the correct output. Also, come up with your own test cases to ensure the robustness of your solution.

Step 6: Submit Your Code

Once you're confident in your solution, submit it using the platform's submission feature.

Step 7: Analyze Feedback

If your solution is incorrect, carefully read the platform's feedback (like a Time Limit Exceeded error or a wrong answer) to debug your code. If it is accepted, consider trying to optimize your solution further (e.g., improving time or space complexity).

Example Problem: Two Sum (LeetCode)

Problem Statement

Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target. You may assume that each input would have exactly one solution, and you may not use the same element twice. You can return the answer in any order.

Constraints:

• $2 \le \text{nums.length} \le 10^{4}$
• $-10^{9} \le \text{nums[i]}, \text{target} \le 10^{9}$
• Only one valid answer exists.

Example

Input: nums = [2, 7, 11, 15], target = 9 Output: [0, 1] (Because nums[0] + nums[1] == 9)

Plan

We can use a hash map (dictionary) to store each number and its index as we iterate through the array. For each number, we check if the complement (target - number) already exists in the hash map. If it does, we return the indices of the number and its complement.

Code

Here's a Python implementation of the plan:

def two_sum(nums, target):
    num_to_index = {}
    
    for index, num in enumerate(nums):
        complement = target - num
        if complement in num_to_index:
            return [num_to_index[complement], index]
        num_to_index[num] = index

# Example usage
nums = [2, 7, 11, 15]
target = 9
print(two_sum(nums, target))  # Output: [0, 1]

Testing

Let's test the function with the example provided in the problem statement.

# Test case 1
print(two_sum([2, 7, 11, 15], 9))  # Output: [0, 1]

# Test case 2
print(two_sum([3, 2, 4], 6))  # Output: [1, 2]

# Test case 3
print(two_sum([3, 3], 6))  # Output: [0, 1]

Submission

Copy the code into the online editor on LeetCode, and click the "Submit" button to verify your solution.

Optimization

The time complexity of this solution is O(n) and the space complexity is also O(n), which is efficient given the problem constraints.

Example Problem: Simple Array Sum (HackerRank)

Problem Statement

Given an array of integers, find the sum of its elements.

Constraints:

• $1 \le \text{ar.length} \le 1000$
• $0 \le \text{ar[i]} \le 1000$

Example

Input: ar = [1, 2, 3] Output: 6 (Because 1 + 2 + 3 = 6)

Plan

We can iterate through the array and maintain a running sum of all elements.

Code

Here's a Python implementation of the plan:

def simple_array_sum(ar):
    total = 0
    for num in ar:
        total += num
    return total

# Example usage
ar = [1, 2, 3]
print(simple_array_sum(ar))  # Output: 6

Testing

Let's test the function with the example provided in the problem statement.

# Test case 1
ar = [1, 2, 3]
print(simple_array_sum(ar))  # Output: 6

# Test case 2
ar = [1000] * 1000
print(simple_array_sum(ar))  # Output: 1000000

# Test case 3
ar = [5, 10, 15]
print(simple_array_sum(ar))  # Output: 30

Submission

Copy the code into the online editor on HackerRank and click the "Submit" button to verify your solution.

Example Problem: A + B (Codeforces)

Problem Statement

Given two integers, print their sum.

Constraints:

• $-1000 \le a, b \le 1000$

Example

Input: a = 3, b = 4 Output: 7 (Because 3 + 4 = 7)

Plan

We can simply read the integers from input, calculate their sum, and print the result.

Code

Here's a Python implementation of the plan:

import sys

def main():
    input = sys.stdin.read().split()
    a = int(input[0])
    b = int(input[1])
    print(a + b)

if __name__ == "__main__":
    main()

Testing

Let's test the function with the example provided in the problem statement.

To simulate input:

import sys
from io import StringIO

def test_main():
    sys.stdin = StringIO("3 4\n")
    sys.stdout = StringIO()
    main()
    output = sys.stdout.getvalue().strip()
    assert output == "7", f"Expected '7', got '{output}'"

# Run the test
test_main()

Submission

Copy the code into the online editor on Codeforces and click the "Submit" button to verify your solution.

Conclusion