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Array Sum: Buggy Code in JavaScript (Time Complexity: O(n))


Inside the code editor we've tried to write a function that takes an array nums as argument and prints to the console the sum of all numbers in that list.

So when we called printSum([1, 2, 3]), we expected our code to print:

6

because 1 + 2 + 3 = 6. But it seems like we made some mistakes because when we run our code, it prints:

1
2
3

Assignment:

Your task is to fix our function such that it correctly computes and prints the desired sum.

Understanding the Problem

The core challenge here is to correctly sum the elements of an array and print the result. This is a common task in many applications, such as calculating totals, averages, or other aggregate values. A common pitfall is misunderstanding how to accumulate the sum and print the result correctly.

Approach

To solve this problem, we need to iterate through the array, accumulate the sum of its elements, and then print the final sum. Let's break down the steps:

  1. Initialize a variable to store the sum.
  2. Iterate through each element of the array.
  3. Add each element to the sum variable.
  4. After the loop, print the sum.

Initially, a naive approach might involve printing each element during the iteration, which is incorrect as it doesn't accumulate the sum. Instead, we need to ensure we only print the final accumulated sum.

Algorithm

Here is a step-by-step breakdown of the algorithm:

  1. Initialize a variable sum to 0.
  2. Loop through each element num in the array nums.
  3. Add num to sum.
  4. After the loop, print the value of sum.

Code Implementation

function printSum(nums) {
  // Initialize sum to 0
  let sum = 0;
  
  // Iterate through each number in the array
  for (let i = 0; i < nums.length; i++) {
    // Add the current number to the sum
    sum += nums[i];
  }
  
  // Print the final sum
  console.log(sum);
}

// Example usage
printSum([1, 2, 3]); // Expected output: 6

Complexity Analysis

The time complexity of this solution is O(n), where n is the number of elements in the array. This is because we iterate through the array once. The space complexity is O(1) as we only use a single variable to store the sum.

Edge Cases

Consider the following edge cases:

  • An empty array: The sum should be 0.
  • An array with one element: The sum should be the element itself.
  • An array with negative numbers: The sum should correctly account for negative values.

Examples:

printSum([]); // Expected output: 0
printSum([5]); // Expected output: 5
printSum([-1, -2, -3]); // Expected output: -6

Testing

To test the solution comprehensively, consider using a variety of test cases:

  • Simple cases with small arrays.
  • Edge cases as mentioned above.
  • Large arrays to ensure performance.

Example test cases:

printSum([1, 2, 3]); // Expected output: 6
printSum([10, 20, 30, 40]); // Expected output: 100
printSum([-5, 5, -10, 10]); // Expected output: 0

Thinking and Problem-Solving Tips

When approaching such problems, consider the following tips:

  • Break down the problem into smaller steps.
  • Think about edge cases and how your solution handles them.
  • Write pseudo-code before actual implementation.
  • Test your solution with a variety of inputs.

To improve problem-solving skills, practice regularly on coding challenge platforms and study different algorithms and data structures.

Conclusion

In this post, we discussed how to fix a buggy function to correctly compute and print the sum of an array. We covered the problem definition, approach, algorithm, code implementation, complexity analysis, edge cases, and testing. Understanding and solving such problems is crucial for developing strong programming skills.

Additional Resources

For further reading and practice, consider the following resources: