How to solve algorithms

1. Understand the Problem Completely

Before writing any code, make sure you fully understand the problem.

Ask yourself:

• What is the input?
• What should the output look like?
• Are there any constraints?
• Are edge cases possible?

Example problem:

Given an array of numbers, return the largest number in the array.

Example input:

[4, 9, 1, 7, 3]

Expected output:

9

It might seem obvious, but many algorithm mistakes happen simply because the problem was misunderstood.

2. Work Through an Example Manually

Take a small example and solve it by hand.

Using the example array:

[4, 9, 1, 7, 3]

You might think through it like this:

1. Start with the first number.
2. Compare it with the next number.
3. Keep track of the biggest number seen so far.

Your thought process becomes the foundation of the algorithm.

3. Identify the Pattern

Most algorithm problems fall into common categories:

• Arrays / Iteration
• Hash maps
• Two pointers
• Recursion
• Sorting
• Binary search
• Dynamic programming

For the “largest number in an array” problem, the pattern is simple iteration.

4. Write Pseudocode First

Before writing real code, outline the logic in plain language.

Example pseudocode:

set max to first number in array

for each n

    if number > max: 

        update max

return max

Pseudocode helps prevent getting stuck on syntax and keeps you focused on the algorithm itself.

5. Translate the Logic Into Code

Here’s what the algorithm might look like in JavaScript:

function findLargest(arr) {
  let max = arr[0]

  for (let i = 1; i < arr.length; i++) {
    if (arr[i] > max) {
      max = arr[i]
    }
  }

  return max
}

This solution works because it systematically compares each value in the array.

6. Test Edge Cases

Good algorithm solutions account for unusual inputs.

Examples:

• Empty array
• One-element array
• Negative numbers
• Very large inputs

Example edge case:

[]

You might want to add logic to handle that case.

7. Analyze Time Complexity

Understanding how efficient your algorithm is is an important part of solving problems.

For the example above:

• The loop goes through the array once.
• That makes the time complexity:

O(n)

Which is optimal for this type of problem.

8. Practice Consistently

The biggest secret to getting better at algorithms is simple:

Practice regularly.

Even experienced developers struggle with algorithm problems if they haven't practiced in a while.

Some good platforms include:

• LeetCode
• HackerRank
• CodeSignal
• Exercism

Over time you'll start recognizing patterns and solving problems much faster.

Final Thoughts

Algorithms can feel intimidating at first, but they become much easier once you follow a consistent process:

1. Understand the problem
2. Work through an example
3. Identify the pattern
4. Write pseudocode
5. Translate into code
6. Test edge cases
7. Analyze complexity

If you stick to this framework, algorithm problems stop feeling like random puzzles and start feeling like structured challenges you can solve step by step.

And honestly, that’s when algorithms start becoming fun.