November 04, 2025

Introduction

Coding interviews can feel like a high-stakes game. You’re given a tricky problem, a ticking clock, and an interviewer watching your every move. It’s easy to freeze up, get overwhelmed, and feel like you’re playing a guessing game.

But what if I told you that a successful interview isn’t about memorizing every single algorithm or data structure? What if it’s about following a predictable, step-by-step process?

In this post, I’ll break down the six key steps of a coding interview. Think of it as a playbook for success. We’ll go from reading the problem to cleaning up your code, so you’ll have a clear roadmap to follow the next time you’re in the hot seat.

Step 1: Read and repeat the problem (Out Loud!)

Before you even think about writing code, slow down and read the problem. Seriously, read the entire thing, and say it out loud if you can. This might feel a little silly, but it’s a critical first step. It forces you to process the information fully and gives your interviewer insight into your thought process.

Once you’ve read it, rephrase the problem in your own words. This is your chance to show the interviewer that you truly understand the core task. Don’t just parrot back the prompt. Instead, explain the goal and confirm all the key details:

Inputs and Outputs: What kind of data are you working with? Is it a string, an array of integers, or something else? What should your function return?

Constraints: Are there any limits you need to consider? For example, is the input array always sorted? Can it contain duplicates? Are the numbers always positive?

Edge Cases: What about the tricky, non-standard inputs? What if the input is empty or null? What if a number is zero or negative? Think of these as the exceptions that could break your code.

This is also a great time to chat with your interviewer. Ask questions about the context of the problem. For example, “Will this function be used on a massive dataset, or just a few hundred entries?” This helps you understand the scale and allows you to discuss potential performance trade-offs.

By taking the time to read, rephrase, and discuss, you’re not just understanding the problem; you’re building a foundation for a successful solution.

Step 2: Ask for examples

After you’ve discussed the problem, the next step is to define the details with examples. Don’t assume you can just jump to a solution. This is where you and the interviewer ensure you’re both on the exact same page before you write a single line of code.

Always start by asking the interviewer for an example. This is a great way to kick things off. They might have a specific scenario in mind, and it’s best to confirm it early. You could say, “Could you walk me through a simple example of the input and expected output?”

Once they’ve provided one, or if they prefer you to start, create an example yourself. Think of a straightforward test case and walk through it step-by-step. For a problem like, “Find the two numbers in an array that add up to a target value,” you could say: “Okay, let’s say the input array is [1, 5, 8, 11] and the target is 13. My output should be [2, 11] since they add up to the target.”

After you’ve shared your example, verify it with the interviewer. “Does that look right to you?” This simple question confirms your understanding and builds a collaborative atmosphere.

Now, it’s time to test your limits. Create one or two simple edge case examples that are easy to test. What if the input array is empty? What if it only has one number? What if the numbers are negative or zero? These are the cases that often break code, so thinking about them now is a smart move.

Finally, tackle a couple of complex examples. These should be more involved scenarios that test the tricky parts of the problem. For instance, what if there are duplicates in the array, or what if the target can be reached with multiple pairs of numbers? Thinking through these examples shows that you’re not just looking for a simple solution; you’re thinking about the problem in its entirety.

By going through these steps, you’ll have a clear, shared understanding of the problem, complete with testable examples that will guide you as you start to code.

Step 3: Start with a simple approach

You’ve got the problem, you’ve got the examples—now what? Don’t jump straight into the most clever, optimized solution you can think of. That’s a common mistake. Instead, start with the simplest, most straightforward, even “naive” solution you can come up with.

This approach shows your interviewer a few things. First, it proves you can solve the problem, even if it’s not the most efficient way. Second, it gives you a solid foundation to build upon.

Once you’ve explained the simple approach, be sure to mention its faults. For example, you could say, “My first thought is to use a nested loop to check every possible pair. The downside is that this would be pretty slow, with a time complexity of O(n²).” This shows that you understand the trade-offs and are thinking critically about your solution’s performance.

With those faults in mind, you can now explain a better, more performant solution. This is where you can show off your knowledge of data structures and algorithms. Maybe you can use a hash map to speed things up, or maybe you can sort the input to make the problem easier to solve.

Don’t just launch into the code, though. Draft your solution with simple annotations. Think of it like an outline. Write down the defined steps you’ll take, in plain English. For example:

1. Create an empty hash map.
2. Loop through the input array.
3. For each number, check if the “complement” is in the hash map.
4. If it is, you’ve found your pair. If not, add the number and its index to the map.

Finally, verify with the interviewer whether your approach is what they’re looking for. You can simply ask, “Does this high-level approach sound good to you?” This ensures you’re on the right track before you invest time writing the code. It’s a great way to collaborate and avoid any major missteps.

Step 4: It’s Time to Code!

You’ve read the problem, nailed down the examples, and outlined your approach. Now, it’s finally time to write some code. But don’t just jump in and start typing. Even at this stage, a structured approach is key.

Start by setting up your solution with a descriptive class and function name. Instead of Solution or Solve, use something that tells you what it does. For example, if you’re writing a function to find the maximum number in an array, call it FindMaxInArray or LargestNumberFinder. This simple step shows the interviewer that you write clean, readable code from the get-go.

Next, focus on short but meaningful variable names. This is a balancing act. You don’t want single-letter variables like x and y that make your code impossible to read later. But you also don’t want overly long names like array_of_integers_that_need_to_be_searched. A good middle ground is something like numbers, count, or target.

As you write, remember that good code is modular. If you find yourself writing a block of code that handles a repetitive, unclear, or complex task, move it to a separate helper function. This makes your main function cleaner and easier to read. It also lets you focus on one small part of the problem at a time. Your interviewer will appreciate seeing a well-organized solution rather than one giant block of code.

As you type, keep talking! Walk through your logic as you implement it. This allows your interviewer to follow along and provides a chance for them to offer guidance if you start to go off track.

Step 5: Test Your Code

You’ve finally written the code. You’re almost there! But don’t celebrate just yet. The next crucial step is to test your solution. This part of the interview isn’t just about showing that your code works; it’s about demonstrating your attention to detail and your ability to debug.

First, test the solution, not the idea. You’ve already talked through the logic, but now it’s time to see if your code actually implements that logic correctly. The best way to do this is to use the examples you discussed earlier. If you can, create quick tests using print() or console.log() statements to check the different inputs and output of your solution. This is a simple but effective way to ensure everything works as expected.

Sometimes, you won’t have the ability to run your code. No problem. This is where you can do a manual walkthrough of your algorithm. You can create a simple table on the whiteboard or in a shared document to track the state of your variables as you “run” through the code with an example input. For each line of code, you’ll update the values in your table. This shows your interviewer exactly how your code would execute and helps you spot any logical errors.

As you test, you’re bound to find a few issues. Don’t panic! Finding and fixing bugs is a normal part of the process. Make a note of any bugs you find and then fix them. Talk through your thought process as you do this. This is a valuable opportunity to show your interviewer how you think critically and adapt to challenges.

By taking the time to test your code, you’re proving that you’re not just a coder—you’re a thorough and reliable problem-solver.

Step 6: Optimize and Clean Up

You’ve solved the problem and your code works. Congratulations! But the interview isn’t quite over yet. The final, and arguably most important, step is to optimize and polish your solution. This is your chance to show the interviewer that you’re a professional, not just someone who can get a basic solution to work.

First, calculate the time and space complexity of your code. This is mandatory. You should know exactly how your algorithm scales. Explain your thinking to the interviewer. For example, you might say, “My current solution has a time complexity of O(n) because I’m iterating through the array once. The space complexity is O(n) as well, because I’m using a hash map to store the numbers.” Being able to articulate this shows a deep understanding of computer science fundamentals.

Next, it’s time to remove unnecessary variables or code and remove duplications. Look for any variables you declared but didn’t use. Look for any repeated blocks of code that could be simplified into a helper function. This isn’t just about making your code shorter—it’s about making it more readable and maintainable.

Finally, search for and remove any bottlenecks. A bottleneck is a part of your code that is slowing the whole thing down. Maybe you’re doing a redundant calculation inside a loop, or maybe you’re using a less efficient data structure than you could be. This is where your understanding of complexity comes into play. If you see a part of your code that’s slowing it down, discuss it with the interviewer and explain how you’d fix it.

By taking the time to optimize, you’re showing that you think about performance and efficiency, not just getting to a working solution. This is what separates a good developer from a great one.

Conclusion

So there you have it—a clear, step-by-step guide to nailing your next coding interview. It’s about more than just knowing an algorithm; it’s about showcasing a structured, professional approach to problem-solving.

Remember, the goal isn’t just to find the right answer. It’s to show your interviewer how you think, communicate, and handle pressure. By breaking down the problem, collaborating on a plan, and building your solution piece by piece, you’re proving that you’re a thorough, thoughtful, and effective developer.

So, the next time you walk into that interview room, take a deep breath and follow these steps.

You’ve got this!