How to Explain LeetCode Solutions in Plain English for Interview Success

Originally published on LeetCopilot Blog

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Got the code right but struggled to explain your approach? Learn the exact framework for translating algorithms into clear, confident verbal explanations that impress interviewers.

The code works. You submit it. "Accepted."

But in your mock interview, when asked to explain your solution, you freeze. You stare at your code and mumble: "Um... so this loop... it like... goes through the array... and then... checks stuff..."

Your interviewer waits. Silence.

The problem: You solved it, but you can't translate your code into coherent English. And in real interviews, communication is just as important as correctness.

This guide teaches you a step-by-step framework for converting your LeetCode solutions into clear, confident verbal explanations that demonstrate both technical depth and communication skill.

TL;DR

• Interviews test two skills: solving the problem AND explaining your thinking clearly.
• Most candidates: Can code but struggle to verbalize their approach without rambling or getting lost in details.
• The framework: (1) State the problem in your own words, (2) Describe the high-level strategy, (3) Explain why it works, (4) Walk through a concrete example, (5) Analyze complexity.
• Common mistake: Narrating code line-by-line instead of explaining the core insight and algorithmic approach.
• Practice technique: Write your solution, then explain it out loud without looking at the code. Record yourself to catch filler words and unclear explanations.
• You'll learn: How to structure verbal explanations, what to emphasize, how to use examples effectively, and communication habits that signal confidence.

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Beginner-Friendly Explanations

Why Explaining is Harder Than Coding

When you code, you're having a conversation with the compiler. When you explain, you're having a conversation with a human who may or may not follow your logic.

Coding:

• Precise syntax
• Sequential execution
• Compiler catches errors

Explaining:

• Natural language (imprecise, ambiguous)
• Non-linear reasoning ("here's the idea, now let me show you an example, now back to the algorithm")
• Interviewer's understanding varies

Many strong coders struggle because they never practiced the translation layer between "what my code does" and "why my approach works."

The Two-Level Explanation Model

Think of explanations in two levels:

Level 1 - The Strategy (High-Level):

• What's the core idea?
• What pattern or technique are we using?
• Why does this approach solve the problem?

Example: "We'll use a sliding window to track the longest substring without repeating characters. As we expand the window, if we hit a duplicate, we shrink from the left until it's valid again."

Level 2 - The Mechanics (Implementation Details):

• How do we track state? (data structures)
• What's the loop structure?
• How do we handle edge cases?

Example: "We'll use a hash set to store characters in the current window. We have two pointers, left and right. Right expands the window, and if we find a duplicate, left shrinks it by removing characters from the set until the duplicate is gone."

Most beginners jump straight to Level 2 (implementation) without establishing Level 1 (strategy). This confuses the interviewer because they don't have the mental scaffold to understand the details.

Always start with strategy, then add mechanics.

What Interviewers Are Actually Listening For

When you explain your solution, interviewers assess:

1. Clarity: Can I follow your reasoning without getting lost?
2. Structure: Do you organize your thoughts logically?
3. Insight: Do you understand why your solution works, or did you just memorize a pattern?
4. Communication: Can you adapt your explanation if I look confused?

Understanding how to explain your thought process is a meta-skill that applies beyond just solution walkthroughs—it shapes how you approach the entire interview.

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Step-by-Step Learning Guidance

Step 1: Restate the Problem in Your Own Words

Before explaining your solution, reframe the problem to show you understand it:

Template:

"So we need to [goal], given [inputs]. The constraints are [notable limits]. Let me clarify: [edge case or ambiguity]."

Example:

"We need to find the longest substring without repeating characters, given a string. The string can be up to 10,000 characters. Just to clarify: does 'repeating' mean any duplicate, or consecutive duplicates?"

Why this works: It demonstrates comprehension and gives the interviewer a chance to correct misunderstandings before you dive into implementation.

Step 2: State Your High-Level Strategy First

Describe the approach in one to two sentences before touching implementation.

Bad (too detailed too fast):

"I'm going to use a hash set and two pointers, one at the start and one that moves right, and when I hit a duplicate I'll remove from the set..."

Good (strategic first):

"I'll use a sliding window approach. The idea is to expand a window to the right as long as all characters are unique, and shrink it from the left when we encounter a duplicate."

Template:

"I'll use [pattern/technique]. The core idea is [one-sentence strategy]."

This creates a mental anchor for the interviewer. Now they can follow along as you explain details.

Step 3: Explain Why Your Approach Works

This is the insight layer. Don't just say what you're doing—say why it's correct.

Example:

"This works because at any moment, the substring between left and right is guaranteed to have no duplicates. By shrinking from the left when we find a duplicate, we maintain that invariant while checking every possible valid substring."

Template:

"This works because [fundamental principle]. By doing [X], we ensure [correctness guarantee]."

This proves you're not just applying a memorized template—you understand the logic.

Step 4: Walk Through a Concrete Example

Use a small, clear example to illustrate your approach in action.

Problem: Longest Substring Without Repeating Characters

Input: "abcabcbb"

Walkthrough:

"Let's trace through 'abcabcbb'. Initially, both pointers are at index 0. We expand right: 'a', 'ab', 'abc'—all unique, so our max is 3. Then we hit the second 'a'. Now we have a duplicate. We shrink from the left: remove the first 'a', so the window is now 'bca'. We continue expanding right. When we hit the second 'b', we shrink again. And so on. The max we ever saw was 3, which is our answer."

Why this works: Concrete examples make abstract algorithms tangible. Interviewers can visualize what's happening.

Step 5: Mention Time and Space Complexity

Finish with Big O analysis to show you think about efficiency.

Template:

"The time complexity is O([expression]) because [reason]. The space complexity is O([expression]) because [reason]."

Example:

"Time complexity is O(n) because we visit each character at most twice—once when expanding right, once when shrinking left. Space complexity is O(min(n, m)) where m is the character set size, since that's the maximum size our hash set can grow to."

This signals you're thinking beyond just "does it work."

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Visualizable Example: Annotated Solution with Verbal Script

Problem: Two Sum

Code:

function twoSum(nums: number[], target: number): number[] {
  const map = new Map<number, number>();

  for (let i = 0; i < nums.length; i++) {
    const complement = target - nums[i];
    if (map.has(complement)) {
      return [map.get(complement)!, i];
    }
    map.set(nums[i], i);
  }

  return [];
}

Verbal Explanation Script:

[Restate Problem]

"We're looking for two numbers in an array that add up to a target, and we need to return their indices. The array is unsorted, and there's exactly one valid pair."

[High-Level Strategy]

"I'll use a hash map to achieve this in a single pass. The idea is to store each number and its index as we go, and for each new number, check if its complement (target minus current number) already exists in the map."

[Why It Works]

"This works because for any pair (a, b) that sums to the target, when we encounter 'b' in the array, 'a' will already be in our map from an earlier iteration. So we can find the pair in O(1) lookup time instead of checking every combination."

[Concrete Example]

"Let's say nums = [2, 7, 11, 15] and target = 9. Start with an empty map. First element is 2. Complement is 9 - 2 = 7. Map doesn't have 7 yet, so we add {2: 0} to the map. Next element is 7. Complement is 9 - 7 = 2. We check the map—yes, it has 2 at index 0. So we return [0, 1]."

[Complexity]

"Time complexity is O(n) because we make one pass through the array, and each lookup and insertion in the hash map is O(1). Space complexity is O(n) in the worst case if we store every element before finding the pair."

Key Insight: Notice the structure—problem → strategy → insight → example → complexity. This flow is easy to follow and covers all bases.

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Practical Preparation Strategies

Practice Out Loud, Not Just in Your Head

Exercise:

1. Solve a problem on LeetCode
2. Close your laptop
3. Explain your solution out loud as if to an interviewer
4. Record yourself (phone voice memo or video)
5. Listen back: Did you ramble? Use filler words? Skip the "why"?

Repeat until your explanation is smooth and concise.

Use the "Rubber Duck" Method

Explain your solution to an inanimate object (or a patient friend). If you can't make a rubber duck "understand" your logic, you don't understand it well enough.

Create a "Translation Cheat Sheet"

For common code patterns, write plain-English translations:

Code Pattern	Plain English Translation
for (let i = 0; i < n; i++)	"We iterate through each element"
if (map.has(key))	"We check if we've seen this value before"
left++; right--;	"We shrink the window from both ends"

This builds muscle memory for translating code to speech.

Study Editorial Explanations

Read LeetCode editorials or watch solution videos. Notice how they structure explanations:

• They start with the intuition
• They use analogies and examples
• They explain why brute force fails before showing the optimized approach

Mimic that structure in your own explanations.

Leverage Interview Mode Practice

Tools like LeetCopilot's Interview Mode simulate real interview scenarios where you're asked to explain your reasoning out loud. Practicing with adaptive feedback helps you refine your communication in a low-stakes environment.

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Common Mistakes to Avoid

Mistake 1: Narrating Code Line-by-Line

Bad: "So on line 1, I create a map. Then on line 2, I start a for loop. On line 3, I calculate the complement..."

Why it's bad: This is just reading code aloud. It doesn't explain the approach or insight.

Fix: Explain the algorithm conceptually first, then optionally reference specific code sections to illustrate.

Mistake 2: Using Jargon Without Explaining It

Bad: "I'm using a monotonic stack to maintain the invariant during traversal."

Why it's bad: If the interviewer doesn't know what a monotonic stack is, they're lost.

Fix: "I'm using a stack that stays in increasing order. Whenever we'd add something that breaks that order, we pop elements until the order is restored. This helps us track previous smaller elements efficiently."

Mistake 3: Skipping the "Why"

Bad: "I use a hash map here." [moves on]

Why it's bad: Interviewers want to know why you chose that data structure.

Fix: "I use a hash map because it gives us O(1) lookups, which lets us check if we've seen a number before without re-scanning the array."

Mistake 4: Not Checking for Understanding

If your interviewer looks confused, they probably are. Pause and ask: "Does that make sense so far? Should I clarify any part?"

This prevents you from rambling through a full explanation while the interviewer is stuck on step 1.

Mistake 5: Memorizing Scripts Instead of Understanding

If you memorize exact phrases for each pattern, you'll sound robotic and struggle with follow-up questions.

Fix: Understand the principles. Then you can explain flexibly, adapting to the interviewer's questions.

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FAQ

How do I avoid rambling during explanations?

Use the five-step structure: restate problem → strategy → why it works → example → complexity. If you follow this order, you'll stay organized and hit all key points without wandering.

What should I practice before focusing on verbal explanations?

First, make sure you can solve the problem. Then practice explaining it. Don't try to do both simultaneously at first, or you'll be overwhelmed. Solve, then explain—treat them as separate skills.

Is this concept important for interviews?

Absolutely. Many candidates fail interviews not because their solution is wrong, but because they can't explain it clearly. Interviewers are hiring teammates, not just coders—communication is critical.

Should I explain my solution before or after coding?

Ideally, explain your high-level approach before coding (gets interviewer buy-in), code it, then walk through the completed solution afterward with an example. This shows both planning and clarity.

How can I practice if I don't have a partner?

Record yourself explaining solutions out loud, then watch the recording. Or use AI-based mock interview tools that ask follow-up questions to simulate real dynamics.

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Conclusion

Writing working code is half the battle. Explaining it clearly is the other half.

The framework is simple: restate the problem, describe the strategy, explain why it works, walk through an example, and analyze complexity. This structure ensures you hit all the points interviewers care about without rambling or getting lost in syntax.

But knowing the framework isn't enough—you need reps. Solve a problem, then practice explaining it out loud. Record yourself. Notice where you stumble. Did you jump to implementation details too fast? Did you forget to explain the "why"? Did you use jargon without defining it?

Over time, you'll build a translation muscle: the ability to take a programmatic solution and convert it into a coherent, confident narrative. And when that happens, interviews shift from nerve-wracking interrogations to collaborative problem-solving sessions—which is exactly what they're supposed to be. That confidence, paired with clear reasoning, is what turns "you got the answer" into "we want to hire you."

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