Overcomplicating Solutions: The Hidden Pitfall in JavaScript Coding Interviews

Outcome-first intro

You want to walk out of a technical interview having demonstrated clarity, confidence, and correctness. You’ll leave with that if you stop overcomplicating problems and start showing simple, well-justified solutions - plus the thought process behind them. One clear idea, clearly explained, wins more interviews than a clever web of optimizations that no one understands.

Why overcomplication happens (and why it hurts)

You’re nervous. The interviewer is watching. Time is ticking. Under pressure we tend to do two things that push us toward complexity:

We try to anticipate every corner case before writing a single line. Good intention. Bad timing.
We want to impress by showing advanced techniques, even when a basic approach is perfectly acceptable.

Both behaviors lead to longer, harder-to-follow explanations and higher risk of bugs. Interviewers rarely judge only on exotic tricks. They judge on problem understanding, correctness, communication, and sound trade-offs. The clearest solution that works and is well-explained usually wins.

The simple-first strategy (what to do, in order)

Clarify the problem quickly. Ask questions about input size, allowed data types, edge cases, and what “correct” means. This prevents building solutions for the wrong requirements.
State a brute-force approach in one sentence. Then give its time and space complexity. That shows you understand the problem baseline.
Propose a simple optimized solution only if necessary. Explain why it’s better and what trade-offs you accept.
Implement the simplest correct approach clearly and test it on examples. Optimize only if the interviewer asks or if constraints demand it.

This sequence demonstrates both breadth (you see options) and depth (you can implement clearly). It prevents you from diving head-first into unnecessary complexity.

Example: Two-sum (a classic where candidates overcomplicate)

Problem: Given an array of integers and a target, return indices of two numbers that add up to the target. You may assume exactly one solution exists.

A typical overcomplicated route is to try sorting with index-tracking, or to maintain multiple passes with auxiliary structures for every possible edge case. Those routes increase error surface and explanation length.

A clean, common solution is a single-pass hash map. Say it aloud, then implement it.

// Simple, single-pass solution: O(n) time, O(n) space
function twoSum(nums, target) {
  const map = new Map(); // value -> index
  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 null; // if no solution found
}

// Example
console.log(twoSum([2, 7, 11, 15], 9)); // [0, 1]

Why this is good in an interview:

It’s easy to explain in two sentences.
Complexity analysis is straightforward.
It handles the most common constraints without elaborate edge-case plumbing.

Only consider sorting-based or other approaches if you need less memory and the interviewer explicitly pushes time constraints or asks to reduce space.

How to communicate your thought process (exact phrases and structure)

Interviewers are as interested in what you say as in what you type. Use short, deliberate statements that give context before diving into code.

Start: “I’ll restate the problem to check I’ve got it: … Is that right?”
Outline: “A brute-force way is X with O(…) complexity. A better approach is Y using a Map in O(n) time. I’ll implement Y unless you prefer I start with the brute-force first.”
While coding: “Now I’ll write the loop that checks for complements. After that I’ll add a quick test.” Say what each block does in one line.
When you encounter a tricky bit: “I see two ways to handle this: A or B. A is simpler and handles most cases; B handles X but adds complexity. Which would you like me to do?”
At the end: “This solution is O(n) time and O(n) space. If we needed O(1) space, we could do … but we’d trade off correctness or index tracking.”

These short scaffolding sentences keep the interviewer aligned with your plan and reduce surprises.

Quick checklist to avoid overcomplication (use in the interview)

Did I restate the problem? Yes/No.
Did I ask about constraints (n, value range, data types)?
Can I propose a brute-force solution briefly? Yes/No.
Can I propose a simple optimized solution next? Yes/No.
Will this solution be accepted under constraints? If unsure, ask.
Implement the simplest working solution first, test, then optimize if needed.

Using this checklist out loud shows process discipline and prevents unnecessary detours.

Common interview traps that sound like “depth” but are actually noise

Premature micro-optimizations (e.g., rewrite loops to tweak constant factors) - skip unless the interviewer asks.
Over-indexing on theoretical worst-case variations that contradict given constraints - clarify constraints first.
Building an elaborate class or pattern when a small function suffices - design matters, but simplicity trumps structure during timed whiteboard/online coding.

When complexity is justified

Complex solutions are not wrong. They are justified when:

Problem constraints force it (huge n, strict memory limits).
The interviewer explicitly asks for advanced optimizations.
You need advanced data structures to meet correctness (e.g., balanced trees, graphs with special properties).

But even then, present the simple approach first, then explain why you must escalate complexity. That ordering demonstrates judgment.

Practical drills to practice simplicity

Timed one-problem sprints: 20 minutes. Clarify, pick simple solution, implement, test.
Pair-programming with a friend who interrupts if you start over-engineering.
Record yourself explaining a brute-force and optimized plan in 1–2 minutes. Tighten until it sounds crisp.

Resources

KISS principle (short overview): https://en.wikipedia.org/wiki/KISS_principle
MDN Map and Set docs (useful for many JS interview solutions): https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Map
A practical interview prep resource: https://leetcode.com
Books that emphasize clarity and design: “Clean Code” by Robert C. Martin (overview): https://www.oreilly.com/library/view/clean-code/9780136083238/

Final note

The single most important thing you can show in an interview is clear thinking. Clear thinking looks like a simple, correct solution first - and an articulate explanation of why you would complicate it only if necessary.