Originally published on LeetCopilot Blog

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Runtime errors feel random when you’re new to LeetCode. This guide shows a repeatable debugging routine, visual walk-throughs, and common traps so you can fix crashes without guessing.

Runtime errors show up as red text and vague messages. Beginners often change code at random, only to trigger new failures. This article gives you a calm, repeatable routine to isolate the real cause and fix it quickly.

What Runtime Errors Usually Mean

• Accessing something that doesn’t exist (array index, null pointer).
• Mismanaging loops (off-by-one, infinite loops, or early returns).
• Breaking problem constraints (wrong assumptions about input size or ordering).
• Time/memory blowups from hidden O(n²) sections.

Visual mental model

Think of your program as a timeline: Input → Parse → Transform → Output. A runtime error is a break in that chain. Find the exact link that snapped.

Step-by-Step Debugging Routine

Step 1: Reproduce on the smallest case

Copy the failing test input and shrink it until the crash still happens. Your goal is a 3–6 element input you can trace mentally.

Step 2: Trace state changes

Add temporary prints or use a debugger to capture values at each phase: parse, loop entry, loop exit, and before return.

Step 3: Validate indices and bounds

• Check every index math, especially i + 1 and mid calculations.
• For pointer-based problems, confirm both pointers stay within [0, n - 1].

Step 4: Confirm invariants

State the rule that must always be true (e.g., "window covers valid range" or "stack top is the last open bracket"). Log when the invariant is updated.

Step 5: Apply a focused fix

Only change the code that violates the invariant. Avoid rewriting the whole function.

Conceptual Diagram: Shrinking a Failing Case

Original failing input: [2, 7, 11, 15], target=9
↓ remove noise
Test: [2, 7], target=9
↓ trace
Step 1: i=0, j=1 → sum=9 (works) → bug disappears
↓ adjust
Add duplicate: [2, 2, 7], target=9 → reveals off-by-one in pointer increment

Preparation Strategies That Prevent Crashes

• Add guard rails early: Null/empty checks before loops.
• Design invariant statements: Write them above your loop before coding.
• Use layered tests: Start with the smallest valid input, then add edge cases.
• Leverage supportive tools: Hints from platforms like LeetCopilot can point to the exact line failing without giving away the full solution, saving time.

Common Mistakes to Avoid

• Panic refactors: Rewriting the entire function instead of fixing the faulty line.
• Ignoring input guarantees: Forgetting the array might be unsorted or contain negatives.
• Silent catches: Swallowing exceptions and hiding the real stack trace.
• Skipping baseline tests: Never confirming that the simplest case works.

Beginner-Friendly Code Example

Here’s a minimal wrapper that catches and logs the exact phase where a crash occurs.

function safeRun(fn: () => number) {
try {
return fn();
} catch (err) {
console.error("Crash in transformation phase", err);
throw err; // rethrow so you still see the stack
}
}

// Usage
safeRun(() => {
const arr = [1, 2];
return arr[3]!; // deliberate crash
});

Use a wrapper like this while debugging to keep error context visible, then remove it when your logic stabilizes.

FAQs

How do I know the bug is fixed?

Rerun the reduced failing case first, then the original case, then a new edge case to confirm the invariant holds.

What should I practice before tackling tough bugs?

Get comfortable tracing loops and pointer movements on paper. It speeds up real debugging sessions.

Are runtime errors common in interviews?

Yes, especially off-by-one and null/empty cases. Interviewers value how you investigate them calmly.

How do I avoid chasing phantom bugs?

Change one line at a time and re-run the smallest failing input after each tweak.

Internal Links for Structured Practice

• How to Analyze LeetCode Constraints Before Coding: A Beginner Playbook
• Sliding Window Intuition for Absolute Beginners: A Step-by-Step Guide

Conclusion

Debugging LeetCode runtime errors gets easier when you follow a stable routine: shrink the failing case, trace state, protect boundaries, and fix only the broken invariant. With deliberate practice and calm iteration, crashes turn into quick learning moments instead of roadblocks.

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