Real-world examples of examples of infinite loop examples in modern software

Classic examples of infinite loop examples in everyday code

When people talk about examples of infinite loop examples, they usually picture the most basic pattern: a loop whose exit condition is never met. That’s the right starting point, but it’s only part of the story.

Consider a simple while (true) loop in C:

#include <stdio.h>

int main(void) {
    while (1) {
        printf("Processing...\n");
    }
    return 0;
}

This is the textbook example of an infinite loop: the condition is always true, and there’s no break. On a modern CPU, this will peg a core at 100% until the process is killed. In production, that shows up as high CPU alerts, throttling in containers, or even autoscaling storms in cloud environments.

A slightly more subtle example of an infinite loop appears when the condition depends on a variable that never changes inside the loop:

count = 0

while count < 10:
    print("Still running...")
#    # Forgot to increment count

This looks like a finite loop at a glance, but because count never changes, count < 10 is always true. These are the best examples of bugs that slip through code review because the intent is correct, but one line is missing.

Real examples of examples of infinite loop examples in web frontends

Frontend JavaScript gives us some of the most painful real examples of infinite loops because they freeze the browser and destroy user experience.

One of the most common patterns: re-render loops in frameworks like React. Imagine this simplified React component:

function PriceWidget({ price }) {
  const [discount, setDiscount] = useState(0);

  if (price > 100 && discount === 0) {
    setDiscount(10);
  }

  return <div>Final: {price - discount}</div>;
}

On paper, it looks harmless. In practice, calling setDiscount during render triggers another render, which calls setDiscount again, and so on. That’s an infinite loop of renders rather than a traditional while loop, but the effect is the same: the tab locks up, the fan spins, and Chrome’s task manager shows the page eating CPU.

In modern SPAs, these examples of infinite loop examples often involve:

• State updates in render functions or computed properties
• useEffect hooks with incorrect dependency arrays that re-trigger themselves
• Recursive component trees where the base case is never reached

These aren’t academic problems. Browser vendors like Google regularly publish performance guidance warning against patterns that lead to runaway re-rendering and layout thrashing (see, for example, the performance docs in web.dev).

Backend and API: examples include runaway polling loops

On the backend, infinite loops often show up as background workers or API handlers that never exit. Here’s a very real example of a bug in a Node.js service that polls another microservice:

async function pollStatus(id) {
  while (true) {
    const res = await fetch(`/status/${id}`);
    const data = await res.json();

    if (data.state === 'done') {
      return data;
    }

    // Forgot to wait before the next poll
  }
}

The intention is to poll until the job is done, but without a delay or timeout, this becomes a tight infinite loop of HTTP requests. In production, this pattern can:

• Hammer downstream services with thousands of requests per second
• Trigger rate limiting or bans from third-party APIs
• Inflate cloud bills because autoscaling responds to the artificial load

Better patterns in 2024–2025 include exponential backoff with jitter and hard caps on retries, as recommended by large cloud providers like AWS and Google Cloud (docs.aws.amazon.com and cloud.google.com).

Concurrency: real examples of infinite loop examples from race conditions

Some of the nastiest real examples of infinite loop examples come from concurrency bugs. The loop condition changes, but not the way you think.

Take a simple producer–consumer pattern in Java:

class QueueWorker implements Runnable {
    private volatile boolean running = true;

    @Override
    public void run() {
        while (running) {
            if (!queue.isEmpty()) {
                process(queue.poll());
            }
        }
    }

    public void stop() {
        running = false;
    }
}

At first glance, this looks fine: the loop runs while running is true. But in real systems:

• The worker might be blocked in process() and never checks running again
• There’s no sleep or blocking read, so it busy-waits when the queue is empty
• If stop() is never called (or called on the wrong instance), the loop persists forever

Monitoring tools like top, htop, or APM dashboards (Datadog, New Relic, etc.) often flag these as threads that run hot even when the system is idle. These are best examples of infinite loops that only appear under certain load or deployment conditions.

Logic bugs: off-by-one and floating-point examples include hidden infinite loops

Not all infinite loops are obvious. Some arise from subtle logic errors.

Off-by-one in counters

A classic example of this in C:

int i = 0;

while (i != 10) {
    // ... work ...
    i += 2;
}

Because i goes 0, 2, 4, 6, 8, 10, 12, it will skip right over the value 10 in a way that never satisfies i != 10 becoming false. In practice, i will never be exactly 10 when the condition is checked, so the loop never exits.

Floating-point comparisons

Another subtle example of infinite loop behavior appears with floating-point math:

x = 0.0

while x != 1.0:
    x += 0.1

Due to floating-point precision, x may never be exactly 1.0. It might be 0.999999999 or 1.000000001, so the condition stays true. This kind of bug is documented in many university CS courses and references like MIT OpenCourseWare (ocw.mit.edu), because it’s such a common trap.

Event loops and async: modern examples of examples of infinite loop examples

In 2024–2025, a lot of real-world examples of infinite loop examples happen in event-driven systems: Node.js, Python’s asyncio, or message-driven microservices.

Consider an asyncio task in Python that listens to a queue:

import asyncio

async def worker(queue):
    while True:
        item = await queue.get()
        try:
            await process(item)
        finally:
            queue.task_done()

This is an intentional infinite loop: it’s expected to run for the lifetime of the service. The problem comes when:

• There is no shutdown signal, so the loop prevents clean application exit
• Error handling restarts the loop endlessly on unrecoverable exceptions
• Resource leaks inside process() accumulate over hours or days

These patterns don’t always crash immediately. Instead, they show up as memory bloat, growing latency, or slow restarts. Modern observability practices—metrics, tracing, structured logs—are often the only way to catch these real examples of loops that never die.

User input and UI: examples include validation loops that never end

Desktop and mobile apps also offer examples of examples of infinite loop examples that feel different to users. Instead of a crash, they see a spinner that never stops.

Imagine a login form that keeps re-validating input on each keystroke and re-rendering the entire form tree. With poorly written reactive bindings, you can easily create a feedback loop:

• User types a character
• Validation logic updates state
• State change triggers full re-render
• Re-render fires validation again

On low-power devices, this can feel like an infinite loop even if the code technically terminates. In performance testing and UX research, these are increasingly treated like runtime errors because they block the user from completing tasks.

Organizations that do serious usability testing, including universities and health systems, often publish guidelines warning against such patterns in critical apps like patient portals or educational platforms (see, for example, accessibility and usability guidance at nngroup.com and many .edu usability labs).

Detecting and debugging infinite loops in 2024–2025

Modern toolchains make it easier to catch examples of infinite loop examples before users ever see them.

In development:

• IDEs like VS Code and IntelliJ highlight suspicious loops, especially while (true) without a break
• Linters (ESLint, Pylint, etc.) flag patterns like for (;;) with no exit condition
• Unit tests with timeouts catch loops that never return

In production:

• APM tools show endpoints or background jobs with abnormally long execution times
• CPU and memory dashboards highlight services that never go idle
• Health checks and readiness probes in container orchestrators (Kubernetes, ECS) restart pods that get stuck

Research from large-scale systems—think Google’s SRE books or academic work from places like Stanford and Berkeley—shows that many incidents still trace back to logic loops that weren’t properly bounded.

Preventing your own examples of infinite loop examples

The best way to avoid contributing your own examples of infinite loop examples is to design loops defensively:

• Always include a clear termination condition, even for long-running workers
• Add maximum iteration counts or timeouts around loops that depend on external systems
• Avoid tight polling; prefer event-driven callbacks, message queues, or backoff strategies
• Treat while (true) as a code smell that requires justification and documentation
• Use feature flags and canary releases so a hidden infinite loop doesn’t hit all users at once

These practices aren’t about perfection. They’re about acknowledging that infinite loops are a normal part of software development—and building guardrails so they’re caught early.

FAQ: common questions and examples

Q: What are some common examples of infinite loops in beginner code?
Beginner-friendly examples include forgetting to update the loop variable (i++ or count += 1), using while (true) without a break, and comparing floating-point numbers for exact equality in the loop condition. These examples of bugs show up constantly in intro CS courses.

Q: Can an infinite loop be intentional and still safe?
Yes. A good example of this is a server process that runs an event loop indefinitely, such as a web server or message consumer. The loop is intentional, but it’s considered safe only if it has proper shutdown hooks, error handling, and resource management.

Q: How do I detect an example of an infinite loop in a large codebase?
Look for functions that never return, endpoints with extremely long response times, or threads that are always running hot. Profilers, logging with timestamps, and timeouts around calls are practical ways to spot real examples of loops that never exit.

Q: Are infinite loops always a runtime error?
Not always. Some infinite loops are part of the design, like GUI event loops. They become runtime errors when they prevent progress, starve other tasks, or cause resource exhaustion. In that sense, the same pattern can be either a valid control structure or one of the worst examples of infinite loop examples in your system.

Q: What are the best examples of tools to prevent infinite loops?
Static analyzers, linters, and test frameworks with timeouts are among the best examples of preventive tools. They don’t catch everything, but combined with code review and observability in production, they significantly reduce the chance that your users will be the ones discovering your infinite loops.