Is it expensive to use try-catch blocks even if an exception is never thrown?

Behind the scenes: JVM optimizations

Try-catch blocks can potentially hinder certain JVM optimizations, such as common subexpression elimination. However, modern JVMs are designed to minimize these kinds of effects. Regardless, the Just-In-Time (JIT) compiler could find exception handling constructs more challenging to optimize compared to their bytecode counterparts.

However, this impact on method's execution order and optimization approach is usually small. The JIT compiler, the ambitious multitasker that it is, manages to perform resourceful optimizations, while always adhering to Java's execution order guarantees.

Loops vs. line-by-line code: Performance hit showdown

Exception handling impacts vary depending on your code's architecture. If you've set a party of exceptions inside a tight loop, that whimsical choice could result in a performance hangover. However, straight-line code, the good kid who reserves exceptions for once-in-a-blue-moon events, experiences a milder impact.

Check out the straight-line code in action here:

try {
  // Just a fraction of our code's day, move along
  int quotient = numerator / denominator;
} catch (ArithmeticException ae) {
  // "Zero fun at parties," says ArithmeticException, rarely gets a word in
  quotient = altMethod();
}
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And here's the impact of inviting exceptions to our tight-loop party:

for (int i = 0; i < LARGE_NUMBER; i++) {
  try {
    // Living on the edge, might trip on the rug
    process(inputArray[i]);
  } catch (ProcessPartyFoulException ppfe) {
    // The party police are watching
    handleException(ppfe);
  }
}


Is the try block really free?

Calling a try block 'free' in performance terms has become a catchphrase among experts. The JVM treats the try block like it would any normal code as long as no exception makes an appearance.

However, the costs attributed to setting up the potential stack party for a guest appearance from an exception are minor.

Benchmarking: Measure twice, code once

To test these theories, let's invite OpenJDK JMH, the official benchmarking tool for Java, to the party. It's the perfect candidate to measure the true performance impact of try-catch blocks in your situation—no hearsay, just hard data.

Benchmarking is like the party photo gallery of our code. Once we've captured enough snapshots, we can use tools like Joshua Bloch's "Effective Java" to understand the before and after performance pictures.

The wake-up call: Real-world practices

While it's fun to theorize about performance impacts, we need to sober up when dealing with our real-world coding practices. A sensible approach would be:

• Reserve exceptions for the actual party crashers, not ordinary guests
• Follow the fail-fast principle, nobody likes a party pooper
• Implement validation checks, like the bouncer at the club door
• Save exceptions for when your code decides to go off-script

Adherence to these principles ensures your execution stays on the straight and narrow, maintaining clear lanes for the superhighway of your code execution.