Benchmark: dfdfddddd - MeasureThat.net

Script Preparation code:

function calculateChange(payment, cost) {
  // 코드를 작성해 주세요.
  let change = payment - cost; // 거스름돈 총액

  function billCounting(amount) {
    const count = Math.floor(change / amount);
    change = change - amount * count;
    return count;
  }

  const fiftyCount = billCounting(50000);
  const tenCount = billCounting(10000);
  const fiveCount = billCounting(5000);
  const oneCount = billCounting(1000);

  console.log(`50000원 지폐: ${fiftyCount}장`);
  console.log(`10000원 지폐: ${tenCount}장`);
  console.log(`5000원 지폐: ${fiveCount}장`);
  console.log(`1000원 지폐: ${oneCount}장`);
}

Tests:

s
calculateChange(100000, 33000);
f
calculateChange(500000, 378000);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
s
f

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down what is tested in the provided JSON benchmark definition and individual test cases.

**Benchmark Definition JSON**

The script preparation code defines a function `calculateChange` that takes two parameters, `payment` and `cost`. The function calculates the change by subtracting the cost from the payment. It then breaks down the change into different denominations (50000원, 10000원, 5000원, and 1000원) using a recursive function called `billCounting`.

The script uses JavaScript's built-in `Math.floor` function to perform integer division.

**Individual Test Cases**

There are two test cases:

1. `calculateChange(100000, 33000);`
2. `calculateChange(500000, 378000);`

These test cases call the `calculateChange` function with different input values for `payment` and `cost`.

**Library Used: None**

There is no explicitly mentioned library used in the script preparation code or individual test cases.

**Special JS Features/Syntax: None**

There are no special JavaScript features or syntax mentioned that would require additional explanation.

Now, let's discuss the options compared during benchmarking:

1. **Native Code vs. Just-In-Time (JIT) Compilation**: The benchmarks compare the performance of native code execution versus JIT compilation. Native code execution is generally faster and more efficient but may not be as performant on JavaScript engines that use JIT compilation.
2. **Dynamic Typing vs. Static Typing**: JavaScript is dynamically typed, which means the data type of a variable is determined at runtime rather than compile time. This flexibility can make development easier, but it can also lead to performance issues due to type checks and conversions.

**Pros and Cons**

* Native Code:
	+ Pros: Generally faster and more efficient.
	+ Cons: May not be compatible with all JavaScript engines or platforms.
* JIT Compilation:
	+ Pros: Can provide better performance for certain workloads, especially those involving complex computations.
	+ Cons: May introduce overhead due to type checks and conversions.

**Other Considerations**

When benchmarking scripts like this one, it's essential to consider the following:

1. **Cache and Memoization**: The `billCounting` function uses memoization ( caching the results of expensive function calls) to improve performance.
2. **Loop Optimization**: The script uses a simple loop structure, but more complex loops or nested loops may require additional optimization techniques.

**Alternatives**

Some alternative approaches for benchmarking JavaScript scripts include:

1. **V8 Benchmark Suite**: A set of benchmarks designed to measure the performance of the V8 engine used in Google Chrome.
2. **SpiderMonkey Benchmark Suite**: A set of benchmarks designed to measure the performance of the SpiderMonkey engine used in Mozilla Firefox.
3. **JavaScript Performance Comparison**: A benchmarking framework that allows users to compare the performance of different JavaScript engines and configurations.

These alternatives can provide more comprehensive and standardized benchmarking results, but may require more setup and configuration effort on your part.

Related benchmarks:

dfdfddddd (version: 0)

dfdfdfdfd

Comparing performance of: s vs f

Created: 4 years ago by: Guest

Jump to the latest result

s

f

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):