Benchmark: 어느게 빠른가

Script Preparation code:

function calculateChange(payment, cost) {
  let change = payment - cost;
  let money = [50000, 10000, 5000, 1000]; // 5만, 1만, 5천, 1천
  let moneyResult = [0, 0, 0, 0];
  
  for(let i= 0; i < money.length; i++) {
    if(change <= 0) break;
    
    if(change / money[i] > 0){
      let temp = Math.floor(change / money[i]);
      moneyResult[i] = temp;
      change = change % money[i];
    }
  }
  
  console.log(`50000원 지폐: ${moneyResult[0]}장`);
  console.log(`10000원 지폐: ${moneyResult[1]}장`);
  console.log(`5000원 지폐: ${moneyResult[2]}장`);
  console.log(`1000원 지폐: ${moneyResult[3]}장`);
}

Tests:

a
calculateChange(100000, 33000);
b
calculateChange(500000, 378000);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
a
b

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model gemma2:9b, generated one year ago):

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This benchmark measures the performance of calculating change in Korean currency.  It simulates giving money to a cashier and determining how many banknotes (of different denominations) are needed as change.

**Here's a breakdown:**

* **The Problem:** The `calculateChange` function takes two numbers: `payment` (the amount paid) and `cost` (the price of the item). It then calculates the correct number of 50,000 won, 10,000 won, 5,000 won, and 1,000 won banknotes needed for the change.

* **Options Compared:** There's only one algorithm implemented in this benchmark. It iterates through each denomination and calculates how many notes are needed from largest to smallest. The code is optimized slightly by breaking out of the loop when the `change` becomes zero or negative.

* **Pros/Cons:**
    * **Simplicity:** This approach is easy to understand and implement.
    * **Efficiency (For this case):** It's efficient because it only iterates through the denominations once.

* **Alternatives:** There are other ways to calculate change, such as:
    * **Greedy Algorithm:** Start with the largest denomination and work down, always using the maximum number of notes possible. This might not always be optimal in terms of minimizing the total number of notes used but it's generally faster. 
    * **Dynamic Programming:** For more complex scenarios (different denominations, finding the minimum number of notes), dynamic programming can be used to find the most efficient solution.

**Key Considerations:**
   *  **Currency System:** The benchmark is specifically tailored to Korean currency denominations.

Let me know if you have any other questions about this benchmark or would like a deeper dive into any of these concepts!

Related benchmarks:

어느게 빠른가 (version: 0)

Comparing performance of: a vs b

Created: 4 years ago by: Guest

Jump to the latest result

a

b

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model gemma2:9b, generated one year ago):