Benchmark: Max and Min values

Script Preparation code:

var data = []
   
for (var x = 1; x <= 100000; x++) {
  data.push({ x: x, y: Math.floor(Math.random() * (1000000)) })
}

Tests:

Reduce
function getMinY() { return data.reduce((min, p) => p.y < min ? p.y : min, data[0].y); } function getMaxY() { return data.reduce((max, p) => p.y > max ? p.y : max, data[0].y); } const min = getMinY(); const max = getMaxY();
For
function getMinY(){ var minY = data[0].y; for (var i = 1; i < data.length; i++) { if (data[i].y < minY) { minY = data[i].y; } } return minY; } function getMaxY(){ var maxY = data[0].y; for (var i = 1; i < data.length; i++) { if (data[i].y > maxY) { maxY = data[i].y; } } return maxY; } var min = getMinY(); var max = getMaxY();
For ternary
function getMinY(){ var minY = data[0].y; for (var i = 1; i < data.length; i++) { minY = data[i].y < minY ? data[i].y : minY; } return minY; } function getMaxY(){ var maxY = data[0].y; for (var i = 1; i < data.length; i++) { maxY = data[i].y > maxY ? data[i].y : maxY; } return maxY; } var min = getMinY(); var max = getMaxY();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce
For
For ternary

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Measuring the performance of different JavaScript code approaches is crucial in understanding how they affect execution speed, especially for complex operations like finding the minimum and maximum values in an array.

**Benchmark Test Case:**

The provided benchmark test case measures the performance difference between three approaches to find the minimum and maximum values in a large dataset:

1. **Reduce**: Uses `Array.prototype.reduce()` to iterate over the data array and find the minimum and maximum values.
2. **For**: Uses a traditional `for` loop to iterate over the data array and find the minimum and maximum values.
3. **For ternary**: Similar to the `For` approach, but uses the ternary operator (`condition ? value1 : value2`) to update the minimum and maximum values.

**Options Compared:**

The three options are compared in terms of their execution speed:

* **Reduce**: This approach is generally faster because it uses a single function call to iterate over the entire array. However, this also means that if the array is very large or the reduction function is slow, the overall performance may suffer.
* **For**: This approach can be slower than `Reduce` because it requires an explicit loop and more memory allocation.
* **For ternary**: Similar to `For`, but with the added overhead of the ternary operator.

**Pros and Cons:**

Here are some pros and cons for each approach:

* **Reduce**:
	+ Pros:
		- Fast execution speed
		- Minimal code changes required
	+ Cons:
		- Limited control over iteration order (may lead to slower performance for certain data structures)
		- May not be suitable for small arrays or arrays with complex data structures
* **For**:
	+ Pros:
		- Control over iteration order and optimization opportunities
		- Suitable for small arrays or arrays with complex data structures
	+ Cons:
		- Slower execution speed compared to `Reduce`
		- More code changes required
* **For ternary**:
	+ Pros:
		- Similar performance to `For` loop
		- Simplified code with reduced number of lines
	+ Cons:
		- Limited control over iteration order and optimization opportunities

**Library:**

There is no explicit library mentioned in the benchmark definition. However, the use of `Array.prototype.reduce()` indicates that the array data structure is being used.

**Special JS Feature/Syntax:**

The test case uses the ternary operator (`condition ? value1 : value2`) which is a feature of JavaScript.

**Alternative Approaches:**

Other alternatives to consider for finding minimum and maximum values in an array include:

* **Using `Math.min()` and `Math.max()` functions**: This approach is simple and easy to understand but may not be suitable for very large arrays due to performance limitations.
* **Using a custom sorting algorithm**: This approach can provide more control over the iteration order and optimization opportunities, but may require more code changes and expertise.

Overall, the choice of approach depends on the specific use case, array size, and performance requirements.

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36

Browser/OS: Chrome 59 on Linux

View result in a separate tab

Test name	Executions per second
Reduce	354.1 Ops/sec
For	32.2 Ops/sec
For ternary	31.5 Ops/sec

Related benchmarks:

Max and Min values (version: 0)

Comparing performance of: Reduce vs For vs For ternary

Created: 7 years ago by: Guest

Jump to the latest result

Reduce

For

For ternary

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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