Benchmark: javascript-performance-call-function-inside-for-loop

Tests:

case 1
var temp = []; for (var i = 0; i < 1000; i++) { var b = plusOne(i); temp.push(b); } for (var j = 0; j < temp.length; j++) { console.log(j); } function plusOne(i) { return i+1; }
case 2
var temp = []; for (var i = 0; i < 1000; i++) { var b = i + 1; temp.push(b); } for (var j = 0; j < temp.length; j++) { console.log(j); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
case 1
case 2

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Windows

View result in a separate tab

Test name	Executions per second
case 1	243.3 Ops/sec
case 2	262.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its components.

**What is tested:**

The benchmark tests the performance of calling a function inside a for loop. Specifically, it compares two approaches:

1. Calling `plusOne(i)` directly within the loop (Case 2).
2. Assigning the result of `i + 1` to a variable `b` and then pushing `b` onto an array `temp` (Case 1).

**Options compared:**

* Case 1 uses a more traditional approach with explicit assignment and array push.
* Case 2 uses a more concise approach with direct function call inside the loop.

**Pros and cons of each approach:**

* **Case 1 (Explicit assignment):**
	+ Pros:
		- Easier to read and understand, especially for those familiar with traditional C-style programming.
		- Less prone to off-by-one errors if the indexing is not correct.
	+ Cons:
		- May incur additional overhead due to explicit assignment and array push.
* **Case 2 (Direct function call):**
	+ Pros:
		- More concise and compact, which can lead to better performance in some cases.
		- Less chance of off-by-one errors if the indexing is not correct.
	+ Cons:
		- May be less readable for those unfamiliar with this syntax.
		- Requires careful consideration of variable scope and lifetime.

**Library usage:**

None of the benchmark definitions explicitly use a library, but we can infer that `plusOne` function is likely implemented in a way that's similar to a simple arithmetic operation. Without more information, it's difficult to say for certain what this function does or how it's implemented.

**Special JS features or syntax:**

The test cases use the following special JavaScript features:

* The `var` keyword for variable declaration.
* The `for` loop construct.
* The `push` method on arrays.
* Function definitions (specifically, the `plusOne` function).

These features are all standard in JavaScript and don't require any additional setup or configuration to run.

**Other alternatives:**

If you're looking for alternative approaches to benchmarking performance, consider the following options:

1. **Using a just-in-time (JIT) compiler:** Some JavaScript engines, like V8 (used by Google Chrome), have built-in JIT compilers that can optimize code at runtime.
2. **Microbenchmarking frameworks:** Libraries like Benchmark.js or Microbenchmark provide additional features and configuration options for benchmarking performance.
3. **Native language benchmarks:** If you're interested in comparing the performance of native languages, consider using tools like `time` (on Linux/macOS) or `timeout` (on Windows).
4. **GPU-accelerated benchmarks:** For GPU-accelerated workloads, consider using frameworks like GLBenchmark or OpenCL.

Keep in mind that the choice of benchmarking tool and approach depends on your specific use case and requirements.

Related benchmarks:

javascript-performance-call-function-inside-for-loop (version: 0)

Comparing performance of: case 1 vs case 2

Created: 4 years ago by: Guest

Jump to the latest result

case 1

case 2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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