Benchmark: testm1 - MeasureThat.net

Script Preparation code:

var mp = new Map(),
    mparr;
for (var i = 0; i < 1000; i++) {
    mp.set(`${i}${i}`, i);
}
mparr = [...mp];

Tests:

m1
var cnt = 0; for (var i = 0; i < 1000; i++) { if (mp.has(`${i+10}${i+10}`)) { cnt++ } }
m2
var cnt = 0, mpp = new Map(mparr), mpparr; for (var i = 0; i < 1000; i++) { if (mpp.has(`${i+10}${i+10}`)) { cnt++ } } mpparr = [...mpp];
m3
var cnt = 0; for (var i = 0; i < 1000; i++) { if (mparr.find(x => x[0] === `${i+10}${i+10}`)) { cnt++ } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
m1
m2
m3

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its various components.

**Benchmark Definition JSON**

The provided JSON represents a JavaScript microbenchmark defined by MeasureThat.net. Here's what each section tests:

* `Script Preparation Code`: This is the code that prepares the script for execution, including variables, data structures, and setup necessary for the benchmark.
* `Html Preparation Code` (not present in this example): This would be HTML code used to set up the testing environment, but it's empty in this case.
* `Benchmark Definition`: This contains the actual JavaScript code that runs the test. In this case, there are three different versions of the same test:
	1. `m1`: Tests a simple iteration using `has()` on a Map (`mp`).
	2. `m2`: Tests iteration using `has()` on another Map created from an array (`mparr`) and a new Map (`mpp`).
	3. `m3`: Tests iteration using `find()` on an array.

**Comparison of Options**

The three test cases compare different approaches to iterating over the data:

* **m1**: Uses `has()` on the original Map (`mp`). This is likely the most straightforward and efficient approach, as it avoids creating unnecessary intermediate objects.
	+ Pros: Simple, easy to understand, and potentially efficient.
	+ Cons: May not be optimized for performance in all cases (e.g., when using a very large dataset).
* **m2**: Creates an array `mpparr` from the original Map (`mparr`) and then iterates over it using `has()` on another Map (`mpp`). This adds unnecessary overhead due to the extra step of creating the array.
	+ Pros: May provide better performance in cases where iteration is expensive (e.g., when dealing with very large datasets).
	+ Cons: More complex, harder to understand, and likely slower due to the added overhead.
* **m3**: Uses `find()` on an array. This approach is often faster than iterating over an object using `has()`, but may be slower for arrays that are already sparse (i.e., most elements have a value).
	+ Pros: May provide better performance, especially when dealing with sparse arrays.
	+ Cons: More complex, and may not be as efficient as using `has()` on objects.

**Other Considerations**

* **Library Usage**: The benchmark uses the built-in `Map` object, which is a part of the JavaScript standard library. This ensures that the results are portable across different browsers and environments.
* **JS Features**: There are no special JavaScript features or syntaxes used in this benchmark (e.g., async/await, promises, destructuring).

**Alternatives**

If you wanted to create your own microbenchmarking framework using MeasureThat.net's approach, here are some alternatives:

1. Create a custom `BenchmarkDefinition` format with the same structure as the provided JSON.
2. Implement a testing engine that can execute the benchmark code and report results in a similar format.
3. Use a library like BenchmarkJS or Microbenchmark to create and run your own benchmarks.

Keep in mind that creating a robust and efficient microbenchmarking framework requires careful consideration of various factors, including performance optimization techniques, error handling, and user experience.

Latest run results:

Run details: (Test run date: 2025 years ago)

User agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36

Browser/OS: Chrome 63 on Windows 7

View result in a separate tab

Test name	Executions per second
m1	4433.0 Ops/sec
m2	2561.1 Ops/sec
m3	48.2 Ops/sec

Related benchmarks:

testm1 (version: 2)

Comparing performance of: m1 vs m2 vs m3

Created: 6 years ago by: Registered User

Jump to the latest result

m1

m2

m3

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):