Benchmark: TestKey - MeasureThat.net

Script Preparation code:

var values = [];
for(let i=0;i<1000000;++i) {
  values[i] = Math.random();
}

Tests:

String
var cache1 = {}; for(let i=0;i<1000; ++i) { for(let j=0;j<1000;++j) { cache1[`${i}-${j}`] = values[i*j]; } }
Number
var cache2 = {}; for(let i=0;i<1000; ++i) { for(let j=0;j<1000;++j) { cache2[i*65000+j] = values[i*j]; } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
String
Number

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Linux

View result in a separate tab

Test name	Executions per second
String	2.1 Ops/sec
Number	3.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's being tested in this specific benchmark.

**Benchmark Definition**

The provided JSON represents a benchmark definition, which is a set of rules for creating and running a JavaScript microbenchmark. The key elements of the benchmark definition are:

* `Name`: A unique identifier for the benchmark (in this case, "TestKey").
* `Script Preparation Code` and `Html Preparation Code`: These codes are executed before the actual benchmark test to prepare the environment.
* `Benchmark Definition`: This is where the actual benchmark code is defined.

In this case, there's only one benchmark definition, which consists of two test cases:

**Test Cases**

The individual test cases are stored in an array and each represents a different approach to measuring performance. Let's analyze them:

1. **String Test Case**
```javascript
var cache1 = {};
for(let i=0;i<1000; ++i) {
  for(let j=0;j<1000;++j) {
    cache1[`${i}-${j}`] = values[i*j];
  }
}
```
This test case measures the performance of a loop that:

* Creates an object (`cache1`) to store data.
* Uses two nested loops to iterate over `values` array, storing intermediate results in the `cache1` object.

Pros and Cons:

Pros: Simple and straightforward implementation.

Cons: This approach can lead to unnecessary computations due to repeated calculations (e.g., `i*j`) inside the loop. It also uses a large amount of memory due to storing all intermediate results in the cache.

2. **Number Test Case**
```javascript
var cache2 = {};
for(let i=0;i<1000; ++i) {
  for(let j=0;j<1000;++j) {
    cache2[i*65000+j] = values[i*j];
  }
```
This test case measures the performance of a loop that:

* Creates an object (`cache2`) to store data.
* Uses two nested loops to iterate over `values` array, storing intermediate results in the `cache2` object. The calculation inside the inner loop is different from the previous test case.

Pros and Cons:

Pros: Similar to the previous test case, but with a slightly optimized inner loop calculation (`i*j`) that's likely faster due to caching effects.

Cons: Still uses unnecessary computations and memory storage for intermediate results.

**Library Use**

Neither of these benchmark definitions explicitly uses any libraries or external dependencies. However, it does rely on the built-in `Math` object and the `values` array, which is generated by the `Script Preparation Code`.

**Special JS Features**

There are no special JavaScript features (e.g., async/await, arrow functions, generators) used in this benchmark definition.

**Alternatives**

If you were to rewrite this benchmark, here are some alternative approaches to consider:

* Use a more efficient data structure, such as an array or a `Map`, instead of objects for caching.
* Optimize the inner loop calculation using techniques like memoization or function inlining.
* Consider using parallel processing or multithreading to measure performance on multi-core CPUs.
* Use a more robust and standardized benchmarking framework, such as WebPageTest or BenchmarkJS.

Keep in mind that microbenchmarks are usually designed for specific purposes (e.g., comparing the performance of different implementations) rather than general-purpose performance measurement.

Related benchmarks:

TestKey (version: 0)

Comparing performance of: String vs Number

Created: one year ago by: Guest

Jump to the latest result

String

Number

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):