Benchmark: q_cshade1 - MeasureThat.net

Script Preparation code:

function colorShade1(color, amount) {
    let [r, g, b] = color.length === 3 ?
      color.split('').map((str) => Number.parseInt(str + str, 16) + amount)
    : color.match(/.{2}/g).map((str) => Number.parseInt(str, 16) + amount);
}

function colorShade2(color, amount) {   
    if (color.length === 3) color = color[0] + color[0] + color[1] + color[1] + color[2] + color[2];
        
  	// Get r,g,b as numbers and with amount applied
  	let r = Number.parseInt(color.substring(0,2), 16) + amount;
  	let g = Number.parseInt(color.substring(2,4), 16) + amount;
  	let b = Number.parseInt(color.substring(4,6), 16) + amount;
}

Tests:

shade1_3
colorShade1('AEF', 10);
shade1_6
colorShade1('36A2EB', 10);
shade2_3
colorShade2('AEF', 10);
shade2_6
colorShade2('36A2EB', 10);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
shade1_3
shade1_6
shade2_3
shade2_6

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Measuring performance differences in JavaScript microbenchmarks can be an intriguing topic.

**Benchmark Definition JSON**

The provided JSON represents the benchmark definition for a simple color-shading function, `colorShade1` and `colorShade2`. The functions take two arguments: a hex color code and an amount value. The purpose of these functions is to demonstrate how different approaches can be used to create shades of colors.

**Script Preparation Code**

The script preparation code is where the actual logic for generating shades of colors is implemented. There are two versions:

1. `colorShade1(color, amount)`: This function uses a single line of code to parse the hex color code and apply the specified amount.
2. `colorShade2(color, amount)`: This function creates a new string by duplicating each character in the original color code (except for the third character, which is duplicated twice), then parses the resulting string to extract the RGB values.

**Options being compared**

The two functions (`colorShade1` and `colorShade2`) represent different approaches to solving the same problem:

* **Direct parsing**: `colorShade1` uses a single line of code to parse the hex color code, which is more efficient but might not be as accurate.
* **String manipulation**: `colorShade2` creates a new string by duplicating each character in the original color code, then parses the resulting string. This approach can lead to slower performance due to string creation and parsing.

**Pros and Cons of each approach**

* **Direct parsing (colorShade1)**:
	+ Pros: Fast execution time, accurate results.
	+ Cons: Limited flexibility if the input format changes.
* **String manipulation (colorShade2)**:
	+ Pros: Flexible for different input formats, can be adapted to other use cases.
	+ Cons: Slower execution time due to string creation and parsing.

**Other considerations**

* The benchmark measures the number of executions per second, which is a common metric for measuring performance in JavaScript microbenchmarks. Other metrics, such as throughput or latency, might also be relevant depending on the specific requirements of the use case.
* The benchmark uses Firefox 102 as the target browser, which might not represent all user bases. Additional benchmarks with different browsers and platforms could provide more comprehensive results.

**Library and syntax usage**

Neither of the functions explicitly uses a library. However, they do demonstrate the use of:

* `Number.parseInt(str, 16)`: A built-in JavaScript function to parse a hexadecimal string.
* String manipulation techniques, such as `split`, `map`, and `substring`, which are also built-in or commonly used in JavaScript.

**Special JS features**

This benchmark does not rely on any special JavaScript features. It uses only standard language features, making it accessible to a wide range of developers.

**Alternatives**

Other alternatives for measuring performance differences in JavaScript microbenchmarks include:

* **Benchmarking libraries**: Libraries like Benchmark.js or jsPerf provide more advanced features and flexibility for creating benchmarks.
* **Profiling tools**: Tools like Chrome DevTools or Node.js Inspector can help identify performance bottlenecks in code, but might require more expertise to set up and interpret.

I hope this explanation helps software engineers understand the basics of measuring performance differences in JavaScript microbenchmarks.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:102.0) Gecko/20100101 Firefox/102.0

Browser/OS: Firefox 102 on Windows

View result in a separate tab

Test name	Executions per second
shade1_3	2691004.0 Ops/sec
shade1_6	2013183.5 Ops/sec
shade2_3	3723825.0 Ops/sec
shade2_6	3500244.8 Ops/sec

Related benchmarks:

q_cshade1 (version: 0)

cshade

Comparing performance of: shade1_3 vs shade1_6 vs shade2_3 vs shade2_6

Created: one year ago by: Guest

Jump to the latest result

shade1_3

shade1_6

shade2_3

shade2_6

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):