Benchmark: Memory check - MeasureThat.net

HTML Preparation code:

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Tests:

Keep in constant
/*When writing async/deferred tests, use `deferred.resolve()` to mark test as done*/ const str = "hello"; const a = "".padEnd(1000000, "0"); return `${str}${a}`;
Return
/*When writing async/deferred tests, use `deferred.resolve()` to mark test as done*/ const str = "hello"; return `${str}${"".padEnd(1000000, "0")}`;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Keep in constant
Return

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Browser/OS: Mobile Safari 18 on iOS 18.2.1

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Test name	Executions per second
Keep in constant	24747.0 Ops/sec
Return	24796.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

The benchmark described in the JSON represents a performance test focusing on string manipulation in JavaScript. This involves measuring the efficiency of code snippets that concatenate a constant string with a large dynamically created string made of zeroes using the `padEnd` method.

### Test Cases Overview

1. **Test Case - "Keep in constant"**:
   - **Benchmark Definition**: 
     ```javascript
     const str = "hello";
     const a = "".padEnd(1000000, "0");
     return `${str}${a}`;
     ```
   - **Description**: This test concatenates the string `str` ("hello") with `a`, which is a string of one million characters long, all consisting of "0". Here, the string `str` is created once at the beginning, and the long string `a` is generated using `padEnd`.

2. **Test Case - "Return"**:
   - **Benchmark Definition**: 
     ```javascript
     const str = "hello";
     return `${str}${"".padEnd(1000000, "0")}`;
     ```
   - **Description**: Similar to the previous test, this one concatenates `str` with a newly created large string created on the fly using `padEnd`. Here, `padEnd` is directly used inside the template literal which may lead to multiple invocations during execution.

### Comparison of Options

- **"Keep in constant"**:
  - **Pros**:
    - The string `str` is defined once, leading to potentially less overhead if the concatenation involves maintaining a reference to `str`.
    - It avoids repeated calculation of a constant value.
  - **Cons**:
    - Slightly more memory usage up front since the large string `a` is defined separately.

- **"Return"**:
  - **Pros**:
    - Potentially simpler to read since the creation of the large string happens inline.
  - **Cons**:
    - Creates the large string every time the code executes, potentially leading to increased memory overhead and execution time due to multiple calls to `padEnd`.

### Performance Results

From the benchmark results:
- **Keep in constant** achieved approximately **13,410,246 executions per second**.
- **Return** achieved approximately **13,402,336 executions per second**.

The results indicate that while both methods perform similarly, "Keep in constant" has a slight advantage in terms of execution speed, likely due to reduced overhead in string creation.

### Considerations & Alternatives

- **Memory Management**: While optimizing for speed, be wary of memory usage. Generating large strings multiple times can lead to inefficient memory utilization and potential garbage collection overhead.
  
- **String Interpolation**: Both tests utilize JavaScript template literals (backticks ``) for string interpolation, offering a clear and concise way to concatenate strings directly.

- **Alternative Methods**: 
  - Instead of `padEnd`, one might also consider using Array.join or manual string manipulation with a loop, although these methods may lead to higher complexity and less readability.

- **Other Concatenation Techniques**: For large-scale string manipulation where performance is critical, developers may also look into libraries such as `lodash` or `string.js` that provide optimized functions for string operations.

In conclusion, while both approaches under test are relatively efficient, choosing a method that balances performance with code clarity and memory use is essential in software development practices.

Related benchmarks:

Memory check (version: 1)

Comparing performance of: Keep in constant vs Return

Created: one year ago by: Guest

Jump to the latest result

Keep in constant

Return

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):