Benchmark: slice vs substr vs substring with search

Script Preparation code:

var example = 'Playlist.js'

Tests:

slice
var result = example.slice(0, example.search(/\./))
substr
var result = example.substr(0, example.search(/\./))
substring
var result = example.substring(0, example.search(/\./))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
substr
substring

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what is being tested.

The test measures the performance of three different string slicing methods in JavaScript: `slice()`, `substr()`, and `substring()` with an optional search parameter.

**What are we testing?**

The benchmark compares the execution speed of these three methods, specifically when used with a regular expression search (`example.search(/\\./)`) to find the index of a specific character (`\`).

**Options being compared:**

1. `slice()`: Returns a new string containing from the start (index 0) up to but not including the specified number of positions.
2. `substr()`: Returns a substring of an existing string, starting at a specified position and ending at another specified position.
3. `substring()`: Similar to `substr()`, but also includes the search parameter in its behavior.

**Pros and Cons:**

* **Performance:** `slice()` is generally considered the fastest of the three methods, as it avoids creating an intermediate string object.
* `substr()` can be slower than `slice()` due to the overhead of parsing the second argument's length.
* `substring()`, which includes the search parameter, might perform better in some cases because it allows for more efficient index calculation.

However, these performance differences are usually negligible unless you're dealing with extremely large strings or working under tight execution constraints. The main takeaway is that `slice()` is often a good choice when speed matters, while `substring()` provides an additional layer of convenience and flexibility.

**Other considerations:**

*   Regular expression searches can introduce overhead due to the parsing and compilation process.
*   Using `search()` instead of `indexOf()`, which finds the index of the first match, might lead to slightly different results.
*   These benchmarks do not account for the nuances of how these methods handle edge cases like null or undefined input strings.

**Library usage:**

The provided benchmark does not explicitly use any external libraries. However, it does rely on built-in JavaScript functionality.

**Special JavaScript features or syntax:**

None are mentioned in this specific benchmark.

Now that we've gone through the individual test cases and considered various factors, here are some alternatives:

1.  **Benchmarking frameworks:** Tools like BenchmarkJS or V8.js can help with setup, execution, and reporting of benchmarks.
2.  **String manipulation libraries:** Depending on your use case, libraries like Lodash or Underscore.js provide additional string manipulation utilities that might affect performance in your benchmark.
3.  **Profiling tools:** Instruments like Chrome DevTools' Profiler allow for more detailed analysis of execution time and resource usage.

In summary, the provided JSON benchmark measures the speed of three string slicing methods (`slice()`, `substr()`, and `substring()` with a search parameter) to help identify which method is generally the fastest in your specific use case. Consider performance, additional features like search functionality, library dependencies, and edge cases when choosing an approach for your project.

Related benchmarks:

slice vs substr vs substring with search (version: 0)

Comparing performance of: slice vs substr vs substring

Created: 5 years ago by: Guest

Jump to the latest result

slice

substr

substring

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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