Benchmark: Test array.slice with big array length

Script Preparation code:

var length = 10000
var tenk = new Array(length);

Tests:

Index 0
tenk.slice(0 * length, (0 + 1) * length)
Index 100
tenk.slice(100 * length, (100 + 1) * length)
Index 5000
tenk.slice(5000 * length, (5000 + 1) * length)
Index 9999
tenk.slice(9999 * length, (9999 + 1) * length)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Index 0
Index 100
Index 5000
Index 9999

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**What is being tested?**

The provided JSON represents a benchmark test case on MeasureThat.net, where users can create and run JavaScript microbenchmarks. Specifically, this test case measures the performance of the `Array.slice()` method with different starting and ending indices on a large array (`tenk`) created in advance.

**Options compared:**

There are four different approaches being compared:

1. **Index 0**: Starting index is 0, which means the slice operation will return the first element of the array (the `tenk` array has 10,000 elements).
2. **Index 100**: Starting index is 100, which means the slice operation will return a subset of the middle elements of the array.
3. **Index 5000**: Starting index is 5,000, which means the slice operation will return a subset of the second half of the array (the last 5,000 elements).
4. **Index 9999**: Starting index is 9,999, which means the slice operation will return the last element of the array.

**Pros and cons of each approach:**

1. **Index 0**: This approach is likely to be the fastest since it only involves accessing a single element.
2. **Index 100**: This approach is more challenging for the browser's JavaScript engine, as it requires accessing a larger subset of elements without knowing their indices in advance.
3. **Index 5000**: Similar to Index 100, this approach is less predictable and may require additional calculations or data structures to optimize performance.
4. **Index 9999**: This approach is likely to be slower than Index 0 since it requires accessing the last element of a large array.

**Library usage:**

None of the provided benchmark definitions use any external libraries.

**Special JS features or syntax:**

There are no special JavaScript features or syntax used in this test case. The code only uses standard JavaScript syntax and built-in methods like `Array.slice()`.

**Other alternatives:**

Some alternative approaches to measuring performance might include:

* Using a different data structure, such as an object or a set, instead of an array.
* Incorporating additional computational overhead, such as encryption or hashing algorithms.
* Using a different browser or JavaScript engine configuration.
* Adding additional variables or dependencies that could affect performance.

Keep in mind that the choice of approach will depend on the specific use case and requirements of the benchmark.

Related benchmarks:

Test array.slice with big array length (version: 0)

Comparing performance of: Index 0 vs Index 100 vs Index 5000 vs Index 9999

Created: 2 years ago by: Guest

Jump to the latest result

Index 0

Index 100

Index 5000

Index 9999

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):