Benchmark: Branch or always

Script Preparation code:

var x = 0;

Tests:

branch
var y = Math.random(); if (y < 0.1 || y > 0.9) { x = y % 0.5; }
always
var y = Math.random(); x = y % 0.5;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
branch
always

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll break down the explanation into smaller parts to help you understand what's being tested on this JSON benchmark.

**Benchmark Definition**

The provided JSON defines two microbenchmarks: "Branch or always". This name hints at the type of comparison being made between two approaches. In essence, it's a test that compares:

* **Conditional Branching**: where an instruction is only executed if certain conditions are met.
* **Unconditional Assignment**: where the assignment happens regardless of any conditions.

**Script Preparation Code and HTML Preparation Code**

The script preparation code `var x = 0;` initializes a variable `x` to zero. This is done to ensure that each execution of the benchmark has a consistent starting point. The HTML preparation code is empty (`null`), which suggests that the focus is on testing the JavaScript engine's behavior rather than any external factors like rendering or layout.

**Individual Test Cases**

There are two test cases:

1. **Branch**: This case tests the `if` statement in the benchmark definition:
```javascript
var y = Math.random();
if (y < 0.1 || y > 0.9) {
  x = y % 0.5;
}
```
In this case, the assignment of `x` happens only if the condition is met.

2. **Always**: This case tests an unconditional assignment:
```javascript
var y = Math.random();
x = y % 0.5;
```
Here, `x` is assigned regardless of any conditions.

**Pros and Cons**

*   **Branching** (the original code with a condition):
    *   **Pros**: Can help identify performance issues related to conditional branching or optimization.
    *   **Cons**: May lead to false positives if the condition is often met or not, masking real performance problems.
*   **Always** (unconditional assignment):
    *   **Pros**: Helps ensure consistent results across different execution scenarios and can highlight performance issues in unconditional assignments.
    *   **Cons**: May not accurately represent real-world usage patterns.

**Library and Special JS Features**

There is no specific library mentioned in the provided JSON. However, JavaScript engines often rely on various libraries or frameworks for tasks like DOM manipulation, event handling, or networking. It's essential to note that some benchmarking efforts might be affected by the presence of third-party libraries or frameworks.

No special JavaScript features are mentioned in this specific benchmark.

**Alternatives**

If you're interested in exploring other microbenchmarking tools or approaches:

1.  **Google Benchmark**: A C++-based benchmarking library for measuring performance.
2.  **JMH (Java Microbenchmarking Harness)**: An open-source tool for writing and executing Java benchmarks.
3.  **JSPerf**: A JavaScript-based benchmarking tool that measures performance in various scenarios.

Keep in mind that each benchmarking tool has its strengths and weaknesses, and some might be more suitable for your specific needs than others.

**Additional Considerations**

When working with microbenchmarks like this one:

1.  **Keep it simple**: Focus on a clear and concise test case to ensure accurate results.
2.  **Use meaningful names**: Choose descriptive names for your benchmarking tests, making them easier to understand and analyze.
3.  **Monitor performance trends**: Regularly review the benchmarking results over time to identify any changes or improvements in performance.

By understanding the basics of microbenchmarks like this one, you can create more effective benchmarks that help identify performance issues in JavaScript engines and optimize your applications for better performance.

Latest run results:

Run details: (Test run date: 2025 years ago)

User agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36

Browser/OS: Chrome 63 on Windows 7

View result in a separate tab

Test name	Executions per second
branch	4830434.5 Ops/sec
always	3194355.8 Ops/sec

Related benchmarks:

Branch or always (version: 0)

Comparing performance of: branch vs always

Created: 6 years ago by: Guest

Jump to the latest result

branch

always

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):