Benchmark: Direct calls versus external function calls

HTML Preparation code:

<!--your preparation HTML code goes here-->

Script Preparation code:

const tabs = {
  one: { label: 'One' },
  two: { label: 'Two' },
  three: { label: 'Three' },
  four: { label: 'Four' }
}

function fetchDataForTab(tabName) {}

function handleData(data, handler) {
    // performance optimized
    const tabNames = Object.keys(data)
    for (let i = 0; i < tabNames.length; i++) {
        handler(tabNames[i])
    }
}

Tests:

Direct calls
// performance optimized const tabNames = Object.keys(tabs) for (let i = 0; i < tabNames.length; i++) { fetchDataForTab(tabNames[i]) }
Function calls
handleData(tabs, fetchDataForTab)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Direct calls
Function calls

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 months ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_2_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.2 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 18 on iOS 18.2.1

View result in a separate tab

Test name	Executions per second
Direct calls	133584120.0 Ops/sec
Function calls	76562056.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 3 months ago):

LLMs can make mistakes. Check important info.

The benchmark in question, "Direct calls versus external function calls", assesses the performance difference between executing tasks directly in the main code versus delegating those tasks to an external helper function.

### Benchmark Components:

1. **Test Cases**:
   - **Direct calls**: This test executes tasks directly within a loop, calling the `fetchDataForTab` function for each tab.
     ```javascript
     const tabNames = Object.keys(tabs);
     for (let i = 0; i < tabNames.length; i++) {
         fetchDataForTab(tabNames[i]);
     }
     ```
   - **Function calls**: This test leverages a helper function, `handleData`, which takes care of iterating over the tab names and calls the `fetchDataForTab` function for each name.
     ```javascript
     handleData(tabs, fetchDataForTab);
     ```

### Options Compared:
- **Direct Calls**:
  - **Pros**:
    - Generally faster for small and straightforward tasks since there is no overhead associated with the function call mechanism.
    - More concise for simple operations without the need for intermediary functions.
  - **Cons**:
    - Code can become difficult to manage as complexity increases, making it less reusable.
    - In a complex scenario with multiple similar operations, this approach may lead to duplicated code.

- **Function Calls**:
  - **Pros**:
    - Promotes code reusability and maintainability by encapsulating logic in a function. This method adheres to DRY (Don't Repeat Yourself) principles.
    - Makes the codebase clearer and easier to follow, especially when handling complex data processing.
  - **Cons**:
    - Typically incurs an overhead due to additional function calls, which can be significant in performance-critical sections of code.
    - The additional layers may slightly increase the cognitive load for understanding flow compared to direct execution in simpler cases.

### Performance Results:
According to the benchmark results, both methods perform at very similar speeds:
- **Direct calls**: 30,504,702 executions per second.
- **Function calls**: 30,033,634 executions per second.

This indicates that while direct calls have a slight edge in execution speed, the difference in performance may not be substantial enough to outweigh the organizational benefits of using functions, particularly in larger codebases.

### Library Used:
In this benchmark, there are no external libraries involved. The implementation utilizes built-in JavaScript functionality like `Object.keys()` to retrieve property names from the `tabs` object.

### Alternative Approaches:
- **Using Arrow Functions**: Instead of traditional function declarations, arrow functions can be used for syntactic brevity but won’t inherently improve performance.
- **Using Higher-order Functions**: Functions like `forEach`, `map`, or even `reduce` can be employed to iterate through data, which may enhance readability and conciseness, although this might introduce additional overhead depending on the implementation.
- **Asynchronous Patterns**: In more complex scenarios, asynchronous processing (e.g., using `async/await`) could be considered. However, this typically targets I/O-bound operations rather than pure computation.

### Conclusion:
In performance-critical applications, the choice between direct calls and external function calls can significantly influence response times, but factors like maintainability, scalability, and code clarity should also guide the decision-making process. Depending on the specific use case and complexity of tasks, either method may be appropriate. For simpler tasks, direct calls may excel, while for larger, more complex operations, leveraging external functions would likely be beneficial.

Related benchmarks:

Direct calls versus external function calls (version: 1)

Compares doing little tasks immediately versus writing a helper function that does it.

Comparing performance of: Direct calls vs Function calls

Created: 3 months ago by: Registered User

Jump to the latest result

Direct calls

Function calls

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 3 months ago):