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Which equals operator (== vs ===) is faster? 2
(version: 0)
Is there a performance benefit to replacing == with ===?
Comparing performance of:
test equality vs test strict equality
Created:
2 years ago
by:
Guest
Go to the latest result
Tests:
test equality
var fun = () => { for (let i = 0; i < 100000; i++) { if (i == 95653) { return true; } } }; fun();
test strict equality
var fun = () => { for (let i = 0; i < 100000; i++) { if (i === 95653) { return true; } } }; fun();
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
test equality
test strict equality
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36
Browser/OS:
Chrome 120 on Windows
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=495400" width="100%" height="500px"></iframe>
test strict equality
4K/s
test equality
4K/s
View exact numbers
Test name
Executions per second
✓
test strict equality
4,270 Ops/sec
test equality
4,176 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net! The provided benchmark tests two approaches to equality comparisons in JavaScript: using the loose equality operator (`==`) versus the strict equality operator (`===`). **What is tested?** In this benchmark, we have a simple script that loops through a range of numbers and checks if a specific number (`95653`) matches a given value. The script uses both loose (`==`) and strict (`===`) equality operators to compare `i` with the magic number. The benchmark measures the execution time of these scripts on different browsers (in this case, Chrome 120) to determine which approach is faster. **Options compared:** 1. **Loose Equality Operator (`==`)**: This operator performs a value comparison without considering data types. It checks if the values are equal, regardless of their type. 2. **Strict Equality Operator (`===`)**: This operator performs both value and data type comparisons. It ensures that both the value and the data type match. **Pros and Cons:** * **Loose Equality Operator (`==`)**: + Pros: - Generally faster, as it avoids type checking. - Can lead to unexpected behavior if used with numeric values (e.g., `5 == "5"`). + Cons: - May produce incorrect results due to type coercion. - Can make code harder to understand and maintain. * **Strict Equality Operator (`===`)**: + Pros: - Provides more accurate results, as it checks both value and data type. - Encourages better code quality, as it helps avoid unexpected behavior. + Cons: - Generally slower than loose equality operator due to type checking. **Other Considerations:** * In modern JavaScript, the `===` operator is generally considered a good practice for equality comparisons. However, in some legacy code or specific cases (e.g., when working with older browsers), using `==` might be necessary. * When comparing values with strings, it's essential to use the `===` operator to ensure accurate results. **Library and Special JS Feature:** There is no explicit library mentioned in the benchmark definition. However, JavaScript's built-in operators (`==` and `===`) are sufficient for this test case. **Special JS Feature:** None of the provided benchmark code uses any special JavaScript features or syntax. The script is straightforward and relies solely on basic JavaScript constructs. Now that we've explored the details of this benchmark, let's consider other alternatives: * Other browsers: MeasureThat.net might include benchmarks for different browsers to provide a more comprehensive understanding of performance differences. * Different equality operators: In some cases, other equality operators like `!=`, `!==`, or even `===` with type coercion might be used. These variants would add additional complexity and interest to the benchmark. * Larger datasets: To further stress the JavaScript engine, larger datasets could be used in future benchmarks. Feel free to ask if you have any questions or need further clarification!
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