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Test if an extension is included in the list of candidates
(version: 0)
Comparing performance of:
RegExp.prototype.test() vs Array.prototype.includes()
Created:
3 years ago
by:
Guest
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Tests:
RegExp.prototype.test()
/^\.(?:js|mjs|cjs|jsx|ts|mts|cts|tsx)$/.test('.js')
Array.prototype.includes()
['.js', '.mjs', '.cjs', '.jsx', '.ts', '.mts', '.cts', '.tsx'].includes('.js')
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Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
RegExp.prototype.test()
Array.prototype.includes()
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'll break down the benchmark definition and test cases to explain what's being tested. **Benchmark Definition** The provided JSON defines two benchmark definitions: 1. `/^\\.(?:js|mjs|cjs|jsx|ts|mts|cts|tsx)$/.test('.js')` 2. `['.js', '.mjs', '.cjs', '.jsx', '.ts', '.mts', '.cts', '.tsx'].includes('.js')` Both benchmarks test the performance of JavaScript (JS) files, but they use different approaches. **Approaches** 1. **Regular Expressions**: The first benchmark uses a regular expression (`/^\\.(?:js|mjs|cjs|jsx|ts|mts|cts|tsx)$/.test('.js')`) to check if the string '.js' matches the pattern of any JavaScript file extension (including variants like `mjs`, `cjs`, etc.). This approach is straightforward but may be slower due to the overhead of regular expression evaluation. 2. **String Array Search**: The second benchmark uses a simple array search (`['.js', '.mjs', '.cjs', '.jsx', '.ts', '.mts', '.cts', '.tsx'].includes('.js')`) to check if the string '.js' is present in the list of JavaScript file extensions. This approach is likely faster since it uses a direct lookup, but it may not be as robust as the regular expression approach. **Pros and Cons** * **Regular Expressions**: + Pros: Robustness (matches various file extensions), ease of maintenance (can add or remove variants easily). + Cons: Slower execution due to regular expression overhead. * **String Array Search**: + Pros: Faster execution, simple implementation. + Cons: Limited robustness (only checks for exact string presence). **Library and Special JS Features** Neither benchmark uses a specific library. However, the use of ES6+ syntax features like template literals (`".js"`) is evident in the `String.prototype.includes()` method. **Other Alternatives** If you want to optimize the first benchmark, you could consider using a more efficient regular expression engine or precompiling the regular expressions for each JavaScript file extension variant. For the second benchmark, using a faster string matching algorithm like Boyer-Moore or Knuth-Morris-Pratt might provide a performance boost. Keep in mind that these optimizations are implementation-specific and may not be relevant to the current benchmark setup.
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