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JS Shift vs Pop w/ Push
(version: 1)
Comparing performance of:
Pop vs Shift
Created:
one year ago
by:
Guest
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Script Preparation code:
var array = []; for(var i = 0; i < 100000; i++){array.push(Math.random());}
Tests:
Pop
for(var i = 0; i < 100000; i++) { let val = array.pop() array.push(val) }
Shift
for(var i = 0; i < 100000; i++) { let val = array.shift() array.push(val) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Pop
Shift
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one month ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/144.0.0.0 Safari/537.36 OPR/128.0.0.0
Browser/OS:
Opera 128 on Mac OS X 10.15.7
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Test name
Executions per second
Pop
1820.8 Ops/sec
Shift
0.7 Ops/sec
Autogenerated LLM Summary
(model
gpt-4o-mini
, generated one year ago):
The benchmark defined by the provided JSON focuses on comparing the performance of two array manipulation operations in JavaScript: `pop` and `shift`. ### Benchmark Overview: - **Name:** JS Shift vs Pop w/ Push - **Objective:** To measure the difference in performance between `array.pop()` and `array.shift()`, both of which retrieve and remove an element from an array, but operate at different ends of the array. - **Setup:** A large array (100,000 elements) is initialized with random numbers. ### Test Cases: 1. **Pop:** - **Benchmark Definition:** ```javascript for(var i = 0; i < 100000; i++) { let val = array.pop(); array.push(val); } ``` - **Description:** The `pop` method removes the last element from the array and stores it in the variable `val`, which is then pushed back onto the array. This simulates an operation of repeatedly removing and then re-adding the same element while focusing on the performance of the `pop` function. 2. **Shift:** - **Benchmark Definition:** ```javascript for(var i = 0; i < 100000; i++) { let val = array.shift(); array.push(val); } ``` - **Description:** The `shift` method removes the first element from the array, again storing it in `val`, which is then pushed back onto the array. This tests the performance of the `shift` function, which operates on the opposite end of the array compared to `pop`. ### Performance Results: The results from the benchmark show significantly different execution speeds: - For the **Pop** operation, there are approximately 1,035.92 executions per second. - For the **Shift** operation, the performance drops dramatically to approximately 0.36 executions per second. ### Pros and Cons of Each Approach: - **Pop:** - **Pros:** - Faster performance, especially in large arrays. - Constant time complexity (O(1)) because it removes elements from the end of the array. - **Cons:** - Limited to removing from the end, which may not be suitable for certain data structures that require accessing elements from the beginning. - **Shift:** - **Pros:** - Useful when elements need to be processed in a FIFO (first in, first out) manner. - **Cons:** - Slower performance due to having to shift all elements in the array after removing the first element, resulting in linear time complexity (O(n)). This can become a bottleneck, especially with large arrays. ### Other Considerations: - **Use Cases:** The choice between `pop` and `shift` depends on the specific use case in application design. If maintaining order and processing in a FIFO manner is crucial, `shift` may be necessary despite its performance drawbacks. For LIFO (last in, first out) operations, `pop` is more suitable. - **Alternatives:** Other alternatives for managing collections of data include using linked lists or queues that may offer better performance for specific operations like insertion and deletion at both ends, though those structures are not built-in JavaScript types. For newer scenarios, the `ArrayBuffer` and typed arrays could be considered, especially in performance-critical applications. In summary, this benchmark effectively highlights the trade-offs in array operations in JavaScript, providing insights that can guide developers in selecting the appropriate methods for their specific needs based on performance implications.
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