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Math.sqrt perf
(version: 0)
Comparing performance of:
Math.sqrt(a ** 2 + b ** 2) vs a ** 2 + b ** 2
Created:
5 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var a = 5 var b = 10
Tests:
Math.sqrt(a ** 2 + b ** 2)
Math.sqrt(a ** 2 + b ** 2)
a ** 2 + b ** 2
a ** 2 + b ** 2
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Math.sqrt(a ** 2 + b ** 2)
a ** 2 + b ** 2
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'll break down the benchmark and its options, explaining what's being tested, the pros and cons of each approach, and other considerations. **Benchmark Definition** The benchmark definition is a JSON object that contains metadata about the test case. In this case: * "Name": "Math.sqrt perf" - This is the name given to the benchmark. * "Description": null - There is no description provided for this benchmark. * "Script Preparation Code": "var a = 5\r\nvar b = 10" - This code is executed before each test run. It defines two variables, `a` and `b`, with values 5 and 10 respectively. * "Html Preparation Code": null - There is no HTML preparation code provided. **Individual Test Cases** The benchmark consists of two individual test cases: 1. "Math.sqrt(a ** 2 + b ** 2)" - This test case defines a new variable, `c`, by executing the expression `(a ** 2 + b ** 2)`. The result is not stored anywhere. 2. "a ** 2 + b ** 2" - This test case simply executes the expression `a ** 2 + b ** 2` and stores the result in a variable. **Test Case Analysis** Both test cases are measuring the performance of the JavaScript engine when executing mathematical expressions involving exponentiation (`**`) and addition (`+`). The first test case defines a new variable `c` by calculating `(a ** 2 + b ** 2)` and discarding the result, while the second test case simply calculates `a ** 2 + b ** 2` and stores it in a variable. The pros of this approach are: * It allows for accurate measurement of the engine's performance when executing complex expressions. * It provides a baseline for comparing the performance of different JavaScript engines. However, there are some potential drawbacks: * The first test case creates an extra variable `c`, which may incur additional overhead due to memory allocation and garbage collection. * Both test cases rely on the JavaScript engine's ability to optimize and execute mathematical expressions efficiently. **Library Usage** In this benchmark, no external libraries are used. The test cases only utilize built-in JavaScript functionality. **Special JS Features or Syntax** None of the provided test cases use any special JavaScript features or syntax that would require additional explanation. **Other Considerations** When running benchmarks like this one, it's essential to consider the following: * Consistency: Ensure that the benchmark is run with consistent input values and settings. * Isolation: Avoid introducing external factors that could influence the benchmark results, such as caching or network effects. * Replication: Run the benchmark multiple times to ensure reliable and representative results. **Alternative Approaches** Other approaches to measuring JavaScript engine performance include: 1. **Simple arithmetic operations**: Measuring the execution time of basic arithmetic operations like addition, subtraction, multiplication, and division. 2. **String manipulation**: Testing the performance of string-related functions, such as concatenation, substring extraction, or regular expression matching. 3. **Object-oriented programming (OOP) examples**: Evaluating the performance of OOP constructs, such as classes, objects, inheritance, and polymorphism. These alternative approaches can provide additional insights into the strengths and weaknesses of different JavaScript engines.
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