translation: Update chapter_computational_complexity/performance_evaluation.md #1557
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SamJin98
reviewed
Dec 3, 2024
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| On the other hand, **conducting a full test is very resource-intensive**. As the volume of input data changes, the efficiency of the algorithms may vary. For example, with smaller data volumes, algorithm `A` might run faster than `B`, but the opposite might be true with larger data volumes. Therefore, to draw convincing conclusions, we need to test a wide range of input data sizes, which requires significant computational resources. | ||
| On the other hand, **conducting a full test is very resource-intensive**. As the volume of input data changes, the efficiency of the algorithms also changes. For example, with smaller data volumes, algorithm `A` might run faster than `B`, but with larger data volumes, the test results may be the opposite. Therefore, to draw convincing conclusions, we need to test a wide range of input data sizes, which requires excessive computational resources. |
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suggestion:
'As the volume of input data changes, the efficiency of the algorithms also changes.'
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'Algorithm efficiency varies with input data size.'
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| On one hand, **it's difficult to eliminate interference from the testing environment**. Hardware configurations can affect algorithm performance. For example, algorithm `A` might run faster than `B` on one computer, but the opposite result may occur on another computer with different configurations. This means we would need to test on a variety of machines to calculate average efficiency, which is impractical. | ||
| On one hand, **it's difficult to eliminate interference from the testing environment**. Hardware configurations can affect algorithm performance. For example, an algorithm with a high degree of parallelism is better suited for running on multi-core CPUs, while an algorithm that involves intensive memory operations performs better with high-performance memory. The test results of an algorithm may vary across different machines. This means we would need to test the algorithm on various machines to calculate average efficiency, which is impractical. |
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suggestion:
'...we need to test the algorithm on various machines to calculate average efficiency, which is impractical.'
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'...testing across multiple machines to calculate average efficiency becomes impractical.'
yuelinxin
reviewed
Dec 13, 2024
| 2. **Seeking the Optimal Solution**: For the same problem, multiple solutions might exist, and we aim to find the most efficient algorithm possible. | ||
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| In other words, under the premise of being able to solve the problem, algorithm efficiency has become the main criterion for evaluating the merits of an algorithm, which includes the following two dimensions. | ||
| In other words, under the premise of being able to solve the problem, algorithm efficiency has become the main criterion for evaluating the quality of an algorithm, which includes the following two dimensions. |
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it might be better here to just not have anything, as in “for evaluating an algorithm”
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I've added some parts to align with the Chinese version and rephrased certain sentences for better readability. I personally prefer the term 'Practical Testing' over 'Actual Testing' because it is more commonly used and more relevant to the content. However, I'm not certain about the definitive correct term, so didn’t make the change.
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