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Average-case performance evaluates the expected efficiency of an algorithm by considering the average number of steps or operations it takes to complete, assuming a distribution of all possible inputs. This measure provides a more realistic assessment of an algorithm's efficiency in practical scenarios compared to worst-case analysis, as it accounts for the typical input cases encountered during execution.
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