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Abstract
This paper investigates algorithmic efficiency from both theoretical and practical perspectives in the context of emerging computational challenges up to the year . By evaluating classical computational models and contrasting them with empirical performance data from modern algorithmic applications, this study reveals the gaps between asymptotic analysis and real-world behavior. Furthermore, it assesses improvements in algorithm design driven by hardware advances and algorithmic paradigms such as parallelism and heuristic methods.
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