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It is not the case that Hartmanis and Stearns' original 1965 framework acknowledged that asymptotic analysis abstracts away practically critical constant factors and thresholds.
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Reasons For
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1.
The claim overstates acknowledgment: their 1965 paper focused on defining computability classes, not critiquing constant-factor abstraction.
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2.
Modern complexity theory often obscures that polynomial algorithms with large constants can be impractical, misleading practitioners about solvability.
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3.
Ignoring thresholds has real consequences: an O(n³) algorithm with huge constants may outperform O(n log n) only beyond infeasible input sizes.
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Reasons Against
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Reason against
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1.
Hartmanis-Stearns explicitly defined complexity classes relative to machine models, acknowledging that constants depend on implementation choices.
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2.
Their framework enabled tractability distinctions (P vs NP) that remain useful despite ignoring constants, validating the abstraction's value.
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3.
Asymptotic analysis was presented as a tool for theoretical understanding, not as a complete model of practical runtime behavior.
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