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This paper empirically evaluates the energy efficiency of the Memento design pattern in software engineering, revealing the hidden "metabolic costs" associated with design abstractions. By contrasting the Memento pattern with both Classic full-snapshot and Differential delta-encoding strategies, the authors utilize high-fidelity telemetry to measure energy dissipation across varying state volumes. The key finding highlights a significant trade-off: while the Differential strategy can achieve up to 65.8% energy reduction for mid-scale states, it encounters a critical "memory wall" at 200 MB, where performance gains are negated by severe garbage collection thrashing and power spikes.
A staggering 65.8% energy reduction is possible with the right design strategy, but beware the "memory wall" that can obliterate those gains at scale.
As Green Software Engineering matures, energy efficiency has transitioned into a mission-critical non-functional requirement. While software design patterns ensure structural integrity, their inherent abstraction layers impose an implicit"metabolic cost"that often remains obscured during the design phase. This paper empirically investigates the energy dynamics of the Memento design pattern, contrasting a direct, unabstracted baseline against Classic full-snapshot and Differential delta-encoding strategies. Leveraging the RAPL interface for high-fidelity hardware telemetry, we quantify energy dissipation across state volumes scaling from 10 MB to 200 MB. Our empirical results expose a critical architectural trade-off: the Differential strategy minimizes memory traffic, yielding a maximum energy reduction of 65.8% for mid-scale states, but collides with a catastrophic"memory wall"at 200 MB. At this saturation point, algorithmic optimizations are completely neutralized by severe GC thrashing and non-linear power spikes. We synthesize these findings into evidence-based heuristics, providing architects with a robust framework to reconcile structural design quality with sustainable Green IT imperatives.
