CAGE：面向覆盖优化的机制感知算法工程
CAGE: Regime-Aware Algorithm Engineering for Coverage Optimization
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中文总结 AI 辅助
CAGE提出机制感知的算法工程框架，通过位集执行基质和帕累托分析，揭示覆盖优化策略的非支配性随工作负载和条件变化，而非存在通用排序。
中文摘要 AI 辅助
优化相同单调目标的覆盖选择策略，在工作负载规模、预算、重复周期和执行基质变化时，可能占据不同的质量-运行时间前沿。CAGE是一个机制感知的算法工程框架，通过共享的位集执行基质保持覆盖语义不变，并研究在受控操作条件下非支配策略集合如何变化。我们将内在的工作负载描述符与测量的策略响应分离，用每个条件的经验帕累托集合表示，并通过帕累托成员变化或统计支持的交叉来识别机制转变。在Defects4J、Epinions、一个受BWSN启发的检测时间工作负载、重复选择以及一个嵌入式RV32实现中，我们观察到不同的转变。在5%的预算下，一次交换细化增加了27行Chart代码，基线中位运行时间为11.3倍，而更深的搜索增加了5行Time代码，约为715倍。在Math上，CP-SAT在20%和40%预算下确认了全域最优性，并保留了较低预算的剩余空间。持久预处理重用首先在周期20时实现置信区间支持的速度提升，并在周期100时达到1.442倍。ModelSim显示了单独的位集宽度交叉。结果表明，策略非支配性依赖于工作负载和条件，支持机制感知的算法工程而非通用的策略排序。
英文摘要
Coverage-selection policies that optimize the same monotone objective can occupy different quality-runtime frontiers as workload scale, budget, repetition horizon, and execution substrate change. CAGE is a regime-aware algorithm-engineering framework that holds coverage semantics fixed through a shared bitset execution substrate and studies how the nondominated strategy set changes under controlled operating conditions. We separate intrinsic workload descriptors from measured strategy response, represent each condition by its empirical Pareto set, and identify regime transitions from changes in Pareto membership or statistically supported crossovers. Across Defects4J, Epinions, a BWSN-inspired time-to-detection workload, repeated selection, and an embedded RV32 realization, we observe distinct transitions. At a 5% budget, one-exchange refinement adds 27 Chart lines at 11.3x baseline median runtime, whereas deeper search adds five Time lines at roughly 715x. On Math, CP-SAT confirms full-universe optimality at 20% and 40% and residual lower-budget headroom. Persistent preprocessing reuse first achieves confidence-interval-supported speedup at horizon 20 and reaches 1.442x at horizon 100. ModelSim shows a separate bitset-width crossover. The results demonstrate that strategy nondominance is workload- and condition-dependent, supporting regime-aware algorithm engineering rather than a universal policy ranking.
发表机构
- University of Tehran（德黑兰大学）
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