MOA deploys LLM agents to detect recurring memory anti-patterns via profiling, synthesize static analyzers, and apply patches, reporting 42% heap and 11% binary-size reductions on OpenHarmony after finding over 10,000 issues.
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Data-access cost scales as N to the 1/4 in an abstract memory hierarchy for a class of applications.
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MOA: A Profiling-Guided LLM Framework for Memory-Optimization Automation at Codebase Scale
MOA deploys LLM agents to detect recurring memory anti-patterns via profiling, synthesize static analyzers, and apply patches, reporting 42% heap and 11% binary-size reductions on OpenHarmony after finding over 10,000 issues.
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The Fourth-Root Complexity of Data Movement
Data-access cost scales as N to the 1/4 in an abstract memory hierarchy for a class of applications.