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• W2106935893 abstract "Predicting a sequence of upcoming function calls is important for optimizing programs written in modern managed languages (e.g., Java, Javascript, C#.) Existing function call predictions are mainly built on statistical patterns, suitable for predicting a single call but not a sequence of calls. This paper presents a new way to enable call sequence prediction, which exploits program structures through Probabilistic Calling Automata (PCA), a new program representation that captures both the inherent ensuing relations among function calls, and the probabilistic nature of execution paths. It shows that PCA-based prediction outperforms existing predictions, yielding substantial speedup when being applied to guide Just-In-Time compilation. By enabling accurate, efficient call sequence prediction for the first time, PCA-based predictors open up many new opportunities for dynamic program optimizations." @default.
• W2106935893 created "2016-06-24" @default.
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• W2106935893 date "2014-10-15" @default.
• W2106935893 modified "2023-10-18" @default.
• W2106935893 title "Call sequence prediction through probabilistic calling automata" @default.
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• W2106935893 doi "https://doi.org/10.1145/2660193.2660221" @default.
• W2106935893 hasPublicationYear "2014" @default.
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