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Software frameworks and libraries are indispensable to today's software systems. As they evolve, it is often time-consuming for developers to keep their code up-to-date, so approaches have been proposed to facilitate this. Usually, these approaches cannot automatically identify change rules for one-replaced-by-many and many-replaced-by-one methods, and they trade o recall for higher precision using one or more experimentally-evaluated thresholds. The authors introduce AURA, a novel hybrid approach that combines call dependency and text similarity analyses to overcome these limitations.
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