Coma704
发表于 2025-3-25 04:45:38
DeepClone: Modeling Clones to Generate Code Predictionsarn from a large code corpus, and generates code tokens using the model learned. We have quantitatively evaluated our solution to assess (1) our model’s quality and its accuracy in token prediction, and (2) its performance and effectiveness in clone method prediction. We also discuss various application scenarios for our approach.
Peculate
发表于 2025-3-25 08:36:11
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Infiltrate
发表于 2025-3-25 13:00:23
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GIST
发表于 2025-3-25 19:17:00
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MUTE
发表于 2025-3-25 20:26:14
A Hybrid Approach Based on Reuse Techniques for Autonomic Adaptation of Business Processesnd rules as reuse techniques. Our solution is implemented as an adaptation engine that instantiates the MAPE-K control loop and that can be connected to any BPMN-based BPMS using appropriate adapters. Our adaptation engine is therefore reusable. Finally, we demonstrate the advantages and feasibility
借喻
发表于 2025-3-26 01:44:05
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不来
发表于 2025-3-26 05:33:59
15 Years of Reuse Experience in Evolutionary Prototyping for the Defense Industrycomponent interfaces transparently in multiple prototypes, whatever the underlying implementation solutions. This kind of reuse spans prototypes and final products which are deployed on different execution platforms. We reuse non-component legacy software that we integrate in our component architect
Hiatus
发表于 2025-3-26 09:22:50
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耕种
发表于 2025-3-26 16:02:25
Learning to Recommend Trigger-Action Rules for End-User Developmenter-action knowledge graph (.) for modeling the relationships among IoT devices/ services, triggers, and actions; and (2) it learns to recommend trigger-action rules by extracting features from . and training a ranking model. We evaluate . against . (a state-of-the-art approach) on real user data col
GILD
发表于 2025-3-26 20:08:46
AndroLib: Third-Party Software Library Recommendation for Android Applications. We aim at guiding the search process towards the best trade-off three objectives to be optimized (.) maximize libraries historical co-usage, (.) maximize libraries functional diversity, and (.) maximize libraries reuse from highly rated apps. We conduct an empirical experiment to evaluate our appr