SCENIC delivers a programmable 200G SmartNIC with offloaded protocol stacks, stream compute units, and full OS transparency that matches commercial performance for custom offloads like collective communication and GPU data partitioning.
InProceedings of the 16th International Conference on Mining Software Repositories(Montreal, Quebec, Canada)(MSR ’19)
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A new open labelled dataset from real district heating substations plus an evaluation framework with accuracy, reliability, and earliness metrics enables reproducible development of early fault detection methods.
A controlled eye-tracking study finds that code priority affects review time, cognitive load, and perceived quality but not reuse decisions, while author reputation changes visual attention patterns without altering performance or reuse choices.
AFGNN detects API misuses in Java code more effectively than prior methods by representing usage as graphs and clustering learned embeddings from self-supervised training.
CoCoMagic applies constrained cooperative co-evolution to metamorphic and differential testing to find up to 287% more distinct behavioral divergences in an end-to-end ADS than baseline search methods.
citing papers explorer
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SCENIC: Stream Computation-Enhanced SmartNIC
SCENIC delivers a programmable 200G SmartNIC with offloaded protocol stacks, stream compute units, and full OS transparency that matches commercial performance for custom offloads like collective communication and GPU data partitioning.
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Enabling Predictive Maintenance in District Heating Substations: A Labelled Dataset and Fault Detection Evaluation Framework based on Service Data
A new open labelled dataset from real district heating substations plus an evaluation framework with accuracy, reliability, and earliness metrics enables reproducible development of early fault detection methods.
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An Eye for Trust: An Exploration of Developers' Trust Perceptions Through Urgency and Reputation
A controlled eye-tracking study finds that code priority affects review time, cognitive load, and perceived quality but not reuse decisions, while author reputation changes visual attention patterns without altering performance or reuse choices.
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AFGNN: API Misuse Detection using Graph Neural Networks and Clustering
AFGNN detects API misuses in Java code more effectively than prior methods by representing usage as graphs and clustering learned embeddings from self-supervised training.
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Constrained Co-evolutionary Metamorphic Differential Testing for Autonomous Systems with an Interpretability Approach
CoCoMagic applies constrained cooperative co-evolution to metamorphic and differential testing to find up to 287% more distinct behavioral divergences in an end-to-end ADS than baseline search methods.