Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot

no code implementations • 13 Feb 2024 • Ionut Daniel Fagadau, Leonardo Mariani, Daniela Micucci, Oliviero Riganelli

For instance, developers can ask for new code directly from within their IDEs by writing natural language prompts, and integrated services based on generative AI, such as Copilot, immediately respond to prompts by providing ready-to-use code snippets.

Prompt Engineering

Cloud Failure Prediction with Hierarchical Temporal Memory: An Empirical Assessment

1 code implementation • 6 Oct 2021 • Oliviero Riganelli, Paolo Saltarel, Alessandro Tundo, Marco Mobilio, Leonardo Mariani

Hierarchical Temporal Memory (HTM) is an unsupervised learning algorithm inspired by the features of the neocortex that can be used to continuously process stream data and detect anomalies, without requiring a large amount of data for training nor requiring labeled data.

FILO: FIx-LOcus Localization for Backward Incompatibilities Caused by Android Framework Upgrades

no code implementations • 31 Dec 2020 • Marco Mobilio, Oliviero Riganelli, Daniela Micucci, Leonardo Mariani

Mobile operating systems evolve quickly, frequently updating the APIs that app developers use to build their apps.

Software Engineering