5 papers
Property-Driven Synthetic Data Engineering for Data-Scarce Software Systems: Reflections from the Breast Cancer Domain
Aurora Francesca Zanenga, Andrea Bombarda, Marsha Chechik +4
Modern software systems increasingly depend on data for analysis, prediction, testing, and decision-making. Yet many important domains, including medicine, safety-critical systems,…
Engineering Resource-constrained Software Systems with DNN Components: a Concept-based Pruning Approach
Federico Formica, Andrea Rota, Aurora Francesca Zanenga +4
Deep Neural Networks (DNNs) are widely used by engineers to solve difficult problems that require predictive modeling from data. However, these models are often massive, with milli…
Ensembles-based Feature Guided Analysis
Federico Formica, Stefano Gregis, Andrea Rota +3
Recent Deep Neural Networks (DNN) applications ask for techniques that can explain their behavior. Existing solutions, such as Feature Guided Analysis (FGA), extract rules on their…
Feature-Guided Analysis of Neural Networks: A Replication Study
Federico Formica, Stefano Gregis, Aurora Francesca Zanenga +3
Understanding why neural networks make certain decisions is pivotal for their use in safety-critical applications. Feature-Guided Analysis (FGA) extracts slices of neural networks…
Failure Modes and Effects Analysis: An Experience from the E-Bike Domain
Andrea Bombarda, Federico Conti, Marcello Minervini +2
Software failures can have catastrophic and costly consequences. Functional Failure Mode and Effects Analysis (FMEA) is a standard technique used within Cyber-Physical Systems (CPS…