This approach involves capturing the variabilities through feature models, designing an automated framework to support the analysis, and developing use cases.

It analyzes the challenges that an automated pilot agent must face when tracking events in this environment. This analysis reveals three new issues that have ...

This approach involves capturing the variabilities through feature models, designing an automated framework to support the analysis, and developing use cases.

Sep 27, 2023 · Towards Automated Variability-Aware Machine-Learning-Based Modeling Analysis. ... A Variability-Aware Design Approach to the Data Analysis ...

Nov 23, 2023 · to automate the various phases of the data analysis process. Some heuristics have been proposed to capture criteria for choosing particular ...

This work proposes a methodological framework for a variability-aware design of databases, whereby this latter is henceforth devised as a Software Product ...

May 6, 2020 · We exploit a polynomial regression technique to model the operation pa- rameters, namely the Wait Buffer and batch sizes with the performance ...

Reliability-and variability-aware design-technology co-optimization (RV-aware DTCO) becomes indispensable with advanced nodes. However, four key issues ...

White-Box Analysis over Machine Learning: Modeling ... machine-learning-based approach to construct influence models for robotic software. ... variability-aware ...

In this context, OpenSpace will develop variability-aware test methods which play a major role in the context of software product lines. ... The share of testing ...