Projects

SWEN

The SWEN Research Group at the University of L’Aquila actively participates in a wide range of projects at the international, national, and industrial levels. Our collaborations aim to address cutting-edge challenges in software development, bringing together academia and industry to innovate in areas such as model-driven engineering, software architecture, performance optimization, and more.

Through partnerships with leading research institutions, companies, and government bodies, our group contributes to groundbreaking research and technological advancements. These projects not only strengthen our expertise but also foster the exchange of knowledge across borders, benefiting both the scientific community and industry stakeholders. By tackling real-world problems, we strive to bridge the gap between theoretical research and practical application, driving the future of software engineering.

International Projects

National Projects

• CN-HPC PNRR Spoke9 (October 2022, September 2025)

HPC and Big Data, combined with appropriate models, methodologies, and algorithms, offer new opportunities to solve key challenges in smart cities and digital societies. These, in fact, are characterized by the confluence and interaction of different systems in the social, organizational and technological domains, which are difficult to solve through mere decomposition into simpler problems, and such as to require new approaches that can overcome this “complexity wall”.

Spoke aims to address this barrier by exploring new approaches that use and extend the concept of the “digital twin”. The goal is to create a faithful digital representation of the social and organizational structures of cities, communities, and their citizens, as well as the physical and virtual contexts in which they operate and interact, leveraging the digital traces of available “big data,” large-scale data analysis, artificial intelligence (AI) techniques, and new opportunities for advanced simulation made possible by ICSC’s HPC infrastructure.

Through digital twins, the Spoke intends to improve the ability to (i) replicate and understand the functioning and behaviors of our cities and societies, (ii) predict future evolutions, also in response to change, and (iii) support the testing and evaluation of the effects of policies, protocols, and scenarios aimed at changing the behavior of cities and communities.

• HALO (September 2023, September 2025)

This research project addresses the growing ethical concerns surrounding AI-enabled Autonomous Systems (AS) in an era where citizens interact daily with autonomous software systems in various settings, such as smart homes, mobile devices, and vehicles. While the European Union has implemented regulations to protect privacy, the project highlights a deeper threat to fundamental human rights, as AI systems challenge ethical values like fairness, dignity, and human control. The Ethics Guidelines for Trustworthy AI, established by the EU High-Level Expert Group on AI, emphasize that AI systems must respect the rule of law, align with ethical principles, keep humans in control, and remain robust and safe.

The project, HALO, aims to empower users to adjust the autonomy of AI systems to align with their ethical preferences. It proposes a dynamic software exoskeleton that allows users to express moral preferences, such as privacy or dignity, and to control how autonomy is distributed across AI components, software agents, and human users. HALO introduces a paradigm shift by offering customizable autonomy features and ethical-aware interactions, ensuring that AI systems behave in ways consistent with users' moral values while adhering to regulations and laws. This innovative approach enhances user control and trust in autonomous systems.

• BeT (September 2023 - September 2025)

The BeT (Behavior-enabled IoT) project focuses on improving the design and implementation of Internet of Behaviors (IoB) systems, which have emerged due to the increasing integration of IoT, AI, and human-centered technologies. The IoB trend, recognized by Gartner as crucial for businesses to navigate the post-pandemic world, involves collecting and analyzing human behaviors through IoT networks or social platforms to influence user actions. Companies like Amazon and Netflix already leverage IoB for personalized recommendations, and sectors like healthcare and insurance are also adopting these systems to enhance user experiences.

However, current IoB applications are often built on traditional IoT architectures in an unsystematic way, leading to inefficiencies and errors. The BeT project addresses this by proposing a reference architecture with AI components designed to analyze and predict human behavior, as well as metrics for optimizing both system performance (Quality of Service, QoS) and human experience (Quality of Experience, QoE). It introduces methods for modeling human behavior and detecting QoE-QoS conflicts, ensuring a dynamic, bi-causal connection between users and systems. BeT’s architecture enables systems to autonomously adapt to real-time human and system needs, with validation through real-world use cases, ensuring systematic, efficient, and human-centered IoB applications.

• RECHARGE (November 2023, November 2025)

The RECHARGE project addresses the challenge of automating performance testing in Continuous Integration and Deployment (CI/CD) pipelines by leveraging static analysis and search-based algorithms. Modern software systems often have non-functional requirements, such as energy efficiency for smartphones or precise timing for embedded systems, but performance issues are frequently neglected during testing, where the focus tends to be on software crashes or incorrect responses. This problem is particularly pronounced in CI/CD environments, where software is continuously re-deployed as changes are pushed.

RECHARGE proposes a novel framework to automate performance testing in CI/CD by introducing automated performance monitoring, which combines static analysis, regression testing optimization, and CI/CD processes to track software performance efficiently over time. It also integrates automated performance test generation, using both developer-crafted and AI-generated tests to identify performance regressions throughout the software lifecycle. Furthermore, the framework provides automated root cause analysis by extracting and analyzing change patterns that lead to performance regressions, helping to uncover the underlying causes and offering solutions to prevent or fix them.

The RECHARGE framework will be validated through practical use cases, including open-source systems and an industrial case study focused on performance analysis. This approach aims to enhance the automation and effectiveness of performance testing in CI/CD environments, ensuring more reliable and efficient software systems.

Industrial Projects