DEEP-SE
Welcome to the DEpendable Evolvable Pervasive Software Engineering (DEEP-SE) team at the Department of Electronics, Information Science and Bioengineering (DEIB) at Politecnico di Milano.
About Us
The DEEP-SE team conducts research on methods, techniques, tools, and frameworks for the design, development, and verification of complex software systems. By complex software we mean those systems that can be characterized, in varying degrees and flavors, as distributed, pervasive, adaptive, reconfigurable, dynamic, and critical. The pursued research activities encompass a variety of aspects of such systems, ranging from modeling and analysis issues in the early phases of their development, to issues related to their implementation and runtime management and optimization.
The team also investigates the economic and strategic impact of software on industry and society in general. Formal languages and techniques for the modeling and verification of the target applications play a central role in the research activity of the team. Most of the research activities eventually lead to software prototypes and experimentation, some of which are available as open-source software. Yet, various members of the team are also committed to methodological and theoretical investigation.
π "Tabular Reinforcement Learning Methods for Artificial Intelligence Tasks Offloading in Smart Eye-Wears" by A.Kambale, H.Sedghani, @f2_filippini, @g_verticale, @DaniloArdagna just got accepted on ACM Transactions on Autonomous & Adaptive Systems!
πRead
β οΈ "How Toxic Can You Get? Search-based Toxicity Testing for Large Language Models" has been accepted on IEEE Transactions on Software Engineering!! π Congrats @simocorbo, L. Bancale, V. De Gennaro, @livia_lestingi, V. Scotti, @matteocamilli π
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π "Federated Reinforcement Learning for Runtime Optimization of AI Applications in Smart Eyewears" by H. Sedghani, A. Wamuhindo Kambale, F. Filippini, F. Palermo, D. Trojaniello, @ardagna_danilo was also accepted at the #MASCOTS2025 Way to 6G Workshop! π