Marin Litoiu

Professor, EECS Department
School of IT, LAPS
Executive and Board Member, IC@L
Graduate Program Director, IST
Scientific Director, DITA

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2023 – 2024 Research Highlights

Software Engineering for Adaptive Software Systems.

The goal of the program is to researches methods, tools and platforms that make large software systems more versatile, resilient, energy-efficient, self-healing or self-optimizing.  In the past year, working with partner companies and collaborators, we focused performance and privacy of large-scale systems, including Internet of Things applications deployed on cloud environments.  We proposed and evaluated architectures and methods to adjust performance and privacy at runtime by tuning the platform, infrastructure, and application services.

Selected Publication

• Closing the Loop: Building Self-Adaptive Software for Continuous Performance Engineering. M. Litoiu. Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024.
• Distributed Governance for Sharing of Big Data. M. Litoiu & M. Shtern. US Patent 12,032,714, 2024.
• Employing Software Diversity in Cloud Microservices to Engineer Reliable and Performant Systems. N. Akhtarian, H. Khazaei, & M. Litoiu. 2024 IEEE International Conference on Autonomic Computing and Self, 2024.
• KubePlaybook: A Repository of Ansible Playbooks for Kubernetes Auto-Remediation with LLMs. Z. Namrud, K. Sarda, M. Litoiu, L. Shwartz, & I. Watts. Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024.
• Leveraging Large Language Models for the Auto-Remediation of Microservice Applications: An Experimental Study. K. Sarda, Z. Namrud, M. Litoiu, L. Shwartz, & I. Watts. Companion Proceedings of the 32nd ACM International Conference on the, 2024.