@article{62973,
  abstract     = {{Large Language Models (LLMs) are increasingly being explored for their potential in software engineering, particularly in static analysis tasks. In this study, we investigate the potential of current LLMs to enhance call-graph analysis and type inference for Python and JavaScript programs. We empirically evaluated 24 LLMs, including OpenAI's GPT series and open-source models like LLaMA and Mistral, using existing and newly developed benchmarks. Specifically, we enhanced TypeEvalPy, a micro-benchmarking framework for type inference in Python, with auto-generation capabilities, expanding its scope from 860 to 77,268 type annotations for Python. Additionally, we introduced SWARM-CG and SWARM-JS, comprehensive benchmarking suites for evaluating call-graph construction tools across multiple programming languages.
 Our findings reveal a contrasting performance of LLMs in static analysis tasks. For call-graph generation, traditional static analysis tools such as PyCG for Python and Jelly for JavaScript consistently outperform LLMs. While advanced models like mistral-large-it-2407-123b and gpt-4o show promise, they still struggle with completeness and soundness in call-graph analysis across both languages. In contrast, LLMs demonstrate a clear advantage in type inference for Python, surpassing traditional tools like HeaderGen and hybrid approaches such as HiTyper. These results suggest that, while LLMs hold promise in type inference, their limitations in call-graph analysis highlight the need for further research. Our study provides a foundation for integrating LLMs into static analysis workflows, offering insights into their strengths and current limitations.}},
  author       = {{Shivarpatna Venkatesh, Ashwin Prasad and Sunil, Rose and Sabu, Samkutty and Mir, Amir M. and Reis, Sofia and Bodden, Eric}},
  journal      = {{Empirical Software Engineering}},
  number       = {{6}},
  publisher    = {{Springer}},
  title        = {{{An Empirical Study of Large Language Models for Type and Call Graph Analysis in Python and JavaScript}}},
  doi          = {{10.48550/ARXIV.2410.00603}},
  volume       = {{30}},
  year         = {{2025}},
}

@inproceedings{63054,
  author       = {{Apostolo, Guilherme Henrique and Bauszat, Pablo and Nigade, Vinod and Bal, Henri E. and Wang, Lin}},
  booktitle    = {{Proceedings of the 31st Annual International Conference on Mobile Computing and Networking (MobiCom)}},
  location     = {{Hong Kong, China}},
  publisher    = {{ACM}},
  title        = {{{Uirapuru: Timely Video Analytics for High-Resolution Steerable Cameras on Edge Devices}}},
  doi          = {{10.1145/3680207.3765260}},
  year         = {{2025}},
}

@article{63057,
  author       = {{Pei, Qiangyu and Yuan, Yongjie and Hu, Haichuan and Wang, Lin and Zhang, Dong and Yan, Bingheng and Yu, Chen and Liu, Fangming}},
  issn         = {{2377-3782}},
  journal      = {{IEEE Transactions on Sustainable Computing}},
  number       = {{4}},
  pages        = {{804--819}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Working Smarter Not Harder: Hybrid Cooling for Deep Learning in Edge Datacenters}}},
  doi          = {{10.1109/tsusc.2025.3542563}},
  volume       = {{10}},
  year         = {{2025}},
}

@inproceedings{63056,
  author       = {{Wu, Jing and Wang, Lin and Deng, Quanfeng and Yu, Chen and Zhang, Dong and Yan, Bingheng and Liu, Fangming}},
  booktitle    = {{2025 IEEE International Parallel and Distributed Processing Symposium (IPDPS)}},
  location     = {{Milan, Italy}},
  publisher    = {{IEEE}},
  title        = {{{It Takes Two to Tango: Serverless Workflow Serving via Bilaterally Engaged Resource Adaptation}}},
  doi          = {{10.1109/ipdps64566.2025.00012}},
  year         = {{2025}},
}

@article{63053,
  author       = {{Hernández, Carlos and Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Cuate, Oliver and Trautmann, Heike and Schütze, Oliver}},
  journal      = {{IEEE Transactions on Evolutionary Computation}},
  keywords     = {{Optimization, Evolutionary computation, Hands, Proposals, Convergence, Computational efficiency, Artificial intelligence, Accuracy, Approximation algorithms, Aerospace electronics, Multi-objective optimization, evolutionary algorithms, nearly optimal solutions, multimodal optimization, archiving, continuation}},
  pages        = {{1--1}},
  title        = {{{An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization}}},
  doi          = {{10.1109/TEVC.2025.3637276}},
  year         = {{2025}},
}

@inproceedings{63058,
  author       = {{Ghafouri, Saeid and Razavi, Kamran and Salmani, Mehran and Sanaee, Alireza and Botran, Tania Lorido and Wang, Lin and Doyle, Joseph and Jamshidi, Pooyan}},
  booktitle    = {{Companion of the 16th ACM/SPEC International Conference on Performance Engineering}},
  publisher    = {{ACM}},
  title        = {{{IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency}}},
  doi          = {{10.1145/3680256.3721266}},
  year         = {{2025}},
}

@unpublished{63403,
  abstract     = {{Stateful signatures like the NIST standardized signature schemes LMS and XMSS provide an efficient and mature realization of post-quantum secure signature schemes. They are recommended for long-term use cases like e.g. firmware signing. However, stateful signature schemes require to properly manage a so-called state. In stateful signature schemes like LMS and XMSS, signing keys consist of a set of keys of a one-time signature scheme and it has to be guaranteed that each one-time key is used only once. This is done by updating a state in each signature computation, basically recording which one-time keys have already been used. While this is straightforward in centralized systems, in distributed systems like secure enclaves consisting of e.g. multiple hardware security modules (HSMs) with limited communication keeping a distributed state that at any point in time is consistent among all parties involved presents a challenge. This challenge is not addressed by the current standardization processes. 
In this paper we present a security model for the distributed key management of post-quantum secure stateful signatures like XMSS and LMS. We also present a simple, efficient, and easy to implement protocol proven secure in this security model, i.e. the protocol guarantees at any point in time a consistent state among the parties in a distributed system, like a distributed security enclave. The security model is defined in the universal composabilty (UC) framework by Ran Canetti by providing an ideal functionality for the distributed key management for stateful signatures. Hence our protocol remains secure even if arbitrarily composed with other instances of the same or other protocols, a necessity for the security of distributed key management protocols. Our main application are security enclaves consisting of HSMs, but the model and the protocol can easily be adapted to other scenarios of distributed key management of stateful signature schemes.}},
  author       = {{Blömer, Johannes and Bröcher, Henrik and Krummel, Volker and Porzenheim, Laurens Alexander}},
  keywords     = {{distributed state, hash-based signature, stateful hash-based signature, universal composability, secure enclave}},
  pages        = {{22}},
  title        = {{{Secure Distributed State Management for Stateful Signatures with a Practical and Universally Composable Protocol}}},
  year         = {{2025}},
}

@inbook{63507,
  author       = {{Pandit, Gaurav and Röder, Michael and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783031945748}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Evaluating Approximate Nearest Neighbour Search Systems on Knowledge Graph Embeddings}}},
  doi          = {{10.1007/978-3-031-94575-5_4}},
  year         = {{2025}},
}

@inbook{63543,
  abstract     = {{<jats:title>Abstract</jats:title>
          <jats:p>Current megatrends are influencing industrial production and leading to ever shorter innovation cycles. The resulting fast pace of production requirements requires an accelerated development of production systems and an associated increase in efficiency in factory planning. Due to its knowledge-intensive activities, rough factory planning promises great potential to be supported in its activities by innovative technologies such as artificial intelligence. However, industrial companies face the challenge to recognize the potential of artificial intelligence (AI) in rough planning and to evaluate possible applications in their business context. As a result, a systematic approach for analyzing AI potential in rough factory planning was developed as part of this work. The system includes a procedural model and several artefacts used in it, which support the identification and evaluation of AI potential in organizations. This approach not only streamlines the planning process but also aligns with sustainable manufacturing principles by enhancing resource efficiency, promoting intelligent system design, and fostering innovation in product development and manufacturing processes.</jats:p>}},
  author       = {{Kürpick, Dominik and Disselkamp, Jan-Philipp and Lick, Jonas and Hovemann, Aschot and Dumitrescu, Roman}},
  booktitle    = {{Lecture Notes in Mechanical Engineering}},
  isbn         = {{9783031938900}},
  issn         = {{2195-4356}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Systematic AI Potential Analysis for Sustainable Rough Factory Planning}}},
  doi          = {{10.1007/978-3-031-93891-7_84}},
  year         = {{2025}},
}

@inproceedings{63542,
  abstract     = {{<jats:title>ABSTRACT:</jats:title><jats:p>This paper presents the MBSE-Graph-RAG framework to address key challenges in Model-Based Systems Engineering (MBSE). Traditional MBSE tools suffer from usability barriers, limited accessibility, and integration challenges. By combining knowledge graphs with Retrieval-Augmented Generation (RAG), the proposed framework enables AI-Augmented engineering through natural language interactions and automated system architecture generation. A systematic literature review establishes a solid research foundation, identifying gaps in AI-assisted MBSE. Key contributions include a structured MBSE-Graph interface, improved usability via Large Language Models (LLMs), and automated graph construction aligned with SysML. A proof-of-concept demonstrates the potential of this approach to enhance MBSE by reducing complexity, improving data accessibility, and supporting engineering collaboration.</jats:p>}},
  author       = {{Hanke, Fabian and Bita, Isaac Mpidi and von Heißen, Oliver  and Weller, Julian and Hovemann, Aschot and Dumitrescu, Roman}},
  booktitle    = {{Proceedings of the Design Society}},
  issn         = {{2732-527X}},
  pages        = {{439--448}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{AI-augmented systems engineering: conceptual application of retrieval-augmented generation for model-based systems engineering graph}}},
  doi          = {{10.1017/pds.2025.10058}},
  volume       = {{5}},
  year         = {{2025}},
}

@inproceedings{63537,
  author       = {{Dondorf, Verena  and Kokilanathan, Kitrujan  and Graunke, Jannis  and Hobscheidt, Daniela  and Dumitrescu, Roman}},
  booktitle    = {{Vorausschau und Technologieplanung}},
  editor       = {{Hölzle, Katharina and Dumitrescu, Roman}},
  isbn         = {{978-3-947647-50-7}},
  location     = {{Berlin}},
  pages        = {{137}},
  publisher    = {{Heinz Nixdorf Institut}},
  title        = {{{Akzeptanz von KI-Lösungen: Analyse der Einflussfaktoren und ihre Relevanz für Mitarbeitende}}},
  volume       = {{431}},
  year         = {{2025}},
}

@inproceedings{63538,
  author       = {{Dohmann, Friederike  and Hobscheidt, Daniela  and Vy Vo, Gia  and Kürpick, Christian  and Dumitrescu, Roman}},
  booktitle    = {{Vorausschau und Technologieplanung}},
  editor       = {{Hölzle, Katharina and Dumitrescu, Roman}},
  isbn         = {{978-3-947647-50-7}},
  location     = {{Berlin}},
  pages        = {{299}},
  title        = {{{Nachhaltigkeit als strategischer Erfolgsfaktor–ein Framework für die unternehmerische Nachhaltigkeitstransformation}}},
  volume       = {{431}},
  year         = {{2025}},
}

@inproceedings{63535,
  author       = {{Bernijazov, Ruslan and Rasor, Rik and Dumitrescu, Roman}},
  booktitle    = {{Tag des Systems Engineering 2025: Tagungsband Salzburg, 29.-31. Oktober 2025}},
  location     = {{Salzburg}},
  pages        = {{131}},
  title        = {{{Können LLMs Model-based Systems Engineering ewertung der M SE-Fähigkeiten von LLMs}}},
  volume       = {{24}},
  year         = {{2025}},
}

@inproceedings{63540,
  author       = {{Könemann, Ulf and Niemeyer, Marcel and Schierbaum, Anja and Dumitrescu, Roman}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{765--770}},
  publisher    = {{Elsevier BV}},
  title        = {{{A serious game to introduce Systems Engineering in interdisciplinary teams}}},
  doi          = {{10.1016/j.procir.2025.02.195}},
  volume       = {{134}},
  year         = {{2025}},
}

@inproceedings{63536,
  author       = {{Könemann, Ulf and Roby, Derik and Schierbaum, Anja and Dumitrescu, Roman}},
  booktitle    = {{Tag des Systems Engineering 2025: Tagungsband Salzburg, 29.-31. Oktober 2025}},
  location     = {{Salzburg}},
  pages        = {{184}},
  title        = {{{Toward a GenAI-Supported Systems Engineering Competency Assessment}}},
  volume       = {{24}},
  year         = {{2025}},
}

@inproceedings{63539,
  author       = {{Wyrwich, Fabian and Hovemann, Aschot and Dumitrescu, Roman}},
  booktitle    = {{Tag des Systems Engineering 2025}},
  location     = {{Salzburg}},
  title        = {{{Auf dem Weg zu einem fähigkeitsbasierten Digital Engineering Zielbild}}},
  year         = {{2025}},
}

@inproceedings{63545,
  abstract     = {{<jats:title>ABSTRACT:</jats:title><jats:p>Cyber-physical production systems (CPPS) are responsible for a significant portion of manufacturers’ carbon emissions. Since 80% of product-related environmental impacts are determined at the design stage, there is a need for CPPS manufacturers to focus on decarbonization at the design stage. To date, there is a lack of design-for-decarbonization guidance for CPPS. This paper proposes a procedural framework for the effective selection of decarbonization measures for the design of CPPS. A Decarbonization Wheel is developed to establish a product-specific decarbonization strategy. This tool is linked to a catalogue of decarbonization measures. A measure prioritization logic provides a structure for systematizing selected measures. The framework is validated in the case of an intelligent industrial control valve.</jats:p>}},
  author       = {{Schreiner, Nick and Cowen, Adam and Volling, Thomas and Dumitrescu, Roman}},
  booktitle    = {{Proceedings of the Design Society}},
  issn         = {{2732-527X}},
  pages        = {{1295--1304}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Design-for-decarbonization: a framework for decarbonizing cyber-physical production systems at the design stage}}},
  doi          = {{10.1017/pds.2025.10143}},
  volume       = {{5}},
  year         = {{2025}},
}

@inproceedings{63547,
  author       = {{Humpert, Lynn and Graunke, Jannis and Lewandowski, Lena and Schierbaum, Anja and Dumitrescu, Roman}},
  booktitle    = {{2025 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE)}},
  publisher    = {{IEEE}},
  title        = {{{Implementation of a web-based support platform for validation using system architecture in the B2B sector}}},
  doi          = {{10.1109/rasse64831.2025.11315318}},
  year         = {{2025}},
}

@inproceedings{63548,
  author       = {{Grigoryan, Khoren and Martin, Lucas and Lamarz, Jessica and Fichtler, Timm and Hohn, Bennett and Asmar, Laban and Kühn, Arno and Dumitrescu, Roman}},
  booktitle    = {{Procedia CIRP}},
  issn         = {{2212-8271}},
  pages        = {{838--843}},
  publisher    = {{Elsevier BV}},
  title        = {{{Product Management: Tasks, Roles, and the Importance of Data}}},
  doi          = {{10.1016/j.procir.2025.08.143}},
  volume       = {{136}},
  year         = {{2025}},
}

@inproceedings{63546,
  author       = {{Trienens, Malte and Schreiner, Nick and Hovemann, Aschot and Dumitrescu, Roman}},
  booktitle    = {{2025 IEEE European Technology and Engineering Management Summit (E-TEMS)}},
  publisher    = {{IEEE}},
  title        = {{{Industry Perspectives on the Digital Product Passport: A Guide to Sustainable Value Chains From an Engineering Perspective}}},
  doi          = {{10.1109/e-tems64751.2025.11239259}},
  year         = {{2025}},
}