human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "facilitating rapid prototyping in the oodida data analytics platform via active code replacement"
  Abstract: OODIDA (On-board/Off-board Distributed Data Analytics) is a platform for distributing and executing concurrent data analysis tasks. It targets a fleet of reference vehicles in the automotive industry and has a particular focus on rapid prototyping. Its underlying message-passing infrastructure has been implemented in Erlang/OTP, but the external applications for user interaction and carrying out data analysis tasks use a language-independent JSON interface. These applications are primarily implemented in Python. A data analyst interacting with OODIDA uses a Python library. The bulk of the data analytics tasks are performed by clients (on-board), while a central server performs supplementary tasks (off-board). OODIDA can be automatically packaged and deployed, which necessitates restarting parts of the system, or all of it. This is potentially disruptive. To address this issue, we added the ability to execute user-defined Python modules on both the client and the server, which can be replaced without restarting any part of the system. Modules can even be swapped between iterations of an ongoing assignment. This facilitates use cases such as iterative A/B testing of machine learning algorithms or deploying experimental algorithms on-the-fly. Active-code replacement is a key feature of our system as well as an example of interoperability between a functional and a non-functional programming language.

Connected through hyperedge HE-1 (induced by source paper "active code replacement in the oodida data analytics platform"):
  with members:
    - "oodida on board off board distributed data analytics for connected vehicles"
    - "functional federated learning in erlang ffl erl"
    - "communication efficient learning of deep networks from decentralized data"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DC(Distributed, Parallel, and Cluster Computing)