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: "narcissus deriving correct by construction decoders and encoders from binary formats"
  Abstract: Every injective function has an inverse, although constructing the inverse for a particular injective function can be quite tricky. One common instance of inverse-function pairs is the binary encoders and decoders used to convert in-memory data into and out of a structured binary format for network communication. Ensuring that a given decoder is a proper inverse of the original encoder is particularly important, as any error has the potential to introduce security vulnerabilities or to corrupt or lose data in translation. #R##N#In this paper, we present a synthesis framework, Narcissus, that eliminates both the tedium and the potential for error in building the inverse of a binary encoder. The starting point of the process is a binary format, expressed as a functional program in the nondeterminism monad, that precisely captures all the valid binary encodings of an arbitrary datatype instance. From this specification, Narcissus synthesizes a decoder that is guaranteed to be the inverse of this relation, drawing on an extensible set of decoding strategies to construct the implementation. Each decoder is furthermore guaranteed to detect malformed encodings by failing on inputs not included in this relation. The derivation is carried out inside the Coq proof assistant and produces a proof trail certifying the correctness of the synthesized decoder. We demonstrate the utility of our framework by deriving and evaluating the performance of decoders for all packet formats used in a standard network stack.

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.PL(Programming Languages)