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: "distributed testing of excluded subgraphs"
  Abstract: We study property testing in the context of distributed computing, under the classical CONGEST model. It is known that testing whether a graph is triangle-free can be done in a constant number of rounds, where the constant depends on how far the input graph is from being triangle-free. We show that, for every connected 4-node graph H, testing whether a graph is H-free can be done in a constant number of rounds too. The constant also depends on how far the input graph is from being H-free, and the dependence is identical to the one in the case of testing triangles. Hence, in particular, testing whether a graph is K_4-free, and testing whether a graph is C_4-free can be done in a constant number of rounds (where K_k denotes the k-node clique, and C_k denotes the k-node cycle). On the other hand, we show that testing K_k-freeness and C_k-freeness for k>4 appear to be much harder. Specifically, we investigate two natural types of generic algorithms for testing H-freeness, called DFS tester and BFS tester. The latter captures the previously known algorithm to test the presence of triangles, while the former captures our generic algorithm to test the presence of a 4-node graph pattern H. We prove that both DFS and BFS testers fail to test K_k-freeness and C_k-freeness in a constant number of rounds for k>4.

Connected through hyperedge HE-1 (induced by source paper "distributed testing of graph isomorphism in the congest model"):
  with members:
    - "distributed detection of cliques in dynamic networks"
    - "property testing of planarity in the congest model"
    - "distributed triangle detection via expander decomposition"
    - "detecting cliques in congest networks"
    - "distributed subgraph detection"
    - "fooling views a new lower bound technique for distributed computations under congestion"
    - "distributed detection of cycles"
    - "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model"

Connected through hyperedge HE-2 (induced by source paper "distributed detection of cliques in dynamic networks"):
  with members:
    - "fast and simple deterministic algorithms for highly dynamic networks"
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "local distributed algorithms in highly dynamic networks"
    - "distributed triangle detection via expander decomposition"
    - "improved algorithms for fully dynamic maximal independent set"
    - "detecting cliques in congest networks"
    - "distributed subgraph detection"

Connected through hyperedge HE-3 (induced by source paper "property testing of planarity in the congest model"):
  with members:
    - "minor excluded network families admit fast distributed algorithms"
    - "fiding forbidden minors in sublinear time a o n 1 2 o 1 query one sided tester for minor closed properties on bounded degree graphs"
    - "distributed subgraph detection"
    - "testing bounded arboricity"
    - "a sublinear tester for outerplanarity and other forbidden minors with one sided error"
    - "distributed detection of cycles"
    - "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model"
    - "distributed property testing for subgraph freeness revisited"

Connected through hyperedge HE-4 (induced by source paper "fooling views a new lower bound technique for distributed computations under congestion"):
  with members:
    - "symmetry breaking in the congest model time and message efficient algorithms for ruling sets"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "tight bounds for distributed graph computations"
    - "a time and message optimal distributed algorithm for minimum spanning trees"
    - "fast distributed algorithms for testing graph properties"
    - "distributed construction of purely additive spanners"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"

Connected through hyperedge HE-5 (induced by source paper "on the multiparty communication complexity of testing triangle freeness"):
  with members:
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"
    - "a hybrid sampling scheme for triangle counting"
    - "fast distributed algorithms for testing graph properties"
    - "dynamic graph stream algorithms in o n space"
    - "approximately counting triangles in sublinear time"
    - "algebraic methods in the congested clique"
    - "optimal principal component analysis in distributed and streaming models"
    - "communication lower bounds for statistical estimation problems via a distributed data processing inequality"

Connected through hyperedge HE-6 (induced by source paper "triangle finding and listing in congest networks"):
  with members:
    - "tight bounds for distributed graph computations"
    - "fast distributed algorithms for testing graph properties"
    - "algebraic methods in the congested clique"
    - "fast partial distance estimation and applications"
    - "almost tight distributed minimum cut algorithms"
    - "large cuts with local algorithms on triangle free graphs"
    - "distributed approximation algorithms for weighted shortest paths"
    - "distributed minimum cut approximation"

Connected through hyperedge HE-7 (induced by source paper "deterministic subgraph detection in broadcast congest"):
  with members:
    - "distributed subgraph detection"
    - "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model"
    - "distributed property testing for subgraph freeness revisited"
    - "tight bounds for distributed graph computations"
    - "fast distributed algorithms for testing graph properties"
    - "algebraic methods in the congested clique"
    - "tri tri again finding triangles and small subgraphs in a distributed setting"
    - "the locality of distributed symmetry breaking"

Connected through hyperedge HE-8 (induced by source paper "distributed detection of cycles"):
  with members:
    - "survey of distributed decision"
    - "fast distributed algorithms for testing graph properties"
    - "a hierarchy of local decision"
    - "randomized distributed decision"
    - "finding cycles and trees in sublinear time"
    - "distributed discovery of large near cliques"

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)