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: "towards concolic testing for hybrid systems"
  Abstract: Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate whether we can combine random sampling and symbolic execution in order to effectively verify hybrid systems. We identify a sufficient condition under which such a combination is more effective than random sampling. Furthermore, we analyze different strategies of combining random sampling and symbolic execution and propose an algorithm which allows us to dynamically switch between them so as to reduce the overall cost. Our method has been implemented as a web-based checker named HyChecker. HyChecker has been evaluated with benchmark hybrid systems and a water treatment system in order to test its effectiveness.

Connected through hyperedge HE-1 (induced by source paper "learning guided network fuzzing for testing cyber physical system defences"):
  with members:
    - "detecting zero day controller hijacking attacks on the power grid with enhanced deep learning"
    - "assessing the effectiveness of attack detection at a hackfest on industrial control systems"
    - "learning from mutants using code mutation to learn and monitor invariants of a cyber physical system"
    - "anomaly detection for a water treatment system using unsupervised machine learning"
    - "log based anomaly detection of cps using a statistical method"
    - "a formal approach to cyber physical attacks"
    - "towards learning and verifying invariants of cyber physical systems by code mutation"
    - "api design for machine learning software experiences from the scikit learn project"

Connected through hyperedge HE-2 (induced by source paper "learning from mutants using code mutation to learn and monitor invariants of a cyber physical system"):
  with members:
    - "anomaly detection for a water treatment system using unsupervised machine learning"
    - "log based anomaly detection of cps using a statistical method"
    - "towards learning and verifying invariants of cyber physical systems by code mutation"

Connected through hyperedge HE-3 (induced by source paper "toward verifying a water treatment system"):
  with members:
    - "should we learn probabilistic models for model checking a new approach and an empirical study"
    - "delta complete analysis for bounded reachability of hybrid systems"
    - "learning markov decision processes for model checking"

Connected through hyperedge HE-4 (induced by source paper "towards learning and verifying invariants of cyber physical systems by code mutation"):
  with members:
    - "should we learn probabilistic models for model checking a new approach and an empirical study"

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.SE(Software Engineering)