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: "fully automated shape analysis based on forest automata"
  Abstract: Forest automata (FA) have recently been proposed as a tool for shape analysis of complex heap structures. FA encode sets of tree decompositions of heap graphs in the form of tuples of tree automata. In order to allow for representing complex heap graphs, the notion of FA allowed one to provide user-defined FA (called boxes) that encode repetitive graph patterns of shape graphs to be used as alphabet symbols of other, higher-level FA. In this paper, we propose a novel technique of automatically learning the FA to be used as boxes that avoids the need of providing them manually. Further, we propose a significant improvement of the automata abstraction used in the analysis. The result is an efficient, fully-automated analysis that can handle even as complex data structures as skip lists, with the performance comparable to state-of-the-art fully-automated tools based on separation logic, which, however, specialise in dealing with linked lists only.

Connected through hyperedge HE-1 (induced by source paper "pointer life cycle types for lock free data structures with memory reclamation"):
  with members:
    - "hyaline fast and transparent lock free memory reclamation"
    - "decoupling lock free data structures from memory reclamation for static analysis"
    - "safe deferred memory reclamation with types"
    - "reasoning about tso programs using reduction and abstraction"
    - "reclaiming memory for lock free data structures there has to be a better way"
    - "proving linearizability using forward simulations"
    - "verifying concurrent stacks by divergence sensitive bisimulation"
    - "effect summaries for thread modular analysis"

Connected through hyperedge HE-2 (induced by source paper "compositional verification of heap manipulating programs through property guided learning"):
  with members:
    - "sling using dynamic analysis to infer program invariants in separation logic"
    - "concolic testing heap manipulating programs"
    - "enhancing symbolic execution of heap based programs with separation logic for test input generation"
    - "gated graph sequence neural networks"
    - "learning universally quantified invariants of linear data structures"
    - "cpachecker a tool for configurable software verification"
    - "the octagon abstract domain"

Connected through hyperedge HE-3 (induced by source paper "reducing nondeterministic tree automata by adding transitions"):
  with members:
    - "efficient reduction of nondeterministic automata with application to language inclusion testing"
    - "reduction of nondeterministic tree automata"
    - "advanced automata minimization"

Connected through hyperedge HE-4 (induced by source paper "reduction of nondeterministic tree automata"):
  with members:
    - "advanced automata minimization"
    - "simulations and antichains for efficient handling of finite automata"

Connected through hyperedge HE-5 (induced by source paper "shape and content incorporating domain knowledge into shape analysis"):
  with members:
    - "on the concept of variable roles and its use in software analysis"
    - "the complexity of reasoning with cardinality restrictions and nominals in expressive description logics"

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.LO(Logic in Computer Science)