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: "active learning of input grammars"
  Abstract: Knowing the precise format of a program's input is a necessary prerequisite for systematic testing. Given a program and a small set of sample inputs, we (1) track the data flow of inputs to aggregate input fragments that share the same data flow through program execution into lexical and syntactic entities; (2) assign these entities names that are based on the associated variable and function identifiers; and (3) systematically generalize production rules by means of membership queries. As a result, we need only a minimal set of sample inputs to obtain human-readable context-free grammars that reflect valid input structure. In our evaluation on inputs like URLs, spreadsheets, or configuration files, our AUTOGRAM prototype obtains input grammars that are both accurate and very readable - and that can be directly fed into test generators for comprehensive automated testing.

Connected through hyperedge HE-1 (induced by source paper "inferring input grammars from dynamic control flow"):
  with members:
    - "building fast fuzzers"
    - "sample free learning of input grammars for comprehensive software fuzzing"
    - "neuzz efficient fuzzing with neural program smoothing"
    - "not all bytes are equal neural byte sieve for fuzzing"
    - "learn fuzz machine learning for input fuzzing"
    - "synthesizing program input grammars"
    - "trx a formally verified parser interpreter"

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)