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: "inferring loop invariants by mutation dynamic analysis and static checking"
  Abstract: Verifiers that can prove programs correct against their full functional specification require, for programs with loops, additional annotations in the form of  loop invariants —properties that hold for every iteration of a loop. We show that significant loop invariant candidates can be generated by systematically mutating postconditions; then, dynamic checking (based on automatically generated tests) weeds out invalid candidates, and static checking selects provably valid ones. We present a framework that automatically applies these techniques to support a program prover, paving the way for fully automatic verification without manually written loop invariants: Applied to 28 methods (including 39 different loops) from various  java.util  classes (occasionally modified to avoid using Java features not fully supported by the static checker), our DYNAMATE prototype automatically discharged 97 percent of all proof obligations, resulting in automatic complete correctness proofs of 25 out of the 28 methods—outperforming several state-of-the-art tools for fully automatic verification.

Connected through hyperedge HE-1 (induced by source paper "cln2inv learning loop invariants with continuous logic networks"):
  with members:
    - "guiding high performance sat solvers with unsat core predictions"
    - "inductive logic programming via differentiable deep neural logic networks"
    - "learning a sat solver from single bit supervision"
    - "learning explanatory rules from noisy data"
    - "adam a method for stochastic optimization"
    - "loop invariants analysis classification and examples"

Connected through hyperedge HE-2 (induced by source paper "faster mutation analysis via equivalence modulo states"):
  with members:
    - "assessing and comparing mutation based fault localization techniques"

Connected through hyperedge HE-3 (induced by source paper "learning likely invariants to explain why a program fails"):
  with members:
    - "casper debugging null dereferences with ghosts and causality traces"
    - "contracts in practice"
    - "cause clue clauses error localization using maximum satisfiability"
    - "automated fault localization using potential invariants 1"

Connected through hyperedge HE-4 (induced by source paper "a survey of symbolic execution techniques"):
  with members:
    - "enhancing reuse of constraint solutions to improve symbolic execution"
    - "loop invariants analysis classification and examples"
    - "compact symbolic execution"

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)