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: "improving strategies via smt solving"
  Abstract: We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widening operators for enforcing convergence within a finite number of iterations (ii) the use of merge operations (often, convex hulls) at the merge points of the control flow graph. It instead computes the least inductive invariant expressible in the domain at a restricted set of program points, and analyzes the rest of the code en bloc. We emphasize that we compute this inductive invariant precisely. For that we extend the strategy improvement algorithm of Gawlitza and Seidl [17]. If we applied their method directly, we would have to solve an exponentially sized system of abstract semantic equations, resulting in memory exhaustion. Instead, we keep the system implicit and discover strategy improvements using SAT modulo real linear arithmetic (SMT). For evaluating strategies we use linear programming. Our algorithm has low polynomial space complexity and performs for contrived examples in the worst case exponentially many strategy improvement steps; this is unsurprising, since we show that the associated abstract reachability problem is II2p-complete.

Connected through hyperedge HE-1 (induced by source paper "safety verification and refutation by k invariants and k induction extended version"):
  with members:
    - "combining k induction with continuously refined invariants"
    - "optimization in smt with la q cost functions"
    - "the octagon abstract domain"

Connected through hyperedge HE-2 (induced by source paper "invariant generation through strategy iteration in succinctly represented control flow graphs"):
  with members:
    - "succinct representations for abstract interpretation"
    - "optimization in smt with la q cost functions"
    - "numerical invariants through convex relaxation and max strategy iteration"
    - "using bounded model checking to focus fixpoint iterations"
    - "automatic modular abstractions for template numerical constraints"
    - "the octagon abstract domain"
    - "symbolic methods to enhance the precision of numerical abstract domains"
    - "a static analyzer for large safety critical software"

Connected through hyperedge HE-3 (induced by source paper "succinct representations for abstract interpretation"):
  with members:
    - "using bounded model checking to focus fixpoint iterations"
    - "the octagon abstract domain"
    - "the parma polyhedra library toward a complete set of numerical abstractions for the analysis and verification of hardware and software systems"
    - "a static analyzer for large safety critical software"

Connected through hyperedge HE-4 (induced by source paper "invariant stream generators using automatic abstract transformers based on a decidable logic"):
  with members:
    - "using bounded model checking to focus fixpoint iterations"
    - "pkind a parallel k induction based model checker"
    - "automatic modular abstractions for linear constraints"

Connected through hyperedge HE-5 (induced by source paper "using bounded model checking to focus fixpoint iterations"):
  with members:
    - "automatic modular abstractions for template numerical constraints"
    - "automatic modular abstractions for linear constraints"
    - "symbolic methods to enhance the precision of numerical abstract domains"
    - "a static analyzer for large safety critical software"

Connected through hyperedge HE-6 (induced by source paper "modular abstractions of reactive nodes using disjunctive invariants"):
  with members:
    - "automatic modular abstractions for template numerical constraints"

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)