human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "stratified static analysis based on variable dependencies"):
  Abstract: In static analysis by abstract interpretation, one often uses widening operators in order to enforce convergence within finite time to an inductive invariant. Certain widening operators, including the classical one over finite polyhedra, exhibit an unintuitive behavior: analyzing the program over a subset of its variables may lead a more precise result than analyzing the original program! In this article, we present simple workarounds for such behavior.

Includes members:
  Member "automatic modular abstractions for template numerical constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "program analysis with local policy iteration")
  Member "a minimalistic look at widening operators":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient generation of correctness certificates for the abstract domain of polyhedra")
  Member "symbolic methods to enhance the precision of numerical abstract domains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "automatically proving microkernels free from privilege escalation from their executable")
  Member "the parma polyhedra library toward a complete set of numerical abstractions for the analysis and verification of hardware and software systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the deep learning compiler a comprehensive survey")
  Member "a static analyzer for large safety critical software":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "automatically proving microkernels free from privilege escalation from their executable")

Question: Please tell me which class the source paper 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)