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 "a parametric counterexample refinement approach for robust timed specifications"):
  Abstract: Robustness analyzes the impact of small perturbations in the semantics of a model. This allows to model hardware imprecision and therefore it has been applied to determine implementability of timed automata. In a recent paper, we extend this problem to a specification theory for real-timed systems based on timed input/output automata, that are interpreted as two-player games. We propose a construction that allows to synthesize an implementation of a specification that is robust under a given timed perturbation, and we study the impact of these perturbations when composing different specifications. #R##N#To complete this work we present a technique that evaluates the greatest admissible perturbation. It consists in an iterative process that extracts a spoiling strategy when a game is lost, and through a parametric analysis refines the admissible values for the perturbation. We demonstrate this approach with a prototype implementation.

Includes members:
  Member "timed parity games complexity and robustness":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timed network games with clocks")
  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-2 (induced by source paper "the deep learning compiler a comprehensive survey")

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.SE(Software Engineering)