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: "semantically configurable consistency analysis for class and object diagrams"
  Abstract: Checking consistency between an object diagram (OD) and a class diagram (CD) is an important analysis problem. However, several variations in the semantics of CDs and ODs, as used in different contexts and for different purposes, create a challenge for analysis tools. To address this challenge in this paper we investigate semantically configurable model analysis. We formalize the variability in the languages semantics using a feature model: each configuration that the model permits induces a different semantics. Moreover, we develop a parametrized analysis that can be instantiated to comply with every legal configuration of the feature model. Thus, the analysis is semantically congured and its results change according to the semantics induced by the selected feature configuration. The ideas are implemented using a parametrized transformation to Alloy. The work can be viewed as a case study example for a formal and automated approach to handling semantic variability in modeling languages.

Connected through hyperedge HE-1 (induced by source paper "cd2alloy class diagrams analysis using alloy revisited"):
  with members:
    - "system model semantics of class diagrams"
    - "monticore a framework for compositional development of domain specific languages"
    - "cddiff semantic differencing for class diagrams"
    - "developing the uml as a formal modelling notation"
    - "the uml as a formal modeling notation"
    - "system model based definition of modeling language semantics"

Connected through hyperedge HE-2 (induced by source paper "correct by construction model composition application to the invasive software composition method"):
  with members:
    - "variability within modeling language definitions"

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)