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: "from good practices to effective policies for preventing errors in spreadsheets"
  Abstract: Thanks to the enormous flexibility they provide, spreadsheets are considered a priceless blessing by many end-users. Many spreadsheets, however, contain errors which can lead to severe consequences in some cases. To manage these risks, quality managers in companies are often asked to develop appropriate policies for preventing spreadsheet errors. Good policies should specify rules which are based on "known-good" practices. While there are many proposals for such practices in literature written by practitioners and researchers, they are often not consistent with each other. Therefore no general agreement has been reached yet and no science-based "golden rules" have been published. This paper proposes an expert-based, retrospective approach to the identification of good practices for spreadsheets. It is based on an evaluation loop that cross-validates the findings of human domain experts against rules implemented in a semi-automated spreadsheet workbench, taking into account the context in which the spreadsheets are used.

Connected through hyperedge HE-1 (induced by source paper "practical challenges with spreadsheet auditing tools"):
  with members:
    - "tool support for continuous quality control"

Connected through hyperedge HE-2 (induced by source paper "investigating effects of common spreadsheet design practices on correctness and maintainability"):
  with members:
    - "effect of range naming conventions on reliability and development time for simple spreadsheet formulas"
    - "spreadsheet good practice is there any such thing"
    - "an exploratory analysis of the impact of named ranges on the debugging performance of novice users"
    - "reducing overconfidence in spreadsheet development"
    - "an investigation of the incidence and effect of spreadsheet errors caused by the hard coding of input data values into formulas"
    - "complexity metrics for spreadsheet models"
    - "correctness is not enough"

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)