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: "what is the connection between issues bugs and enhancements lessons learned from 800 software projects"
  Abstract: Agile teams juggle multiple tasks so professionals are often assigned to multiple projects, especially in service organizations that monitor and maintain a large suite of software for a large user base. If we could predict changes in project conditions changes, then managers could better adjust the staff allocated to those projects.This paper builds such a predictor using data from 832 open source and proprietary applications. Using a time series analysis of the last 4 months of issues, we can forecast how many bug reports and enhancement requests will be generated next month. The forecasts made in this way only require a frequency count of this issue reports (and do not require an historical record of bugs found in the project). That is, this kind of predictive model is very easy to deploy within a project. We hence strongly recommend this method for forecasting future issues, enhancements, and bugs in a project.

Connected through hyperedge HE-1 (induced by source paper "sequential model optimization for software process control"):
  with members:
    - "finding faster configurations using flash"
    - "data driven search based software engineering"
    - "warmstarting of model based algorithm configuration"
    - "negative results for software effort estimation"
    - "why is differential evolution better than grid search for tuning defect predictors"
    - "tuning for software analytics"

Connected through hyperedge HE-2 (induced by source paper "security smells in infrastructure as code scripts"):
  with members:
    - "source code properties of defective infrastructure as code scripts"
    - "characterizing the influence of continuous integration empirical results from 250 open source and proprietary projects"
    - "we don t need another hero the impact of heroes on software development"
    - "rehearsal a configuration verification tool for puppet"

Connected through hyperedge HE-3 (induced by source paper "bad smells in software analytics papers"):
  with members:
    - "the impact of automated parameter optimization on defect prediction models"
    - "is better data better than better data miners on the benefits of tuning smote for defect prediction"
    - "what is wrong with topic modeling and how to fix it using search based software engineering"
    - "data driven search based software engineering"
    - "we don t need another hero the impact of heroes on software development"
    - "revisiting unsupervised learning for defect prediction"
    - "easy over hard a case study on deep learning"
    - "sampling as a baseline optimizer for search based software engineering"

Connected through hyperedge HE-4 (induced by source paper "characterizing the influence of continuous integration empirical results from 250 open source and proprietary projects"):
  with members:
    - "we don t need another hero the impact of heroes on software development"

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)