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: "are delayed issues harder to resolve revisiting cost to fix of defects throughout the lifecycle"
  Abstract: Many practitioners and academics believe in a delayed issue effect (DIE); i.e. the longer an issue lingers in the system, the more effort it requires to resolve. This belief is often used to justify major investments in new development processes that promise to retire more issues sooner. This paper tests for the delayed issue effect in 171 software projects conducted around the world in the period from 2006---2014. To the best of our knowledge, this is the largest study yet published on this effect. We found no evidence for the delayed issue effect; i.e. the effort to resolve issues in a later phase was not consistently or substantially greater than when issues were resolved soon after their introduction. This paper documents the above study and explores reasons for this mismatch between this common rule of thumb and empirical data. In summary, DIE is not some constant across all projects. Rather, DIE might be an historical relic that occurs intermittently only in certain kinds of projects. This is a significant result since it predicts that new development processes that promise to faster retire more issues will not have a guaranteed return on investment (depending on the context where applied), and that a long-held truth in software engineering should not be considered a global truism.

Connected through hyperedge HE-1 (induced by source paper "the changing nature of computational science software"):
  with members:
    - "sequential model optimization for software process control"
    - "why software projects need heroes lessons learned from 1100 projects"
    - "we don t need another hero the impact of heroes on software development"

Connected through hyperedge HE-2 (induced by source paper "assessing practitioner beliefs about software defect prediction"):
  with members:
    - "we don t need another hero the impact of heroes on software development"
    - "bellwethers a baseline method for transfer learning"

Connected through hyperedge HE-3 (induced by source paper "learning general principles from hundreds of software projects"):
  with members:
    - "bellwethers a baseline method for transfer learning"
    - "better predictors for issue lifetime"
    - "better data is better than better data miners benefits of tuning smote for defect prediction"
    - "a dissection of the test driven development process does it really matter to test first or to test last"
    - "defining and conceptualizing actionable insight a conceptual framework for decision centric analytics"
    - "smote synthetic minority over sampling technique"

Connected through hyperedge HE-4 (induced by source paper "assessing practitioner beliefs"):
  with members:
    - "we don t need another hero the impact of heroes on software development"
    - "bellwethers a baseline method for transfer learning"

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)