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: "rapid quality assurance with requirements smells"
  Abstract: Abstract   Bad requirements quality can cause expensive consequences during the software development lifecycle, especially if iterations are long and feedback comes late. We aim at a light-weight static requirements analysis approach that allows for rapid checks immediately when requirements are written down. We transfer the concept of  code smells  to requirements engineering as  Requirements Smells . To evaluate the benefits and limitations, we define Requirements Smells, realize our concepts for a smell detection in a prototype called  Smella  and apply Smella in a series of cases provided by three industrial and a university context. The automatic detection yields an average precision of 59% at an average recall of 82% with high variation. The evaluation in practical environments indicates benefits such as an increase of the awareness of quality defects. Yet, some smells were not clearly distinguishable. Lightweight smell detection can uncover many practically relevant requirements defects in a reasonably precise way. Although some smells need to be defined more clearly, smell detection provides a helpful means to support quality assurance in requirements engineering, for instance, as a supplement to reviews.

Connected through hyperedge HE-1 (induced by source paper "explainable software for cyber physical systems es4cps report from the gi dagstuhl seminar 19023 january 06 11 2019 schloss dagstuhl"):
  with members:
    - "formal specification and verification of autonomous robotic systems a survey"
    - "the orca hub explainable offshore robotics through intelligent interfaces"
    - "introducing liveness into multi lane spatial logic lane change controllers using uppaal"
    - "explainable security"
    - "explain yourself a natural language interface for scrutable autonomous robots"
    - "imperfect knowledge in autonomous urban traffic manoeuvres"
    - "cyber physical systems security a survey"
    - "causes and explanations a structural model approach part ii explanations"

Connected through hyperedge HE-2 (induced by source paper "towards an holistic definition of requirements debt"):
  with members:
    - "technical debt prioritization state of the art a systematic literature review"
    - "the technical debt dataset"

Connected through hyperedge HE-3 (induced by source paper "identifying relevant information cues for vulnerability assessment using cvss"):
  with members:
    - "comparing vulnerability severity and exploits using case control studies"

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)