human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "faster creation of smaller test suites with snap"):
  Abstract: State-of-the-art theorem provers, combined with smart sampling heuristics, can generate millions of test cases in just a few hours. But given the heuristic nature of those methods, not all of those tests may be valid. Also, test engineers may find it too burdensome to run all those tests. #R##N#Within a large space of tests, there can be redundancies (duplicate entries or similar entries that do not contribute much to overall diversity). Our approach, called SNAP uses specialized sub-sampling heuristics to avoid finding those repeated tests. By avoiding those repeated structures SNAP explores a smaller space of options. Hence, it is possible for SNAP to verify all its tests. #R##N#To evaluate SNAP, this paper applied 27 real-world case studies from a recent ICSE'18 paper. Compared to prior results, SNAP's test case generation was 10 to 3000 times faster (median to max). Also, while prior work showed that their tests were 70% valid, our method generates 100% valid tests. Most importantly, test engineers would find it relatively easiest to apply SNAP's tests since our test suites are 10 to 750 times smaller (median to max) than those generated using prior work.

Includes members:
  Member "data driven search based software engineering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sequential model optimization for software process control")
  Member "hyperparameter optimization for effort estimation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cross dataset design discussion mining")
  Member "riot a stochastic based method for workflow scheduling in the cloud":
    also connected through other hyperedges:
      (none)
  Member "revisiting unsupervised learning for defect prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data driven search based software engineering")
  Member "beyond evolutionary algorithms for search based software engineering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "better software analytics via duo data mining algorithms using used by optimizers")
  Member "a survey of symbolic execution techniques":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cbr controlled burst recording")
  Member "sampling as a baseline optimizer for search based software engineering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "how to evaluate solutions in pareto based search based software engineering a critical review and methodological guidance")
  Member "enhancing reuse of constraint solutions to improve symbolic execution":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "constraint solving with deep learning for symbolic execution")

Question: Please tell me which class the source paper 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)