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 "semantic fuzzing with zest"):
  Abstract: Programs expecting structured inputs often consist of both a syntactic analysis stage, which parses raw input, and a semantic analysis stage, which conducts checks on the parsed input and executes the core logic of the program. Generator-based testing tools in the lineage of QuickCheck are a promising way to generate random syntactically valid test inputs for these programs. We present Zest, a technique which automatically guides QuickCheck-like random input generators to better explore the semantic analysis stage of test programs. Zest converts random-input generators into deterministic parametric input generators. We present the key insight that mutations in the untyped parameter domain map to structural mutations in the input domain. Zest leverages program feedback in the form of code coverage and input validity to perform feedback-directed parameter search. We evaluate Zest against AFL and QuickCheck on five Java programs: Maven, Ant, BCEL, Closure, and Rhino. Zest covers 1.03x-2.81x as many branches within the benchmarks' semantic analysis stages as baseline techniques. Further, we find 10 new bugs in the semantic analysis stages of these benchmarks. Zest is the most effective technique in finding these bugs reliably and quickly, requiring at most 10 minutes on average to find each bug.

Includes members:
  Member "smart greybox fuzzing":
    also connected through other hyperedges:
      (none)
  Member "fairfuzz a targeted mutation strategy for increasing greybox fuzz testing coverage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "evaluating fuzz testing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "improving function coverage with munch a hybrid fuzzing and directed symbolic execution approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hotfuzz discovering algorithmic denial of service vulnerabilities through guided micro fuzzing")
  Member "angora efficient fuzzing by principled search":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "superion grammar aware greybox fuzzing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cagfuzz coverage guided adversarial generative fuzzing testing of deep learning systems")
  Member "learn fuzz machine learning for input fuzzing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "synthesizing program input grammars":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a systematic review of fuzzing based on machine learning techniques")

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)