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 "targeted greybox fuzzing with static lookahead analysis"):
  Abstract: Automatic test generation typically aims to generate inputs that explore new paths in the program under test in order to find bugs. Existing work has, therefore, focused on guiding the exploration toward program parts that are more likely to contain bugs by using an offline static analysis. #R##N#In this paper, we introduce a novel technique for targeted greybox fuzzing using an online static analysis that guides the fuzzer toward a set of target locations, for instance, located in recently modified parts of the program. This is achieved by first semantically analyzing each program path that is explored by an input in the fuzzer's test suite. The results of this analysis are then used to control the fuzzer's specialized power schedule, which determines how often to fuzz inputs from the test suite. We implemented our technique by extending a state-of-the-art, industrial fuzzer for Ethereum smart contracts and evaluate its effectiveness on 27 real-world benchmarks. Using an online analysis is particularly suitable for the domain of smart contracts since it does not require any code instrumentation---instrumentation to contracts changes their semantics. Our experiments show that targeted fuzzing significantly outperforms standard greybox fuzzing for reaching 83% of the challenging target locations (up to 14x of median speed-up).

Includes members:
  Member "v fuzz vulnerability oriented evolutionary fuzzing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "verifying software vulnerabilities in iot cryptographic protocols")
  Member "harvey a greybox fuzzer for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ae gis shielding vulnerable smart contracts against attacks")
  Member "finding the greedy prodigal and suicidal contracts at scale":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "online detection of effectively callback free objects with applications to smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "smacs smart contract access control service")
  Member "quantitative analysis of smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "oracle supported dynamic exploit generation for smart contracts")
  Member "fairfuzz a targeted mutation strategy for increasing greybox fuzz testing coverage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "evaluating fuzz testing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "contractfuzzer fuzzing smart contracts for vulnerability detection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")

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)