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 "harvey a greybox fuzzer for smart contracts"):
  Abstract: We present Harvey, an industrial greybox fuzzer for smart contracts, which are programs managing accounts on a blockchain. Greybox fuzzing is a lightweight test-generation approach that effectively detects bugs and security vulnerabilities. However, greybox fuzzers randomly mutate program inputs to exercise new paths; this makes it challenging to cover code that is guarded by narrow checks, which are satisfied by no more than a few input values. Moreover, most real-world smart contracts transition through many different states during their lifetime, e.g., for every bid in an auction. To explore these states and thereby detect deep vulnerabilities, a greybox fuzzer would need to generate sequences of contract transactions, e.g., by creating bids from multiple users, while at the same time keeping the search space and test suite tractable. In this experience paper, we explain how Harvey alleviates both challenges with two key fuzzing techniques and distill the main lessons learned. First, Harvey extends standard greybox fuzzing with a method for predicting new inputs that are more likely to cover new paths or reveal vulnerabilities in smart contracts. Second, it fuzzes transaction sequences in a targeted and demand-driven way. We have evaluated our approach on 27 real-world contracts. Our experiments show that the underlying techniques significantly increase Harvey's effectiveness in achieving high coverage and detecting vulnerabilities, in most cases orders-of-magnitude faster; they also reveal new insights about contract code.

Includes members:
  Member "finding the greedy prodigal and suicidal contracts at scale":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "smacs smart contract access control service")
  Member "quantitative analysis of smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "targeted greybox fuzzing with static lookahead analysis")
  Member "evaluating fuzz testing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "smart contract development from the perspective of developers topics and issues discussed on social media")
  Member "vandal a scalable security analysis framework for smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "angora efficient fuzzing by principled search":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "meuzz smart seed scheduling for hybrid fuzzing")
  Member "securify practical security analysis of smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "an overview on smart contracts challenges advances and platforms")

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)