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: "domain specific code smells in smart contracts"
  Abstract: Smart contracts are programs running on a blockchain. They are immutable to patch for bugs once deployed -- it is critical to ensure they are bug-free and well-designed before deploying. Code smells are symptoms in source code that possibly indicate deeper problems. The detection of code smells is a method to avoid potential bugs and improve the design of existing code. However, traditional code smell patterns are designed for centralized OO programs, e.g., Java or C++; while smart contracts are decentralized and contain numerous distinctive features, such as the gas system. To fill this gap, we collected smart-contract-related posts from Stack Exchange, as well as real-world smart contracts. We manually analyzed these posts and defined 20 kinds of \emph{code smells for smart contracts. We categorized these into security, architecture, and usability problems. To validate if practitioners consider these contract smells as harmful, we created an online survey and received 96 responses from 24 different countries. Feedback showed these code smells are harmful and removing them would improve quality and robustness of smart contracts. We manually identified our defined code smells in 587 contract accounts and publicly released our dataset. Finally, we summarized 5 impacts caused by contract code smells. These help developers better understand the symptoms of the smells and removal priority.

Connected through hyperedge HE-1 (induced by source paper "empirical review of automated analysis tools on 47 587 ethereum smart contracts"):
  with members:
    - "a survey on ethereum systems security vulnerabilities attacks and defenses"
    - "the art of the scam demystifying honeypots in ethereum smart contracts"
    - "slither a static analysis framework for smart contracts"
    - "smart contract vulnerabilities does anyone care"
    - "manticore a user friendly symbolic execution framework for binaries and smart contracts"
    - "tool demonstration fsolidm for designing secure ethereum smart contracts"
    - "finding the greedy prodigal and suicidal contracts at scale"
    - "ethir a framework for high level analysis of ethereum bytecode"

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)