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: "stateful testing finding more errors in code and contracts"
  Abstract: Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new faults, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new faults and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.

Connected through hyperedge HE-1 (induced by source paper "contracts in practice"):
  with members:
    - "flexible invariants through semantic collaboration"
    - "class schema evolution for persistent object oriented software model empirical study and automated support"
    - "what good are strong specifications"
    - "collaborative software development on the web"

Connected through hyperedge HE-2 (induced by source paper "loop invariants analysis classification and examples"):
  with members:
    - "reducing the number of annotations in a verification oriented imperative language"
    - "inferring loop invariants using postconditions"
    - "a static analyzer for large safety critical software"

Connected through hyperedge HE-3 (induced by source paper "what good are strong specifications"):
  with members:
    - "guiding a general purpose c verifier to prove cryptographic protocols"
    - "specifying reusable components"

Connected through hyperedge HE-4 (induced by source paper "the evolution of contracts"):
  with members:
    - "class schema evolution for persistent object oriented software model empirical study and automated support"

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)