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: "high level combined deterministic and pseudo exhuastive test generation for risc processors"
  Abstract: Recent safety standards set stringent requirements for the target fault coverage in embedded microprocessors, with the objective to guarantee robustness and functional safety of the critical electronic systems. This motivates the need for improving the quality of test generation for microprocessors. A new high-level implementation-independent test generation method for RISC processors is proposed. The set of instructions of the processor is partitioned into groups. For each group, a dedicated test template is created, to be used for generating two test programs, for testing the control and the data paths respectively. For testing the control part, a novel high-level control fault model is proposed. Using this model, a set of deterministic test data operands are generated for each instruction of the given group. The advantage of the high-level fault model is that it covers larger than SAF fault class including multiple fault coverage in the control part. For generating the data path test, pseudo-exhaustive data operands are used. We investigated the feasibility of the approach and demonstrated high efficiency of the generated test programs for testing the execute module of the miniMIPS RISC processor.

Connected through hyperedge HE-1 (induced by source paper "rescue interdependent challenges of reliability security and quality in nanoelectronic systems"):
  with members:
    - "pascal timing sca resistant design and verification flow"
    - "challenges of reliability assessment and enhancement in autonomous systems"
    - "accelerating transient fault injection campaigns by using dynamic hdl slicing"
    - "functional failure rate due to single event transients in clock distribution networks"
    - "on the estimation of complex circuits functional failure rate by machine learning techniques"
    - "towards multidimensional verification where functional meets non functional"

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.AR(Hardware Architecture)