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: "computation of wcet using program slicing and real time model checking"
  Abstract: Computing accurate WCET on modern complex architectures is a challenging task. This problem has been devoted a lot of attention in the last decade but there are still some open issues. First, the control flow graph (CFG) of a binary program is needed to compute the WCET and this CFG is built using some internal knowledge of the compiler that generated the binary code; moreover once constructed the CFG has to be manually annotated with loop bounds. Second, the algorithms to compute the WCET (combining Abstract Interpretation and Integer Linear Programming) are tailored for specific architectures: changing the architecture (e.g. replacing an ARM7 by an ARM9) requires the design of a new ad hoc algorithm. Third, the tightness of the computed results (obtained using the available tools) are not compared to actual execution times measured on the real hardware. In this paper we address the above mentioned problems. We first describe a fully automatic method to compute a CFG based solely on the binary program to analyse. Second, we describe the model of the hardware as a product of timed automata, and this model is independent from the program description. The model of a program running on a hardware is obtained by synchronizing (the automaton of) the program with the (timed automata) model of the hardware. Computing the WCET is reduced to a reachability problem on the synchronised model and solved using the model-checker UPPAAL. Finally, we present a rigorous methodology that enables us to compare our computed results to actual execution times measured on a real platform, the ARM920T.

Connected through hyperedge HE-1 (induced by source paper "scalable and precise estimation and debugging of the worst case execution time for analysis friendly processors a comeback of model checking"):
  with members:
    - "how to compute worst case execution time by optimization modulo theory and a clever encoding of program semantics"
    - "approaches for software verification of an emergency recovery system for micro air vehicles"

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)