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: "leveraging program analysis to reduce user perceived latency in mobile applications"
  Abstract: Reducing network latency in mobile applications is an effective way of improving the mobile user experience and has tangible economic benefits. This paper presents PALOMA, a novel client-centric technique for reducing the network latency by prefetching HTTP requests in Android apps. Our work leverages string analysis and callback control-flow analysis to automatically instrument apps using PALOMA's rigorous formulation of scenarios that address "what" and "when" to prefetch. PALOMA has been shown to incur significant runtime savings (several hundred milliseconds per prefetchable HTTP request), both when applied on a reusable evaluation benchmark we have developed and on real applications.

Connected through hyperedge HE-1 (induced by source paper "mobile app analysis and instrumentation techniques reimagined with decree"):
  with members:
    - "empirically assessing opportunities for prefetching and caching in mobile apps"
    - "do android taint analysis tools keep their promises"
    - "dexpler converting android dalvik bytecode to jimple for static analysis with soot"

Connected through hyperedge HE-2 (induced by source paper "four presumed gaps in the software engineering research community s knowledge"):
  with members:
    - "consensus in software engineering a cognitive mapping study"
    - "a survey of machine learning for big code and naturalness"

Connected through hyperedge HE-3 (induced by source paper "a microservice architecture for online mobile app optimization"):
  with members:
    - "dexpler converting android dalvik bytecode to jimple for static analysis with soot"

Connected through hyperedge HE-4 (induced by source paper "empirically assessing opportunities for prefetching and caching in mobile apps"):
  with members:
    - "how far can client only solutions go for mobile browser speed"

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)