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: "abstracting abstract control extended"
  Abstract: The strength of a dynamic language is also its weakness: run-time flexibility comes at the cost of compile-time predictability. Many of the hallmarks of dynamic languages such as closures, continuations, various forms of reflection, and a lack of static types make many programmers rejoice, while compiler writers, tool developers, and verification engineers lament. The dynamism of these features simply confounds statically reasoning about programs that use them. Consequently, static analyses for dynamic languages are few, far between, and seldom sound. #R##N#The "abstracting abstract machines" (AAM) approach to constructing static analyses has recently been proposed as a method to ameliorate the difficulty of designing analyses for such language features. The approach, so called because it derives a function for the sound and computable approximation of program behavior starting from the abstract machine semantics of a language, provides a viable approach to dynamic language analysis since all that is required is a machine description of the interpreter. #R##N#The original AAM recipe produces finite state abstractions, which cannot faithfully represent an interpreter's control stack. Recent advances have shown that higher-order programs can be approximated with pushdown systems. However, these automata theoretic models either break down on features that inspect or modify the control stack. #R##N#In this paper, we tackle the problem of bringing pushdown flow analysis to the domain of dynamic language features. We revise the abstracting abstract machines technique to target the stronger computational model of pushdown systems. In place of automata theory, we use only abstract machines and memoization. As case studies, we show the technique applies to a language with closures, garbage collection, stack-inspection, and first-class composable continuations.

Connected through hyperedge HE-1 (induced by source paper "abstracting definitional interpreters functional pearl"):
  with members:
    - "pushdown control flow analysis for free"
    - "galois transformers and modular abstract interpreters reusable metatheory for program analysis"
    - "soft contract verification"
    - "pushdown flow analysis with abstract garbage collection"
    - "simulation of two way pushdown automata revisited"
    - "introspective pushdown analysis of higher order programs"
    - "systematic abstraction of abstract machines"
    - "cfa2 a context free approach to control flow analysis"

Connected through hyperedge HE-2 (induced by source paper "pushdown control flow analysis for free"):
  with members:
    - "optimizing abstract abstract machines"
    - "introspective pushdown analysis of higher order programs"
    - "cfa2 a context free approach to control flow analysis"
    - "pushdown control flow analysis of higher order programs"
    - "abstracting abstract machines"

Connected through hyperedge HE-3 (induced by source paper "soft contract verification"):
  with members:
    - "concrete semantics for pushdown analysis the essence of summarization"
    - "dependent types for javascript"
    - "systematic abstraction of abstract machines"
    - "higher order symbolic execution via contracts"
    - "abstracting abstract machines"

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.PL(Programming Languages)