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: "enforcing information flow policies with type targeted program synthesis"
  Abstract: Author(s): Polikarpova, N; Yang, J; Itzhaky, S; Hance, T; Solar-Lezama, A | Abstract: We present a technique for static enforcement of high-level, declarative information flow policies. Given a program that manipulates sensitive data and a set of declarative policies on the data, our technique automatically inserts policy-enforcing code throughout the program to make it provably secure with respect to the policies. We achieve this through a new approach we call type-targeted program synthesis, which enables the application of traditional synthesis techniques in the context of global policy enforcement. The key insight is that, given an appropriate encoding of policy compliance in a type system, we can use type inference to decompose a global policy enforcement problem into a series of small, local program synthesis problems that can be solved independently. We implement this approach in Lifty, a core DSL for data-centric applications. Our experience using the DSL to implement three case studies shows that (1) Lifty's centralized, declarative policy definitions make it easier to write secure data-centric applications, and (2) the Lifty compiler is able to efficiently synthesize all necessary policy-enforcing code, including the code required to prevent several reported real-world information leaks.

Connected through hyperedge HE-1 (induced by source paper "concise read only specifications for better synthesis of programs with pointers extended version"):
  with members:
    - "resource guided program synthesis"
    - "automating deductive verification for weak memory programs"
    - "program synthesis from polymorphic refinement types"

Connected through hyperedge HE-2 (induced by source paper "targeted synthesis for programming with data invariants"):
  with members:
    - "neural sketch learning for conditional program generation"
    - "programmatic and direct manipulation together at last"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"
    - "flexible invariants through semantic collaboration"

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)