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: "structuring the synthesis of heap manipulating programs"
  Abstract: This paper describes a deductive approach to synthesizing imperative programs with pointers from declarative specifications expressed in Separation Logic. Our synthesis algorithm takes as input a pair of assertions---a pre- and a postcondition---which describe two states of the symbolic heap, and derives a program that transforms one state into the other, guided by the shape of the heap. The program synthesis algorithm rests on the novel framework of Synthetic Separation Logic (SSL), which generalises the classical notion of heap entailment $\mathcal{P} \vdash \mathcal{Q}$ to incorporate a possibility of transforming a heap satisfying an assertion $\mathcal{P}$ into a heap satisfying an assertion $\mathcal{Q}$. A synthesized program represents a proof term for a transforming entailment statement $\mathcal{P} \leadsto \mathcal{Q}$, and the synthesis procedure corresponds to a proof search. The derived programs are, thus, correct by construction, in the sense that they satisfy the ascribed pre/postconditions, and are accompanied by complete proof derivations, which can be checked independently. #R##N#We have implemented a proof search engine for SSL in a form the program synthesizer called SuSLik. For efficiency, the engine exploits properties of SSL rules, such as invertibility and commutativity of rule applications on separate heaps, to prune the space of derivations it has to consider. We explain and showcase the use of SSL on characteristic examples, describe the design of SuSLik, and report on our experience of using it to synthesize a series of benchmark programs manipulating heap-based linked data structures.

Connected through hyperedge HE-1 (induced by source paper "structuring the synthesis of heap manipulating programs"):
  with members:
    - "synthesizing bijective lenses"
    - "synthesizing imperative programs from examples guided by static analysis"
    - "neural sketch learning for conditional program generation"
    - "component based synthesis of table consolidation and transformation tasks from examples"
    - "program synthesis from polymorphic refinement types"

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)