human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "heap abstractions for static analysis"):
  Abstract: Heap data is potentially unbounded and seemingly arbitrary. Hence, unlike stack and static data, heap data cannot be abstracted in terms of a fixed set of program variables. This makes it an interesting topic of study and there is an abundance of literature employing heap abstractions. Although most studies have addressed similar concerns, insights gained in one description of heap abstraction may not directly carry over to some other description.   In our search of a unified theme, we view heap abstraction as consisting of two steps: (a) heap modelling, which is the process of representing a heap memory (i.e., an unbounded set of concrete locations) as a heap model (i.e., an unbounded set of abstract locations), and (b) summarization, which is the process of bounding the heap model by merging multiple abstract locations into summary locations. We classify the heap models as storeless, store based, and hybrid. We describe various summarization techniques based on k-limiting, allocation sites, patterns, variables, other generic instrumentation predicates, and higher-order logics. This approach allows us to compare the insights of a large number of seemingly dissimilar heap abstractions and also paves the way for creating new abstractions by mix and match of models and summarization techniques.

Includes members:
  Member "liveness based garbage collection for lazy languages":
    also connected through other hyperedges:
      (none)
  Member "flow and context sensitive points to analysis using higher order reachability":
    also connected through other hyperedges:
      (none)
  Member "interprocedural data flow analysis in soot using value contexts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "demand driven alias analysis formalizing bidirectional analyses for soundness and precision")
  Member "abstracting runtime heaps for program understanding":
    also connected through other hyperedges:
      (none)
  Member "heap reference analysis using access graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "demand driven alias analysis formalizing bidirectional analyses for soundness and precision")

Question: Please tell me which class the source paper 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)