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: "on the time and space complexity of aba prevention and detection"
  Abstract: We investigate the time and space complexity of detecting and preventing ABAs in shared memory algorithms for systems with n processes and bounded base objects. To that end, we define ABA-detecting registers, which are similar to normal read/write registers, except that they allow a process q to detect with a read operation, whether some process wrote the register since q's last read. ABA-detecting registers can be implemented trivially from a single unbounded register, but we show that they have a high complexity if base objects are bounded: An obstruction-free implementation of an ABA-detecting single bit register cannot be implemented from fewer than n-1 bounded registers. Moreover, bounded CAS objects (or more generally, conditional read-modify-write primitives) offer little help to implement ABA-detecting single bit registers: We prove a linear time-space tradeoff for such implementations. We show that the same time-space tradeoff holds for implementations of single bit LL/SC primitives from bounded writable CAS objects. This proves that the implementations of LL/SC/VL by Anderson and Moir (1995) as well as Jayanti and Petrovic (2003) are optimal. We complement our lower bounds with tight upper bounds: We give an implementation of ABA-detecting registers from n+1 bounded registers, which has step complexity O(1). We also show that (bounded) LL/SC/VL can be implemented from a single bounded CAS object and with O(n) step complexity. Both upper bounds are asymptotically optimal with respect to their time-space product. These results give formal evidence that the ABA problem is inherently difficult, that even writable CAS objects do not provide significant benefits over registers for dealing with the ABA problem itself, and that there is no hope of finding a more efficient implementation of LL/SC/VL from bounded CAS objects and registers than the ones mentioned.

Connected through hyperedge HE-1 (induced by source paper "strongly linearizable implementations of snapshots and other types"):
  with members:
    - "putting strong linearizability in context preserving hyperproperties in programs that use concurrent objects"
    - "linearizable implementations do not suffice for randomized distributed computation"

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.DC(Distributed, Parallel, and Cluster Computing)