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 "an efficient strongly connected components algorithm in the fault tolerant model"):
  Abstract: In this paper we study the problem of maintaining the strongly connected components of a graph in the presence of failures. In particular, we show that given a directed graph $G=(V,E)$ with $n=|V|$ and $m=|E|$, and an integer value $k\geq 1$, there is an algorithm that computes in $O(2^{k}n\log^2 n)$ time for any set $F$ of size at most $k$ the strongly connected components of the graph $G\setminus F$. The running time of our algorithm is almost optimal since the time for outputting the SCCs of $G\setminus F$ is at least $\Omega(n)$. The algorithm uses a data structure that is computed in a preprocessing phase in polynomial time and is of size $O(2^{k} n^2)$. #R##N#Our result is obtained using a new observation on the relation between strongly connected components (SCCs) and reachability. More specifically, one of the main building blocks in our result is a restricted variant of the problem in which we only compute strongly connected components that intersect a certain path. Restricting our attention to a path allows us to implicitly compute reachability between the path vertices and the rest of the graph in time that depends logarithmically rather than linearly in the size of the path. This new observation alone, however, is not enough, since we need to find an efficient way to represent the strongly connected components using paths. For this purpose we use a mixture of old and classical techniques such as the heavy path decomposition of Sleator and Tarjan and the classical Depth-First-Search algorithm. Although, these are by now standard techniques, we are not aware of any usage of them in the context of dynamic maintenance of SCCs. Therefore, we expect that our new insights and mixture of new and old techniques will be of independent interest.

Includes members:
  Member "preserving distances in very faulty graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "multiple source dual fault tolerant bfs trees":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graph spanners a tutorial review")
  Member "connectivity oracles for graphs subject to vertex failures":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "multiple edge fault tolerant approximate shortest path trees":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "compact and fast sensitivity oracles for single source distances":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a trivial yet optimal solution to vertex fault tolerant spanners")
  Member "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "dual failure resilient bfs structure":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "improved algorithms for decremental single source reachability on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")

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.DS(Data Structures and Algorithms)