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 "on low high orders of directed graphs incremental algorithms and applications"):
  Abstract: A flow graph $G=(V,E,s)$ is a directed graph with a distinguished start vertex $s$. The dominator tree $D$ of $G$ is a tree rooted at $s$, such that a vertex $v$ is an ancestor of a vertex $w$ if and only if all paths from $s$ to $w$ include $v$. The dominator tree is a central tool in program optimization and code generation and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of $G$ is a preorder $\delta$ of $D$ that certifies the correctness of $D$ and has further applications in connectivity and path-determination problems. In this paper, we first consider how to maintain efficiently a low-high order of a flow graph incrementally under edge insertions. We present algorithms that run in $O(mn)$ total time for a sequence of $m$ edge insertions in an initially empty flow graph with $n$ vertices.These immediately provide the first incremental certifying algorithms for maintaining the dominator tree in $O(mn)$ total time, and also imply incremental algorithms for other problems. Hence, we provide a substantial improvement over the $O(m^2)$ simple-minded algorithms, which recompute the solution from scratch after each edge insertion. We also show how to apply low-high orders to obtain a linear-time $2$-approximation algorithm for the smallest $2$-vertex-connected spanning subgraph problem (2VCSS). Finally, we present efficient implementations of our new algorithms for the incremental low-high and 2VCSS problems and conduct an extensive experimental study on real-world graphs taken from a variety of application areas. The experimental results show that our algorithms perform very well in practice.

Includes members:
  Member "incremental 2 edge connectivity in directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "incremental strong connectivity and 2 connectivity in directed graphs")
  Member "an experimental study of dynamic dominators":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "incremental strong connectivity and 2 connectivity in directed graphs")
  Member "finding 2 edge and 2 vertex strongly connected components in quadratic time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computing and testing small connectivity in near linear time and queries via fast local cut algorithms")
  Member "popular conjectures imply strong lower bounds for dynamic problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "2 edge connectivity in directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "twinless articulation points and some related problems")
  Member "computing the 2 blocks of directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "twinless articulation points and some related problems")
  Member "on computing the 2 vertex connected components of directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "twinless articulation points and some related problems")
  Member "finding dominators via disjoint set union":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "concurrent disjoint set union")

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)