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 "configcrusher white box performance analysis for configurable systems"):
  Abstract: In configurable software systems, stakeholders are often interested in knowing how configuration options influence the performance of a system to facilitate, for example, the debugging and optimization processes of these systems. There are several black-box approaches to obtain this information, but they usually require a large number of samples to make accurate predictions, whereas the few existing white-box approaches impose limitations on the systems that they can analyze. This paper proposes ConfigCrusher, a white-box performance analysis that exploits several insights of configurable systems. ConfigCrusher employs a static data-flow analysis to identify how configuration options may influence control-flow decisions and instruments code regions corresponding to these decisions to dynamically analyze the influence of configuration options on the regions' performance. Our evaluation using $10$ real-world configurable systems shows that ConfigCrusher is more efficient at building performance models that are similar to or more accurate than current state-of-the-art black-box and white-box approaches. Overall, this paper showcases the benefits and potential of white-box performance analyses to outperform black-box approaches and provide additional information for analyzing configurable systems.

Includes members:
  Member "igen dynamic interaction inference for configurable software":
    also connected through other hyperedges:
      (none)
  Member "test them all is it worth it assessing configuration sampling on the jhipster web development stack":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards quality assurance of software product lines with adversarial configurations")
  Member "do android taint analysis tools keep their promises":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "are free android app security analysis tools effective in detecting known vulnerabilities")
  Member "self adaptive static analysis":
    also connected through other hyperedges:
      (none)
  Member "an uncertainty aware approach to optimal configuration of stream processing systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "black or white how to develop an autotuner for memory based analytics extended version")
  Member "a comparison of 10 sampling algorithms for configurable systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards quality assurance of software product lines with adversarial configurations")
  Member "precise dynamic information flow for database backed applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "contextual and granular policy enforcement in database backed applications")

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.SE(Software Engineering)