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: "efficiently manifesting asynchronous programming errors in android apps"
  Abstract: Android, the #1 mobile app framework, enforces the single-GUI-thread model, in which a single UI thread manages GUI rendering and event dispatching. Due to this model, it is vital to avoid blocking the UI thread for responsiveness. One common practice is to offload long-running tasks into async threads. To achieve this, Android provides various async programming constructs, and leaves developers themselves to obey the rules implied by the model. However, as our study reveals, more than 25% apps violate these rules and introduce hard-to-detect, fail-stop errors, which we term as aysnc programming errors (APEs). To this end, this paper introduces APEChecker, a technique to automatically and efficiently manifest APEs. The key idea is to characterize APEs as specific fault patterns, and synergistically combine static analysis and dynamic UI exploration to detect and verify such errors. Among the 40 real-world Android apps, APEChecker unveils and processes 61 APEs, of which 51 are confirmed (83.6% hit rate). Specifically, APEChecker detects 3X more APEs than the state-of-art testing tools (Monkey, Sapienz and Stoat), and reduces testing time from half an hour to a few minutes. On a specific type of APEs, APEChecker confirms 5X more errors than the data race detection tool, EventRacer, with very few false alarms.

Connected through hyperedge HE-1 (induced by source paper "an empirical assessment of security risks of global android banking apps"):
  with members:
    - "a large scale empirical study on industrial fake apps"
    - "storydroid automated generation of storyboard for android apps"
    - "ausera large scale automated security risk assessment of global mobile banking apps"
    - "identifying relevant information cues for vulnerability assessment using cvss"
    - "large scale analysis of framework specific exceptions in android apps"
    - "automated poisoning attacks and defenses in malware detection systems an adversarial machine learning approach"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-2 (induced by source paper "core automating review recommendation for code changes"):
  with members:
    - "an empirical assessment of security risks of global android banking apps"
    - "pythia ai assisted code completion system"
    - "an empirical study towards characterizing deep learning development and deployment across different frameworks and platforms"
    - "storydroid automated generation of storyboard for android apps"
    - "ausera large scale automated security risk assessment of global mobile banking apps"
    - "code completion with neural attention and pointer networks"
    - "deep contextualized word representations"
    - "code2seq generating sequences from structured representations of code"

Connected through hyperedge HE-3 (induced by source paper "storydroid automated generation of storyboard for android apps"):
  with members:
    - "a large scale empirical study on industrial fake apps"
    - "understanding android obfuscation techniques a large scale investigation in the wild"
    - "ausera large scale automated security risk assessment of global mobile banking apps"
    - "automated reporting of gui design violations for mobile apps"
    - "machine learning based prototyping of graphical user interfaces for mobile apps"
    - "large scale analysis of framework specific exceptions in android apps"
    - "pix2code generating code from a graphical user interface screenshot"
    - "automated poisoning attacks and defenses in malware detection systems an adversarial machine learning approach"

Connected through hyperedge HE-4 (induced by source paper "a large scale empirical study on industrial fake apps"):
  with members:
    - "storydroid automated generation of storyboard for android apps"
    - "ausera large scale automated security risk assessment of global mobile banking apps"
    - "large scale analysis of framework specific exceptions in android apps"
    - "automated poisoning attacks and defenses in malware detection systems an adversarial machine learning approach"

Connected through hyperedge HE-5 (induced by source paper "ausera large scale automated security risk assessment of global mobile banking apps"):
  with members:
    - "automated poisoning attacks and defenses in malware detection systems an adversarial machine learning approach"
    - "efficient estimation of word representations in vector space"

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.SE(Software Engineering)