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: "revisiting exception handling practices with exception flow analysis"
  Abstract: Modern programming languages, such as Java and C#, typically provide features that handle exceptions. These features separate error-handling code from regular source code and aim to assist in the practice of software comprehension and maintenance. Having acknowledged the advantages of exception handling features, their misuse can still cause reliability degradation or even catastrophic software failures. Prior studies on exception handling aim to understand the practices of exception handling in its different components, such as the origin of the exceptions and the handling code of the exceptions. Yet, the observed findings were scattered and diverse. In this paper, to complement prior research findings on exception handling, we study its features by enriching the knowledge of handling code with a flow analysis of exceptions. Our case study is conducted with over 10K exception handling blocks, and over 77K related exception flows from 16 open-source Java and C# (.NET) libraries and applications. Our case study results show that each try block has up to 12 possible potentially recoverable yet propagated exceptions. More importantly, 22% of the distinct possible exceptions can be traced back to multiple methods (average of 1.39 and max of 34). Such results highlight the additional challenge of composing quality exception handling code. To make it worse, we confirm that there is a lack of documentation of the possible exceptions and their sources. However, such critical information can be identified by exception flow analysis on well- documented API calls (e.g., JRE and .NET documentation). Finally, we observe different strategies in exception handling code between Java and C#. Our findings highlight the opportunities of leveraging automated software analysis to assist in exception handling practices and signify the need of more further in-depth studies on exception handling practice.

Connected through hyperedge HE-1 (induced by source paper "unveiling exception handling guidelines adopted by java developers"):
  with members:
    - "studying the prevalence of exception handling anti patterns"
    - "on the use of context in recommending exception handling code examples"

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)