一个。net应用程序的异常流分析工具

Israel García, N. Cacho
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引用次数: 18

摘要

在本文中,我们提出了一个异常流分析工具,称为流挖掘,它可以在多种编程语言中自动收集和可视化异常处理结构的过程。更具体地说,当前版本的flow Mining侧重于使用。. NET框架来帮助开发人员检查应用程序,以改进它们或了解它们的异常处理行为。流挖掘提取异常流的度量和信息。NET应用程序,提供异常处理的不同视图。例如,演进视图允许开发人员可视化应用程序历史上多个指标的行为。使用这个工具在五。NET应用程序证明了该工具可以帮助开发人员使用适当的错误处理策略构建和改进应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
eFlowMining: An Exception-Flow Analysis Tool for .NET Applications
In this paper, we present a exception-flow analysis tool, called eFlow Mining, that automates the process of gathering and visualizing exception-handling constructs in multi-programming languages. More specifically, the current version of eFlow Mining focuses on code written using the. NET framework to help developers in inspecting applications either to improve them or to understand their exception handling behavior. eFlow Mining extracts metrics and information about the exception flows in. NET applications, providing different views of the exception handling. For instance, an Evolution View allows developers to visualize the behavior of multiple metrics over the application history. Use of this tool on five. NET applications demonstrates that the tool can be helpful to support developers building and evolving applications with appropriate error-handling strategies.
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