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Gistable: Evaluating the Executability of Python Code Snippets on GitHub

机译：Gistable：评估GitHub上Python代码片段的可执行性

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摘要

Software developers create and share code online to demonstrate programming language concepts and programming tasks. Code snippets can be a useful way to explain and demonstrate a programming concept, but may not always be directly executable. A code snippet can contain parse errors, or fail to execute if the environment contains unmet dependencies. This paper presents an empirical analysis of the executable status of Python code snippets shared through the GitHub gist system, and the ability of developers familiar with software configuration to correctly configure and run them. We find that 75.6% of gists require non-trivial configuration to overcome missing dependencies, configuration files, reliance on a specific operating system, or some other environment configuration. Our study also suggests the natural assumption developers make about resource names when resolving configuration errors is correct less than half the time. We also present Gistable, a database and extensible framework built on GitHub's gist system, which provides executable code snippets to enable reproducible studies in software engineering. Gistable contains 10,259 code snippets, approximately 5,000 with a Dockerfile to configure and execute them without import error. Gistable is publicly available at https://github.com/gistable/gistable.
机译：软件开发人员在线创建和共享代码以演示编程语言概念和编程任务。代码片段可以是解释和演示编程概念的有用方法，但可能并不总是直接可执行。代码段可以包含解析错误，或者如果环境包含未满足的依赖项，则无法执行。本文介绍了通过Github Gist系统共享的Python代码片段的可执行状态的实证分析，以及熟悉软件配置的开发人员正确配置和运行它们的能力。我们发现75.6％的GISTS需要非琐碎的配置来克服缺失的依赖项，配置文件，依赖于特定操作系统或其他一些环境配置。我们的研究还提出了当解决配置错误时，自然的假定开发人员在解决配置错误时正确的时间不到一半时间。我们还存在在Github的GIST系统上构建的Gistable，数据库和可扩展框架，它提供可执行的代码片段，可在软件工程中启用可重复的研究。 Gistable包含10,259个代码片段，大约5,000，使用dockerfile配置并在没有导入错误的情况下配置和执行它们。 Gistable在https://github.com/gistable/gistable公开使用。

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