代码复杂化：从代码推荐到逻辑推荐
Code Sophistication: From Code Recommendation to Logic Recommendation
摘要：
一个典型的编程方法是首先编写主要的执行场景，然后专注于填充替代行为和角落案例。但是，几乎总是存在触发非典型行为的不寻常条件，这些行为在程序规范中很难预测，因此通常没有编码。在本文中，我们考虑的问题，检测和推荐这种缺失的行为，我们称之为代码复杂性的任务。以前对编码助手的研究通常集中在基于预期行为的规范推荐代码片段。相比之下，代码复杂性发生在没有规范的情况下，旨在帮助开发人员完成他们的程序逻辑与缺失和未指定的行为。我们概述了这个问题的研究挑战，并提出了早期的结果，显示如何利用代码结构和输入参数的使用信息，可以完成程序逻辑。
英文摘要：
A typical approach to programming is to first code the main execution scenario, and then focus on filling out alternative behaviors and corner cases. But, almost always, there exist unusual conditions that trigger atypical behaviors, which are hard to predict in program specifications, and are thus often not coded. In this paper, we consider the problem of detecting and recommending such missing behaviors, a task that we call code sophistication. Previous research on coding assistants usually focuses on recommending code fragments based on specifications of the intended behavior. In contrast, code sophistication happens in the absence of a specification, aiming to help developers complete the logic of their programs with missing and unspecified behaviors. We outline the research challenges to this problem and present early results showing how program logic can be completed by leveraging code structure and information about the usage of input parameters.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
