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Managing Ambiguity in Programming by Finding Unambiguous Examples

机译:通过查找明确的示例来管理编程中的歧义

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摘要

We propose a new way to raise the level of discourse in the programming process: permit ambiguity, but manage it by linking it to unambiguous examples. This allows programming environments to work with informal descriptions that lack precise semantics, such as natural language descriptions or conceptual diagrams, without requiring programmers to formulate their ideas in a formal language first. As an example of this idea, we present Zones, a code search and reuse interface that connects code with ambiguous natural language statements about its purpose. The backend, called ProcedureSpace, relates purpose statements, static code analysis features, and natural language background knowledge. ProcedureSpace can search for code given statements of purpose or vice versa, and can find code that was never annotated or commented. Since completed Zones searches become annotations, system coverage grows with user interaction. Users in a preliminary study found that reasoning jointly over natural language and programming language helped them reuse code.
机译:我们提出了一种提高编程过程中话语水平的新方法:允许歧义,但通过将其链接到明确的示例进行管理。这使编程环境可以使用缺乏精确语义的非正式描述(例如自然语言描述或概念图)来工作,而无需程序员先以正式语言来表达他们的想法。作为该想法的一个示例,我们介绍了Zones,这是一个代码搜索和重用接口,该接口将代码与有关其目的的模棱两可的自然语言语句连接起来。后端称为ProcedureSpace,与目的陈述,静态代码分析功能和自然语言背景知识相关。 ProcedureSpace可以搜索给出给定目的陈述的代码,反之亦然,并且可以找到从未注释或注释过的代码。由于完成的区域搜索成为注释,因此系统覆盖范围随着用户交互的增加而增加。初步研究的用户发现,通过自然语言和编程语言共同进行推理有助于他们重用代码。

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