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Managing Ambiguity in Programming by Finding Unambiguous Examples

机译:通过查找明确的例子来管理编程中的歧义

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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:我们提出了一种新的方法来提高编程过程中的话语水平:允许歧义,但通过将其链接到明确的例子来管理它。这允许编程环境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,而无需先进的程序员首先以正式语言制定他们的想法。作为这个想法的示例,我们呈现区域,代码搜索和重用接口,该接口连接了关于其目的的模糊自然语言陈述的代码。后端称为过程空间,涉及目的语句,静态代码分析功能和自然语言背景知识。过程空间可以搜索给定的代码或者反之亦然,可以找到从未注释或评论的代码。由于已完成的区域搜索成为注释,系统覆盖与用户交互一起增长。在初步研究中的用户发现,在自然语言和编程语言中共同推理,帮助他们重用代码。

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