从文档中提取信息,用于自动化软件测试

Patricia Lutsky
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引用次数: 6

摘要

基于自然语言的工具对于自动化软件工程,特别是自动化软件测试是有价值的。然而,自动化软件工程的努力很少包括自然语言文本,而不是专注于源代码或专门格式的编码知识。来自文本的规范信息(SIFT)工具展示了将现有文本直接合并到自动化测试系统中的潜力;它直接从从规范文档或用户手册中提取的信息生成测试。SIFT为使用特定于领域的解析技术提供了一个通用框架,并且在为OpenVMS操作系统接口例程构建测试时显示了它的实用性。
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Information extraction from documents for automating software testing

Natural-language-based tools can be valuable for automating software engineering, in particular for automating software testing. However, efforts to automate software engineering rarely include natural-language texts, instead of focusing on source code or on encoding knowledge in specialized formats. The specification information from text (SIFT) tool demonstrates the potential for incorporating existing texts directly into an automated testing system; it generates tests directly from information extracted from specification documents or user manuals. SIFT provides a general framework for using domain-specific parsing techniques, and has shown its utility in constructing tests for the OpenVMS operating system interface routines.

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