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Keeping Evolving Requirements and Acceptance Tests Aligned with Automatically Generated Guidance

机译:保持不断发展的要求和接受测试与自动生成的指导对齐

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[Context and motivation] When a software-based system evolves, its requirements continuously change. This affects the acceptance tests, which must be adapted accordingly in order to maintain the quality of the evolving system. [Question/problem] In practice, requirements and acceptance test documents are not always aligned with each other, nor with the actual system behavior. Such inconsistencies may introduce software quality problems, unintended costs and project delays. [Principal ideas/results] To keep evolving requirements and their associated acceptance tests aligned, we are developing an approach called GuideGen that automatically generates guidance in natural language on how to modify impacted acceptance tests when a requirement is changed. We evaluated GuideGen using real-world data from three companies. For 262 non-trivial changes of requirements, we generated guidance on how to change the affected acceptance tests and evaluated the quality of this guidance with seven experts. The correctness of the guidance produced by our approach ranged between 67 and 89% of all changes for the three evaluated data sets. We further found that our approach performed better for agile requirements than for traditional ones. [Contribution] Our approach facilitates the alignment of acceptance tests with the actual requirements and also improves the communication between requirements engineers and testers.
机译:[背景和动机]当基于软件的系统发展时,其要求不断变化。这会影响验收测试,必须相应地调整,以便保持不断发展的系统的质量。 [问题/问题]在实践中,要求和验收测试文档并不总是彼此对齐,也不会与实际的系统行为保持一致。此类不一致可能会引入软件质量问题,意外成本和项目延误。 [主要思想/结果]为了保持不断变化的要求及其相关的验收测试对齐,我们正在开发一种名为GUINGGEN的方法,该方法可以在改变要求时自动为如何修改受影响的接受测试进行自然语言生成指导。我们使用来自三家公司的真实数据进行评估。对于262个非琐碎的要求变动,我们为如何改变受影响的接受测试而产生指导,并评估了七位专家的这种指导的质量。我们的方法产生的指导的正确性范围在67%至89%之间的所有变化之间的所有变化的数据集之间。我们进一步发现,我们的方法对于敏捷要求而言比传统方式更好。 [贡献]我们的方法有助于与实际要求进行验收测试的对准,也提高了需求工程师和测试人员之间的沟通。

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