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- W35678840 abstract "A problem with model-based requirements engineering is that new projects may lack the data required to customize old models. Such data droughts are a common problem in software engineering and are particularly acute in early life cycle activities such as requirements engineering. When specific data relevant to a new project is missing, one technique is to simulate a model across the range of possibilities that might be relevant to a project. This generates voluminous output which can be summarized via a new machine learning technique called treatment learning." @default.
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- W35678840 date "2001-01-01" @default.
- W35678840 modified "2023-10-17" @default.
- W35678840 title "Reusing Models For Requirements Engineering" @default.
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