Automated Inspection of Industrial Use Case Models Inferred from Textual Descriptions

Use cases are increasingly important for requirements capture. They feed into downstream activities such as requirements specification and test generation. The quality of use cases is thus a concern, and there are numerous guidelines for use case style and content. However, most use cases are written in (possibly structured) natural language, and their characteristics and quality can vary widely. We have developed an approach for automated inspection of use cases based on the construction and analysis of models of use cases. Use case texts are analyzed by a Linguistic Engine that produces an abstract model of the use case. The model records linguistic properties and is analyzed to evaluate additional properties, such as integrity, completeness, complexity, concurrency, dataflow, and others. Feedback is provided to the user in the form of error and warning messages. We also provide guidelines to facilitate the writing of linguistically analyzable use cases. Authors can iteratively refine their use cases to eliminate problems. Appropriately correct use cases can be used as input for flow-graph or test-case generation.

We describe a prototype IDE that implements this approach and report on experience in analyzing and refining sample groups of industrial use cases.

By: Palani Kumanan; Amit Paradkar; Avik Sinha; Stanley M. Sutton Jr.

Published in: RC24729 in 2009


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