A clustering-based approach for discovering flaws in requirements specifications
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Automatic analysis of multimodal requirements: a research preview
REFSQ'12 Proceedings of the 18th international conference on Requirements Engineering: foundation for software quality
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High-level software artifacts, such as requirements, domain-specific requirements, and so on, are an important source of information that is often neglected during the reverse- and re-engineering processes. We posit that domain specific pre-requirements information (PRI) can be obtained by eliciting the stakeholders’ understanding of generic systems or domains. We discuss the semi-automatic recovery of domain-specific PRI that can then be used during reverse- and re-engineering, for example, to recover traceability links or to assess the degree of obsolescence of a system with respect to competing systems and the clients’ expectations. We present a method using partition around medoids and agglomerative clustering for obtaining, structuring, analyzing, and labeling textual PRI from a group of diverse stakeholders. We validate our method using PRI for the development of a generic Web browser provided by 22 different stakeholders. We show that, for a similarity threshold of about 0.36, about 55% of the PRI were common to two or more stakeholders and 42% were outliers. We automatically label the common and outlier PRI (82% correctly labeled), and obtain 74% accuracy for the similarity threshold of 0.36 (78% for a threshold of 0.5). We assess the recall and precision of the method, and compare the labeled PRI to a generic Web browser requirements specification.