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Relevance-based abstraction identification: technique and evaluation

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>09/2011
<mark>Journal</mark>Requirements Engineering
Issue number3
Number of pages15
Pages (from-to)251-265
<mark>Original language</mark>English


When first approaching an unfamiliar domain or requirements document, it is often useful to get a quick grasp of what the essential concepts and entities in the domain are. This process is called abstraction identification, where the word abstraction refers to an entity or concept that has a particular significance in the domain. Abstraction identification has been proposed and evaluated as a useful technique in requirements engineering (RE). In this paper, we propose a new technique for automated abstraction identification called relevance-based abstraction identification (RAI), and evaluate its performance—in multiple configurations and through two refinements—compared to other tools and techniques proposed in the literature, where we find that RAI significantly outperforms previous techniques. We present an experiment measuring the effectiveness of RAI compared to human judgement, and discuss how RAI could be used to good effect in requirements engineering.