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Text analytics for discovering concerns in requirements documents
Recent trends in the software engineering community advocate for the improvement of textual requirements using (semi-)automated tools. In particular, the detection of incomplete or understated concerns at early development stages hold potential, due to the negative effects of untreated concerns on the development. Assistive tools can be of great help for analysts to get a quick picture of the requirements and narrow down the search for latent concerns. In this article, we present a tool called REAssistant that supports the process of discovering concerns in textual specifications. To do so, the tool relies on the UIMA framework and EMF-based technologies to provide an extensible architecture for concern-related analyses. Currently, the tool is configured to process textual use cases by using a number of textual analytics modules that identify lexical, syntactical and semantic entities in the specifications.We have conducted a preliminary evaluation of our tool in two case studies, obtaining promising results when comparing to manual inspections and to another tool.
Sociedad Argentina de Informática e Investigación Operativa
Ciencias Informáticas, software requirement, tool-support,, Natural language processing
Ciencias Informáticas, software requirement, tool-support,, Natural language processing
- National University of La Plata Argentina
- National University of La Plata Argentina
Recent trends in the software engineering community advocate for the improvement of textual requirements using (semi-)automated tools. In particular, the detection of incomplete or understated concerns at early development stages hold potential, due to the negative effects of untreated concerns on the development. Assistive tools can be of great help for analysts to get a quick picture of the requirements and narrow down the search for latent concerns. In this article, we present a tool called REAssistant that supports the process of discovering concerns in textual specifications. To do so, the tool relies on the UIMA framework and EMF-based technologies to provide an extensible architecture for concern-related analyses. Currently, the tool is configured to process textual use cases by using a number of textual analytics modules that identify lexical, syntactical and semantic entities in the specifications.We have conducted a preliminary evaluation of our tool in two case studies, obtaining promising results when comparing to manual inspections and to another tool.
Sociedad Argentina de Informática e Investigación Operativa