The state of the art in automated requirements elicitation

  • Authors:

  • Hendrik Meth;Manuel Brhel;Alexander Maedche

  • Affiliations:

  • Institute for Enterprise Systems, University of Mannheim, L 15, 1-6, 68131 Mannheim, Germany;Chair of Information Systems IV, University of Mannheim, L 15, 1-6, 68131 Mannheim, Germany;Institute for Enterprise Systems, University of Mannheim, L 15, 1-6, 68131 Mannheim, Germany and Chair of Information Systems IV, University of Mannheim, L 15, 1-6, 68131 Mannheim, Germany

  • Venue:
  • Information and Software Technology
  • Year:
  • 2013

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Abstract

Context: In large software development projects a huge number of unstructured text documents from various stakeholders becomes available and needs to be analyzed and transformed into structured requirements. This elicitation process is known to be time-consuming and error-prone when performed manually by a requirements engineer. Consequently, substantial research has been done to automate the process through a plethora of tools and technologies. Objective: This paper aims to capture the current state of automated requirements elicitation and derive future research directions by identifying gaps in the existing body of knowledge and through relating existing works to each other. More specifically, we are investigating the following research question: What is the state of the art in research covering tool support for automated requirements elicitation from natural language documents? Method: A systematic review of the literature in automated requirements elicitation is performed. Identified works are categorized using an analysis framework comprising tool categories, technological concepts and evaluation approaches. Furthermore, the identified papers are related to each other through citation analysis to trace the development of the research field. Results: We identified, categorized and related 36 relevant publications. Summarizing the observations we made, we propose future research to (1) investigate alternative elicitation paradigms going beyond a pure automation approach (2) compare the effects of different types of knowledge on elicitation results (3) apply comparative evaluation methods and multi-dimensional evaluation measures and (4) strive for a closer integration of research activities across the sub-fields of automatic requirements elicitation. Conclusion: Through the results of our paper, we intend to contribute to the Requirements Engineering body of knowledge by (1) conceptualizing an analysis framework for works in the area of automated requirements elicitation, going beyond former classifications (2) providing an extensive overview and categorization of existing works in this area (3) formulating concise directions for future research.