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Information and Software Technology
Article . 2013 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2013
Data sources: DBLP
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The state of the art in automated requirements elicitation

Authors: Hendrik Meth; Manuel Brhel; Alexander Maedche;

The state of the art in automated requirements elicitation

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.

Country
Germany
Keywords

info:eu-repo/classification/ddc/330, 330, ddc:330, Economics

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    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
58
Top 10%
Top 10%
Top 10%
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