DocumentCode :
713915
Title :
Towards a Model of Topic Relevance during requirements elicitation - Preliminary results
Author :
Burnay, Corentin ; Jureta, Ivan ; Faulkner, Stephane
Author_Institution :
Fonds de la Rech. Sci., Brussels, Belgium
fYear :
2015
fDate :
13-15 May 2015
Firstpage :
151
Lastpage :
158
Abstract :
Requirements elicitation is the activity in requirements engineering (RE) which focuses on the collection of information about requirements of the system-to-be and its environment. One important challenge is elicitation incompleteness; it occurs when information, which may have been relevant for requirements engineering, is not elicited. This may be due to various factors, such as that the requirements engineer asked no questions about it, and the stakeholders did not consider it important. To help requirements engineers reduce elicitation incompleteness, we propose the so-called Model of Elicitation Topic Relevance (METRe). METRe is a diagram that shows topics which can be discussed during requirements elicitation, and expresses the relative importance of each topic to stakeholders and engineers. The more likely it is that a stakeholder or engineer will discuss the topic spontaneously during elicitation, the more important it is for, respectively, stakeholders or engineers. METRe was made by combining our prior work on the importance of topics to stakeholders, and a new round of empirical research. The new round consisted of data collection using a survey, in which the various topics were presented to and evaluated by 50 IT-experts in Belgium. Subjects were asked to evaluate the relative importance of the topics, that is, how relevant they find these topics when eliciting information, and how pro-active they would be in collecting them.
Keywords :
formal specification; formal verification; management information systems; systems analysis; METRe; elicitation incompleteness; model of elicitation topic relevance; requirements elicitation; requirements engineering; Companies; Context; Data collection; Data models; Interviews; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research Challenges in Information Science (RCIS), 2015 IEEE 9th International Conference on
Conference_Location :
Athens
Type :
conf
DOI :
10.1109/RCIS.2015.7128875
Filename :
7128875
Link To Document :
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