Details
| Original language | English |
|---|---|
| Title of host publication | 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08 |
| Publisher | IEEE Computer Society |
| Pages | 25-31 |
| Number of pages | 7 |
| ISBN (print) | 9780769536279 |
| Publication status | Published - 2008 |
| Event | 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08 - Barcelona, Spain Duration: 8 Sept 2008 → 8 Sept 2008 |
Publication series
| Name | 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08 |
|---|
Abstract
(SRS) aim at establishing a common ground of definitions. However, ambiguous terms as due to tacit knowledge are seldom captured in glossaries. In addition, even if they are captured, they are seldom read, because potential readers are convinced that they already know how the term is defined. Such misunderstandings introduce high risks in projects - especially because they are so hard to detect. Therefore, a trigger is needed to start a discussion about these potentially dangerous terms. In this paper we show how context aware Requirements Engineering tools can heuristically detect these terms and point out the risk attached. We introduce two simple, yet powerful heuristics: Occurence counting detects important terms, comparison with old glossaries detects terms that others found worth defining in a glossary. Thus, we make use of glossaries from past projects to suggest possible terms of interest for current projects. Our approach was implemented and applied to six software projects. Based on these experiences we show the effectivity of our heuristics and how they could be used by learning organizations to reduce such ambiguity risks in their specific domain.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Software
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2008 1st International Workshop on Managing Requirements Knowledge, MARK'08. IEEE Computer Society, 2008. p. 25-31 4797435 (2008 1st International Workshop on Managing Requirements Knowledge, MARK'08).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Recommending terms for glossaries
T2 - 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08
AU - Knauss, Eric
AU - Meyer, Sebastian
AU - Schneider, Kurt
PY - 2008
Y1 - 2008
N2 - (SRS) aim at establishing a common ground of definitions. However, ambiguous terms as due to tacit knowledge are seldom captured in glossaries. In addition, even if they are captured, they are seldom read, because potential readers are convinced that they already know how the term is defined. Such misunderstandings introduce high risks in projects - especially because they are so hard to detect. Therefore, a trigger is needed to start a discussion about these potentially dangerous terms. In this paper we show how context aware Requirements Engineering tools can heuristically detect these terms and point out the risk attached. We introduce two simple, yet powerful heuristics: Occurence counting detects important terms, comparison with old glossaries detects terms that others found worth defining in a glossary. Thus, we make use of glossaries from past projects to suggest possible terms of interest for current projects. Our approach was implemented and applied to six software projects. Based on these experiences we show the effectivity of our heuristics and how they could be used by learning organizations to reduce such ambiguity risks in their specific domain.
AB - (SRS) aim at establishing a common ground of definitions. However, ambiguous terms as due to tacit knowledge are seldom captured in glossaries. In addition, even if they are captured, they are seldom read, because potential readers are convinced that they already know how the term is defined. Such misunderstandings introduce high risks in projects - especially because they are so hard to detect. Therefore, a trigger is needed to start a discussion about these potentially dangerous terms. In this paper we show how context aware Requirements Engineering tools can heuristically detect these terms and point out the risk attached. We introduce two simple, yet powerful heuristics: Occurence counting detects important terms, comparison with old glossaries detects terms that others found worth defining in a glossary. Thus, we make use of glossaries from past projects to suggest possible terms of interest for current projects. Our approach was implemented and applied to six software projects. Based on these experiences we show the effectivity of our heuristics and how they could be used by learning organizations to reduce such ambiguity risks in their specific domain.
UR - http://www.scopus.com/inward/record.url?scp=64949130042&partnerID=8YFLogxK
U2 - 10.1109/MARK.2008.8
DO - 10.1109/MARK.2008.8
M3 - Conference contribution
AN - SCOPUS:64949130042
SN - 9780769536279
T3 - 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08
SP - 25
EP - 31
BT - 2008 1st International Workshop on Managing Requirements Knowledge, MARK'08
PB - IEEE Computer Society
Y2 - 8 September 2008 through 8 September 2008
ER -