Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - ArborCraft
T2 - automatic feature models from textual requirements documents
AU - Weston, Nathan
AU - Rashid, Awais
PY - 2009
Y1 - 2009
N2 - One of the tasks facing requirements engineers working in the field of Product Line Engineering is the creation of feature models, which represent the domain of the product line and from which product configurations can be derived. Requirements documents, which are to be mined for this information, are often very large and written in potentially ambiguous natural language, and can be written over a long period of time by various authors. This makes the engineer's task very arduous, and a clear separation of concerns is often difficult to infer from textual documents. We present ArborCraft, a tool which automatically mines textual requirements documents, identifies features based on natural-language processing techniques, and produces a candidate feature model. We show that this can significantly reduce the burden on the requirements engineer and promote separation of concerns early in the Product Line Engineering process.
AB - One of the tasks facing requirements engineers working in the field of Product Line Engineering is the creation of feature models, which represent the domain of the product line and from which product configurations can be derived. Requirements documents, which are to be mined for this information, are often very large and written in potentially ambiguous natural language, and can be written over a long period of time by various authors. This makes the engineer's task very arduous, and a clear separation of concerns is often difficult to infer from textual documents. We present ArborCraft, a tool which automatically mines textual requirements documents, identifies features based on natural-language processing techniques, and produces a candidate feature model. We show that this can significantly reduce the burden on the requirements engineer and promote separation of concerns early in the Product Line Engineering process.
U2 - 10.1145/1509825.1509836
DO - 10.1145/1509825.1509836
M3 - Conference contribution/Paper
SP - 45
EP - 46
BT - EA '09 Proceedings of the 15th workshop on Early aspects
PB - ACM
CY - New York, NY, USA
ER -