Abstract
This chapter presents a methodology for identification of crosscutting concerns in textual requirements along with its supporting tool EA-Miner. This chapter discusses how EA-Miner uses natural language processing techniques in aspect identification and structuring using a requirements level feature model as an example. The process is illustrated using the Car Crash case study.
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Notes
- 1.
The details on concept identification are presented in [23].
- 2.
The model is derived using the ArborCraft tool. Any other way of model construction that has text related to the respective features would be equally suitable. Although the process of this specific model derivation is irrelevant to the present chapter, the interested reader is referred to [25] for more detail on ArborCraft and its use.
- 3.
This has been referred to as “in-text” variability in [25].
- 4.
This is a peculiarity of the ArborCraft tool used for the generation of the initial feature model. In this tool all text of the higher level features is also considered within the lower level ones.
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Weston, N., Chitchyan, R., Sampaio, A., Rashid, A., Greenwood, P. (2013). Aspect Identification in Textual Requirements with EA-Miner. In: Moreira, A., Chitchyan, R., Araújo, J., Rashid, A. (eds) Aspect-Oriented Requirements Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38640-4_1
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