2016
Journal article  Open Access

Ambiguity and tacit knowledge in requirements elicitation interviews

Ferrari A., Spoletini P., Gnesi S.

Information Systems  Requirements elicitation  Natural language  Software  Requirements engineering  Interviews  Ambiguity 

Interviews are the most common and effective means to perform requirements elicitation and support knowledge transfer between a customer and a requirements analyst. Ambiguity in communication is often perceived as a major obstacle for knowledge transfer, which could lead to unclear and incomplete requirements documents. In this paper, we analyze the role of ambiguity in requirements elicitation interviews, when requirements are still tacit ideas to be surfaced. To study the phenomenon, we performed a set of 34 customer-analyst interviews. This experience was used as a baseline to define a framework to categorize ambiguity. The framework presents the notion of ambiguity as a class of four main sub-phenomena, namely unclarity, multiple understanding, incorrect disambiguation and correct disambiguation. We present examples of ambiguities from our interviews to illustrate the different categories, and we highlight the pragmatic components that determine the occurrence of ambiguity. Along the study, we discovered a peculiar relation between ambiguity and tacit knowledge in interviews. Tacit knowledge is the knowledge that a customer has but does not pass to the analyst for any reason. From our experience, we have discovered that, rather than an obstacle, the occurrence of an ambiguity is often a resource for discovering tacit knowledge. Again, examples are presented from our interviews to support this vision.

Source: Requirements engineering (Lond., Print) 21 (2016): 333–355. doi:10.1007/s00766-016-0249-3

Publisher: Springer., London, Regno Unito


Metrics



Back to previous page
BibTeX entry
@article{oai:it.cnr:prodotti:353983,
	title = {Ambiguity and tacit knowledge in requirements elicitation interviews},
	author = {Ferrari A. and Spoletini P. and Gnesi S.},
	publisher = {Springer., London, Regno Unito},
	doi = {10.1007/s00766-016-0249-3},
	journal = {Requirements engineering (Lond., Print)},
	volume = {21},
	pages = {333–355},
	year = {2016}
}

LEARN PAD
Model-Based Social Learning for Public Administrations


OpenAIRE