Analyzing the Impact of Natural Language Processing over Feature Location in Models
Feature Location (FL) is a common task in the Software Engineering field, specially in maintenance and evolution of software products. The results of FL depend in a great manner in the style in which Feature Descriptions and software artifacts are written. Therefore, Natural Language Processing (NLP) techniques are used to process them. Through this paper, we analyze the influence of the most common NLP techniques over FL in Conceptual Models through Latent Semantic Indexing, and the influence of human participation when embedding domain knowledge in the process. We evaluated the techniques in a real-world industrial case study in the rolling stocks domain.
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Lukas Linsbauer Johannes Kepler University Linz, Thorsten Berger Chalmers University of Technology, Sweden / University of Gothenburg, Sweden, Paul Grünbacher JKU Linz, AustriaDOI Authorizer link
|Analyzing the Impact of Natural Language Processing over Feature Location in Models|
Raúl Lapeña San Jorge University, Spain, Jaime Font San Jorge University, Spain, Oscar Pastor Universitat Politècnica de València, Spain, Carlos Cetina San Jorge University, SpainDOI Authorizer link
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