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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Mon 23 Oct
|13:30 - 13:55|
Lukas LinsbauerJohannes Kepler University Linz, Thorsten BergerChalmers University of Technology, Sweden / University of Gothenburg, Sweden, Paul GrünbacherJKU Linz, AustriaDOI Authorizer link
|13:55 - 14:20|
Raúl LapeñaSan Jorge University, Spain, Jaime FontSan Jorge University, Spain, Oscar PastorUniversitat Politècnica de València, Spain, Carlos CetinaSan Jorge University, SpainDOI Authorizer link
|14:20 - 14:45|
How Preprocessor Annotations (Do Not) Affect Maintainability: A Case Study on Change-PronenessBest Paper
Wolfram FenskeUniversity of Magdeburg, Germany, Sandro SchulzeUniversity of Magdeburg, Germany, Gunter SaakeUniversity of Magdeburg, GermanyDOI Authorizer link