Cruz, DanielFigueiredo, EduardoMartinez, Jabier2024-07-242024-07-242019-02-06Cruz , D , Figueiredo , E & Martinez , J 2019 , A literature review and comparison of three feature location techniques using ArgoUML-SPL . in Proceedings of the 13th International Workshop on Variability Modelling of Software-Intensive Systems, VAMOS 2019 . ACM International Conference Proceeding Series , Association for Computing Machinery , 13th International Workshop on Variability Modelling of Software-Intensive Systems, VAMOS 2019 , Leuven , Belgium , 6/02/19 . https://doi.org/10.1145/3302333.3302343conference9781450366489https://hdl.handle.net/11556/1884Publisher Copyright: © 2019 Association for Computing Machinery.Over the last decades, the adoption of Software Product Line (SPL) engineering for supporting software reuse has increased. An SPL can be extracted from one single product or from a family of related software products, and feature location strategies are widely used for variability mining. Several feature location strategies have been proposed in the literature and they usually aim to map a feature to its source code implementation. In this paper, we present a systematic literature review that identifies and characterizes existing feature location strategies. We also evaluated three different strategies based on textual information retrieval in the context of the ArgoUML-SPL feature location case study. In this evaluation, we compare the strategies based on their ability to correctly identify the source code of several features from ArgoUML-SPL ground truth. We then discuss the strengths and weaknesses of each feature location strategy.enginfo:eu-repo/semantics/restrictedAccessA literature review and comparison of three feature location techniques using ArgoUML-SPLconference output10.1145/3302333.3302343BenchmarkFeature locationReverse engineeringSoftware product linesVariability miningSoftwareHuman-Computer InteractionComputer Vision and Pattern RecognitionComputer Networks and Communicationshttp://www.scopus.com/inward/record.url?scp=85123041036&partnerID=8YFLogxK