Please use this identifier to cite or link to this item: https://repositorio.usj.es/handle/123456789/389

Title: Evaluating Low-Cost in Internal Crowdsourcing for Software Engineering: The Case of Feature Location in an Industrial Environment
Authors: Pérez, Francisca ORCID SCOPUSID
Marcén, Ana Cristina ORCID SCOPUSID
Lapeña, Raúl SCOPUSID
Cetina, Carlos ORCID RESEARCHERID SCOPUSID
Keywords: Ingeniería de software de crowdsourcing; Crowdsourcing; Recuperación de información colaborativa; Reformulación de consultas
Issue Date: 17-Apr-2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Perez, F., Marcen, A. C., Lapena, R., & Cetina, C. (2020). Evaluating low-cost in internal crowdsourcing for software engineering: The case of feature location in an industrial environment. IEEE Access, 8, 65745-65757. doi:10.1109/ACCESS.2020.2985915
Abstract: Internal crowdsourcing in software engineering is a mechanism for recruiting engineers to carry out more ef ciently software engineering tasks. However, engineers are busy resources and time is a valuable asset in industry, which hinders internal crowdsourcing in software engineering from becoming a widespread practice. In this work, we propose a low-cost variant of internal crowdsourcing for locating features in models, which limits the time that engineers can spend for providing knowledge. Our approach uses the knowledge provided by the internal crowd to automatically reformulate an initial feature description. The result is taken as input to automatically locate the relevant model fragment using Latent Semantic Indexing. We evaluate our approach using four query reformulation techniques in a real-world case study from our industrial partner.We compare the results of our approach in terms of recall, precision and F-measure with a baseline by means of statistical methods to show that the impact of the results of our approach is signi cant. Despite the limitation of time, the results showthat low-cost in internal crowdsourcing improves signi cantly the results in an industrial context where engineers' availability is scarce.
URI: https://repositorio.usj.es/handle/123456789/389
ISSN: 2169-3536
Appears in Collections:Artículos de revistas

Files in This Item:
File Description SizeFormat 
Evaluating Low-Cost in Internal Crowdsourcing for Software Engineering.pdf1,45 MBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons