Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/29453
Author(s): | Reis, J. P. dos. Brito e Abreu, F. Carneiro, G. de F. Almeida, D. |
Editor: | Fernandes, J. M., Travassos, G. H., Lenarduzzi, V., and Li, X. |
Date: | 2023 |
Title: | Scientific workflow management for software quality assessment replication: An open source architecture |
Volume: | 1871 |
Book title/volume: | Quality of Information and Communications Technology. Communications in Computer and Information Science |
Pages: | 1 - 14 |
Event title: | 16th International Conference on the Quality of Information and Communications Technology, QUATIC 2023 |
Reference: | Reis, J. P. dos., Brito e Abreu, F., Carneiro, G. de F., & Almeida, D. (2023). Scientific workflow management for software quality assessment replication: An open source architecture. In J. M. Fernandes, G. H. Travassos, V. Lenarduzzi, & X. Li (Eds.), Quality of Information and Communications Technology. Communications in Computer and Information Science (vol.1871, pp. 1-14). Springer. https://doi.org/10.1007/978-3-031-43703-8_1 |
ISSN: | 1865-0929 |
ISBN: | 978-3-031-43703-8 |
DOI (Digital Object Identifier): | 10.1007/978-3-031-43703-8_1 |
Keywords: | Scientific workflow Software quality Quality assessment Replication Code smells Open source |
Abstract: | Replication of research experiments is important for establishing the validity and generalizability of findings, building a cumulative body of knowledge, and addressing issues of publication bias. The quest for replication led to the concept of scientific workflow, a structured and systematic process for carrying out research that defines a series of steps, methods, and tools needed to collect and analyze data, and generate results. In this study, we propose a cloud-based framework built upon open source software, which facilitates the construction and execution of workflows for the replication/reproduction of software quality studies. To demonstrate its feasibility, we describe the replication of a software quality experiment on automatically detecting code smells with machine learning techniques. The proposed framework can mitigate two types of validity threats in software quality experiments: (i) internal validity threats due to instrumentation, since the same measurement instruments can be used in replications, thus not affecting the validity of the results, and (ii) external validity threats due to reduced generalizability, since different researchers can more easily replicate experiments with different settings, populations, and contexts while reusing the same scientific workflow. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | ISTAR-CRI - Comunicações a conferências internacionais |
Files in This Item:
File | Size | Format | |
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conferenceobject_97795.pdf | 391,1 kB | Adobe PDF | View/Open |
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