Supplementary material of the study “Unveiling the Landscape of System Thinking Modeling Tools Use in Software Engineering"
Creators: name: de Souza Borges, Julia
name: Felippe Neitzke Lahass, Thiago
name: Apolinario, Amanda
name: Santos Júnior, Paulo Sérgio
name: Barcellos, Monalessa P.
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 461203
subject: Formal methods for software

description: DescriptionThis artifact represents the <b>study package of a systematic mapping conducted to investigate how System Thinking (ST) modeling tools have been applied in Software Engineering (SE)</b>. It provides detailed documentation of the research protocol, including search strategies, inclusion and exclusion criteria, and analysis methods, ensuring the study’s replicability and enabling other researchers to reproduce or extend the research based on the same methodological guidelines. Moreover, the artifact presents the results of each stage of the publication selection process, the extracted data, and the categorizations made, promoting transparency and facilitating the audit of the results. By organizing information in a structured manner, the artifact becomes a valuable resource l not only for the current study but also for future reviews or expansions of knowledge about ST in SE. The package includes a set of spreadsheets detailing the study protocol, selected publications, extracted data, and the corresponding Parsifal file.Paper ReferenceThis artifact is related to the paper ‘Unveiling the Landscape of System Thinking Modeling Tools Use in Software Engineering’, available on SBC OpenLib (SOL). You can access the PDF of the paper directly on SOL or in this repository.Repository OrganizationAt the root of the repository, you will find three key files related to the Systematic Mapping Review, along with the PDF of the paper and license file:• _SBES_2024__Unveiling_the_Landscape_of_ST_Modeling_Tools_Use_in_SE-autores: This file contains the paper.• PARSIFAL-unveiling-landscape-ST-SE.pdf: This file encompasses comprehensive data from the entire process, including the PICOC framework, research questions, keywords and their synonyms, search string, inclusion and exclusion criteria, data extraction forms, and the search strings used.• csv-SLR-MR-ST-SE.csv: Spreadsheets detailing the results of the systematic mapping process in <b>csv</b> format.• SLR-MR-ST-SE.xlsx: Spreadsheets detailing the results of the systematic mapping process in <b>Excel</b> format.• legalcode.txt: All files are distributed under the CC BY 4.0 license, allowing for sharing and adaptation use with appropriate attribution.• README.md and README.pdf: A markdown file containing essential information about the repository, including instructions on how to navigate. A PDF version of the readme file, providing the same essential information in a format that is easy to view and print.Ethical and Legal StatementsThis repository is protected under the <b>CC BY 4.0 license</b>. This means you are free to share and adapt the material for any purpose, even commercially, as long as you provide appropriate credit, indicate if changes were made, and do not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Be sure to review the terms of this license before using the data and artifacts in this repository.Storage RequirementsThis repository requires approximately <b>1 MB</b> of storage for the complete use of all artifacts. Ensure you have sufficient space and a stable connection to clone or download the necessary files.How to citeThis study and its package are publicly available on Figshare under the DOI https://doi.org/10.6084/m9.figshare.25647963.v7.To cite this <b>artifact package</b>, please use:de Souza Borges, Julia; Felippe Neitzke Lahass, Thiago; Apolinario, Amanda; Santos Júnior, Paulo Sérgio; Barcellos, Monalessa P. (2024). Supplementary material of the study “Unveiling the Landscape of System Thinking Modeling Tools Use in Software Engineering". figshare. Conference contribution. https://doi.org/10.6084/m9.figshare.25647963.v7To cite this <b>paper</b>, please use:BORGES, J. S. ; LAHASS, T. F. N. ; APOLINARIO, A. B. ; SANTOS JUNIOR, P. S. ; BARCELLOS, M. P. . Unveiling the Landscape of System Thinking Modeling Tools Use in Software Engineering. In: XXXVIII Brazilian Symposium on Software Engineering (SBES 2024), 2024, Curitiba - PR. Proceedings of the XXXVIII Brazilian Symposium on Software Engineering (SBES 2024), 2024.ACKNOWLEDGMENTSThis research is supported by the Coordination for the Improvement of Higher Education Personnel - CAPES Brazil (Finance Code 001) and the Espírito Santo Research and Innovation Support Foundation - FAPES (Processes 2023-5L1FC, 2022-NGKM5, 2021-GL60J, and T.O. 1022/2022).Paper AbstractContext: Software organizations involve several processes, people, practices, culture, and other factors that affect their behavior. Understanding the organizational environment is crucial for improving processes and products. System Thinking (ST) provides several tools that help in this matter. ST views an organization as a system, comprising elements and interconnections coherently organized in a structure that produces a characteristic set of behaviors. Objective: Given ST's successful application in different areas of industry and academia, and its potential to address Software Engineering (SE) problems, we decided to investigate how ST modeling tools have been used in SE. Our goal is to provide a panorama of the use of such tools in SE, identify gaps, and shine a light on research opportunities. Method: We carried out a systematic literature mapping, analyzing 704 publications. From these, we identified 10 publications addressing the use of ST modeling tools in SE and conducted an in-depth analysis. Results: ST modeling tools have been employed to tackle SE issues in organizational contexts and to model and analyze the results of SE studies. Project Management and Requirements Engineering have been the most common processes in which these tools have been applied. ST modeling tools have helped get a holistic view of complex systems and identify strategies to address problematic behaviors that affect SE outcomes. Causal loop diagrams, depicting cause-and-effect relationships and feedback loops, have been the predominant tool. The lack of knowledge necessary for using the tools has been a challenge. Conclusion: In summary, the results indicate that using ST tools in SE holds promise. Nevertheless, they also suggest that ST modeling tools have been underexplored in SE. Hence, further investigation into their potential for enhancing SE products and processes is warranted.