CaLMo: A Tool to support the use of Causal Loop Diagram in Software Engineering

  • Amanda Brito Apolinário UFES
  • Thiago Felippe Neitzke Lahass UFES
  • Júlia de Souza Borges UFES
  • Paulo Sérgio dos Santos Júnior IFES
  • Monalessa P. Barcellos UFES

Resumo


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) can help in this matter. It views an organization as a system composed of elements and interconnections coherently organized in a structure that produces a characteristic set of behaviors. ST offers several tools, among which the Causal Loop Diagram (CLD) stands out. It represents feedbackdriven behaviors in complex systems and enables the visualization of organizational dynamics and the identification of systemic patterns. By understanding how the organization behaves, it is possible to identify problems and define actions aimed at improving products and processes. Currently, the creation of CLDs often relies on generic drawing/diagramming tools, which are prone to modeling errors and do not support the identification or analysis of behavior patterns. Additionally, most of these tools are limited to drawing the diagram and do not store the underlying represented data. To address this gap, this paper presents CaLMo, a tool designed to assist software engineers in modeling and analyzing CLDs to support Software Engineering tasks. CaLMo allows users to define variables, establish causal links between them, and detect feedback loops. Moreover, it automatically identifies archetypes that represent behavior patterns. We illustrate the use of the tool considering a case study in which CLDs were used to support the adoption of agile practices in an organization. A short video showing CaLMo is available at https://doi.org/10.5281/zenodo.15477387.

Palavras-chave: Causal Loop Diagram, System Thinking, Software Engineering, Modeling Tool

Referências

Monalessa Perini Barcellos. 2020. Towards a Framework for Continuous Software Engineering. In Proceedings of the 34th Brazilian Symposium on Software Engineering (Natal, Brazil) (SBES ’20). Association for Computing Machinery, New York, NY, USA, 626–631. DOI: 10.1145/3422392.3422469

Júlia Borges, Thiago Lahass, Amanda Apolinário, Paulo Santos Júnior, and Monalessa Barcellos. 2024. Unveiling the Landscape of System Thinking Modeling Tools Use in Software Engineering. In Anais do XXXVIII Simpósio Brasileiro de Engenharia de Software (Curitiba/PR). SBC, Porto Alegre, RS, Brasil, 47–57. DOI: 10.5753/sbes.2024.3232

Timothy Clancy. 2018. Systems thinking: Three system archetypes every manager should know. IEEE Engineering Management Review 46, 2 (2018), 32–41.

Paulo Sérgio dos Santos Júnior, Monalessa Perini Barcellos, and Rodrigo Fernandes Calhau. 2022. First step climbing the Stairway to Heaven Model-Results from a Case Study in Industry. Journal of Software Engineering Research and Development 10 (2022), 5–1. DOI: 10.5753/jserd.2021.1992

Manfred Drack and Wilfried Apfalter. 2007. Is Paul A. Weiss’ and Ludwig von Bertalanffy’s system thinking still valid today? Systems Research and Behavioral Science: The Official Journal of the International Federation for Systems Research 24, 5 (2007), 537–546. DOI: 10.1002/sres.855

M. Fakhimi, D. Robertson, and T. Boness. 2021. THE BASIC PRINCIPLES OF SYSTEMS THINKING AND SYSTEM DYNAMICS. Proceedings of the Operational Research Society Simulation Workshop (2021). DOI: 10.36819/SW21.003

ISACA. 2024. CMMI Model Quick Reference Guide: AnOverviewof the Capability Maturity Model Integration (CMMI)® Model. [link].

P. John Sterman. 2000. Business Dynamics: Systems Thinking and Modeling for a Complex World with CD-ROM. McGraw-Hill Education.

Daniel H Kim and Virginia Anderson. 1998. Systems archetype basics: From story to structure. Waltham: Pegasus Communications.

Donella H Meadows. 2008. Thinking in systems: A primer. chelsea green publishing.

William Schoenberg. 2020. LoopX: Visualizing and understanding the origins of dynamic model behavior. (2020). DOI: 10.48550/arXiv.1909.01138

J. Sterman. 2010. Business Dynamics: Systems Thinking And Modeling For The Complex World. Tata McGraw Hill Education Private Limited. DOI: 10.1057/palgrave.jors.2601336
Publicado
22/09/2025
APOLINÁRIO, Amanda Brito; LAHASS, Thiago Felippe Neitzke; BORGES, Júlia de Souza; SANTOS JÚNIOR, Paulo Sérgio dos; BARCELLOS, Monalessa P.. CaLMo: A Tool to support the use of Causal Loop Diagram in Software Engineering. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE (SBES), 39. , 2025, Recife/PE. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2025 . p. 969-975. ISSN 2833-0633. DOI: https://doi.org/10.5753/sbes.2025.11543.