Tytuł pozycji:
Optimization of the Cell-based Software Architecture by Applying the Community Detection Approach
The aim of this research is to present the Cell-based software architecture and explore its optimization. Cell-based software architecture organizes a software system into interconnected cells, each containing multiple elements. This research focuses on optimizing cell-based architecture, particularly the number of cells and their internal organization. In this context, the Community Detection approach, which identifies closely connected elements, was applied. Additionally, the model incorporates the concept of functionality, defined as a set of capabilities allowable and actionable by the software system. We conducted a series of experiments based on the defined mathematical model to validate our approach, achieving optimal and near-optimal solutions within a given time limit. Considering that each cell can contain multiple elements realized in various architectural styles, the proposed model allows for the integration of different architectures within the same software system. This flexibility enhances the system's overall adaptability and efficiency.
1. Input data and optimization results from a series of experiments can be accessed at the following address: https://github.com/mmilicfon/fedcsis2024.
2. Main Track: Regular Papers
3. Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
