SALSA: Swarm Algorithm Simulator

Swarm algorithms are being increasingly investigated as potential solutions for addressing distributed, complex problems across various domains. However, developing and testing these algorithms remains challenging due to the lack of robust and flexible testbeds. Moreover, efficiently tuning the parameters of swarm algorithms to suit specific situations is a significant challenge. This artifact paper presents SALSA, a comprehensive and extensible framework designed to streamline the development and evaluation of swarm algorithms - designed with ease of use in mind. Our testbed enables users to define custom swarm algorithms, drone types, targets to detect, and agent interaction processes. It also allows for dynamic parameter updates, providing instant feedback to optimize algorithm performance. Additionally, the testbed supports both user-defined and automated data collection, ensuring that users can gather relevant data efficiently. Overall, SALSA enhances research effectiveness by reducing the time and effort required to set up and test swarm algorithms.