Algorithm Dynamics

Algorithm dynamics refer to how algorithms operate and adapt over time as they process data and solve problems. It involves understanding the sequence of steps, decision points, and how information flows within the algorithm. Think of it like a roadmap that guides a process: the dynamics reveal how the algorithm moves from start to finish, responds to new data, and improves its performance. Analyzing these dynamics helps optimize efficiency, predict behavior, and ensure the algorithm functions correctly across different scenarios. Essentially, it’s the study of how algorithms behave and evolve during their execution.