Efficient Code Reachability Analysis and Visualization Using Probabilistic Model Checking

In software development, the rapid expansion of code often leads to increased complexity and higher maintenance costs, particularly when unused or redundant code accumulates over time. This study introduces a novel approach to analyzing and visualizing code reachability using probabilistic model checking, enabling efficient identification of components that may no longer be necessary. By leveraging probabilistic reachability analysis, our method evaluates the usage trends of packages, classes and methods throughout the system’s lifecycle. We implemented a prototype tool and conducted case studies on real-world projects to validate its effectiveness. The results demonstrate the tool’s potential to support strategic code management by identifying and visualizing frequently used, rarely used and unused code components, thereby facilitating system optimization and reducing maintenance overhead.