Coverage optimization is a fundamental problem in Directional Sensor Networks (DSNs). Apart from solutions for omnidirectional sensor nodes, more intelligent algorithms are required for this unique and non-trivial problem. In recent years, several centralized and decentralized methods were introduced to improve the coverage in randomly deployed DSNs. A thorough review reveals that the performance of random deployment is the most preferred way to measure the performance of a newly introduced algorithm. However, the relative performance gains of two separate algorithms do not necessarily reflect the mutual performance comparison of these algorithms. Therefore, to make this comparison more quantitative, we have designed a comprehensive simulation platform, called simDSN, for both occluded and non-occluded 2D-regions. The main goal of simDSN is to make the researchers to test their algorithms for different cases against other solutions under exactly the same conditions. Thus, researchers would save time due to not implementing their simulation environment, since they could exploit the ready-to-use components, such as, node, field, obstacle and etc., of simDSN. Also, the comprehensive infrastructure of simDSN allow developers to save/load/analyze each movement of directional sensor nodes during each iteration of the simulation process, which would help to debug their algorithms.