During optical proximity correction (OPC), layout edges or fragments are migrated to proper positions in order to minimize edge placement error (EPE). During this fragment migration, several factors other than EPE are a part of the cost function for optimal fragment displacement. Several factors are devised in favor of OPC stability, which can accommodate room for high mask error enhancement factor (MEEF), lack of process window, catastrophic pattern failure such as pinch/bridge and improper fragmentation. As technology nodes becomes finer, there are conflicts between OPC accuracy and stability, especially for metal layers. To address this, several techniques have been introduced, including target smoothing, process window-aware OPC, model-based re-targeting, and adaptive OPC. Those techniques invoke additional edges, or fragments, prior to correction or during OPC iteration. As a result, the number of jogs – and shot count – are dramatically increased. There is trade-off relationship between data complexity and various methods for OPC stability. In this paper, those relationships have been investigated. Mask shot count reduction is achieved by reducing the number of jogs with jog smoothing. The effect of jog smoothing on OPC output – in view of OPC performance and mask data preparation - was studied quantitatively for respective technology nodes.