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Wireless Sensor Networks (WSNs) play a vital role in applications such as environmental monitoring, smart cities, healthcare, and military surveillance, where reliable sensing coverage is essential. However, due to random deployment, node failures, energy depletion, and environmental constraints, coverage holes in regions that remain unmonitored often arise, significantly degrading network performance. This survey paper provides a comprehensive review of coverage hole detection, localization, and healing techniques in WSNs.It categorizes existing approaches into geometric methods (e.g., Voronoi diagrams and Delaunay triangulation), grid-based techniques, and optimization-based methods, including metaheuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithms (GA), and Ant Colony Optimization (ACO). A comparative analysis of various techniques is presented based on performance parameters, including coverage efficiency, computational complexity, energy consumption, and scalability. The paper also highlights current challenges and emerging research directions in coverage optimization