The paper introduces and analyzes the splay tree, a self-adjusting form of binary search tree. Splay trees are designed to minimize the amortized time per operation, achieving an O(log n) bound for all standard search tree operations on an n-node tree. The key heuristic used in splay trees is splaying, which moves a specified node to the root of the tree by performing a sequence of rotations along the access path. This heuristic ensures that frequently accessed items are moved closer to the root, improving future access times. The authors prove that splay trees are as efficient as dynamically balanced trees and static optimum trees in terms of amortized complexity, and conjecture that they are even more efficient for sufficiently long access sequences. The paper covers several aspects of splay trees, including their implementation, variants, and practical efficiency. It discusses the benefits and drawbacks of splaying, such as its simplicity and adaptability to skewed access patterns, and compares it with other data structures like balanced trees and optimum search trees. The authors also explore techniques to reduce the amount of restructuring in splay trees, such as semisplaying and conditional splaying, and provide theoretical bounds on their performance. Overall, the paper provides a comprehensive analysis of splay trees, demonstrating their efficiency and potential for practical applications in data structures and algorithms.The paper introduces and analyzes the splay tree, a self-adjusting form of binary search tree. Splay trees are designed to minimize the amortized time per operation, achieving an O(log n) bound for all standard search tree operations on an n-node tree. The key heuristic used in splay trees is splaying, which moves a specified node to the root of the tree by performing a sequence of rotations along the access path. This heuristic ensures that frequently accessed items are moved closer to the root, improving future access times. The authors prove that splay trees are as efficient as dynamically balanced trees and static optimum trees in terms of amortized complexity, and conjecture that they are even more efficient for sufficiently long access sequences. The paper covers several aspects of splay trees, including their implementation, variants, and practical efficiency. It discusses the benefits and drawbacks of splaying, such as its simplicity and adaptability to skewed access patterns, and compares it with other data structures like balanced trees and optimum search trees. The authors also explore techniques to reduce the amount of restructuring in splay trees, such as semisplaying and conditional splaying, and provide theoretical bounds on their performance. Overall, the paper provides a comprehensive analysis of splay trees, demonstrating their efficiency and potential for practical applications in data structures and algorithms.