A Simple and Efficient Union-Find-Delete Algorithm - Corelab

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Full or Reduced Trees We maintain certain invariants to achieve the desired efficiency. Every tree will be either • Full – each node is either a leaf of rank 0, or a parent with at least three children 7 0 1 9 Rank 0 5 2 3 8 4 6 Rank 0 Rank 0
or • Reduced – a single node of rank 0, • or a root of rank 1 with leaves of rank 0 Rank 1 0 Rank 0 or 7 0 3 1 5 9 Rank 0 Rank 0 Rank 0
Page 1 and 2: A Simple and Efficient Union-Find-D
Page 3 and 4: Union Find Delete data structure Ma
Page 5 and 6: The classic data structure Represen
Page 7 and 8: Find climbs from the provided eleme
Page 9 and 10: To increase the amortized efficienc
Page 11 and 12: Purpose of this talk: Describe a si
Page 13 and 14: Delete operation Deleting a leaf no
Page 15 and 16: Possible Solution Find a leaf, swit
Page 17 and 18: Possible Solution Find a leaf, swit
Page 19 and 20: Previous Work • H. Kaplan, N. Sha
Page 21 and 22: • The solution instead of finding
Page 23 and 24: • The solution instead of finding
Page 25 and 26: Tree Nodes in DFS Order The predece
Page 27: • The predecessor is a parent or
Page 31 and 32: Implementing Union One of the trees
Page 33 and 34: Both trees are of size ≥ 4 : Unio
Page 35 and 36: Implementing Find • Instead of pa
Page 37 and 38: Fixing The DFS Order • If node x
Page 39 and 40: Fixing The DFS Order • If node x
Page 41 and 42: • If node x is the leftmost child
Page 43 and 44: Implementing Delete Tree is of size
Page 45 and 46: Local Rebuild If node y is not the
Page 47 and 48: Local Rebuild If node y is not the
Page 49 and 50: If node y is the root and node c is
Page 51 and 52: Analysis Our asymptotic worst case
Page 53: E Thank You

A Simple and Efficient Union-Find-Delete Algorithm - Corelab

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