|[+] Dynamic graphs: Ω(lg n)|
This lecture covers our second of two lower bounds. This one is work by Mihai Pătraşcu (former 6.851 TA) and myself. We'll show that maintaining a graph subject to edge insertion, edge deletion, and connectivity queries (are v & w connected by a path?) requires Ω(lg n) time per operation, even if the graph is just a bunch of paths. This in particular proves optimality of the logarithmic dynamic tree data structures, and shows that the O(lg2 n) data structure we saw for general graphs is pretty good. The lower bound introduces a new but very simple technique, which at the time was the first “truly logarithmic” lower bound for a natural problem, yet the whole proof is relatively clean.
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