Plain tree data structure will not help much.Its a conceptual way how you can save data and retrieve it in less time. If plain tree is associated with certain constraints ,it will be quite useful.
Examples:
- Binary Search Tree – Used in many search applications where data is constantly entering/leaving, such as the map and set objects in many languages’ libraries.
- Binary Space Partition – Used in almost every 3D video game to determine what objects need to be rendered.
- Binary Tries – Used in almost every high-bandwidth router for storing router-tables.
- Hash Trees – used in p2p programs and specialized image-signatures in which a hash needs to be verified, but the whole file is not available.
- Heaps – Used in implementing efficient priority-queues, which in turn are used for scheduling processes in many operating systems, Quality-of-Service in routers, and A*
(path-finding algorithm used in AI applications, including robotics and video games)Also used in heap-sort. - Huffman Coding Tree (Chip Uni) – used in compression algorithms, such as those used by the .jpeg and .mp3 file-formats.
- GGM Trees – Used in cryptographic applications to generate a tree of pseudo-random numbers.
- Syntax Tree – Constructed by compilers and (implicitly) calculators to parse expressions.
- Treap– Randomized data structure used in wireless networking and memory allocation.
- T-tree – Though most databases use some form of B-tree to store data on the drive, databases which keep all (most) their data in memory often use T-trees to do so.
- BTree : we use BTree in indexing large records in database to improve search.
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