Trie / Ternary Search Tree (TST) / Radix Tree

Description of this project

I have created three data structures that are implementations of the abstract data type dictionary. But they are enhanced with an extra method called "keys", this returns the keys with that share a provided prefix. This can be useful to use it in tasks such as autocomplete searches.

The aim of this study is to compare the performance of these three data structures in different scenarios and against the std::map and std::unordered_map. Moreover, the second aim of this project is to practice new things added in the standard C++11 and the Google Test as a unit test framework.

Operations supported by the three data structures tested in this project.

Operation	Description
clear	Removes all the content of the data structure
find	Returns the value stored in the data structure for a specific key provided
insert	Adds a new pair of key and value to the data structure
size	Returns the amount of elements stored in the data structure
show	Prints the content of the data structure in the dot format
erase	Removes the value stored in the data structure for a specific key provided
contains	Returns true if there is a value associated to the key provided
keys	Returns a std::vector with all the keys in the data structure that have the provided prefix. If no prefix is provided returns a std::vector with all the keys in the data structure.
lcp	Returns the longest common prefix of all keys stored in the data structure.

Scenarios tested

I have develop several test scenarios (and I am still developing new ones) to compare the performance of these five data structures.

• Memory
  • Random values
  • Dictionaries
• Insert
  • Random values
• Remove
  • Random values
    • Found
    • Not found
  • Dictionaries
    • Found
    • Not found
• Seach
  • Random values
    • Found
    • Not found
  • Dictionaries
    • Found
    • Not found
• Get Keys
  • Random values
  • Dictionaries
• Get Keys with Prefix
  • Random values
  • Dictionaries
• Longest Common Path
  • Random values
  • Dictionaries