Data structures efficiency
Telerik Academy Alpha
DSA
Table of contents
Comparing Data Structures
Big-O
Comparison of operations
Array sorting comparison
More information
Choosing a data structure
Choosing the right data structure
-
Arrays (T[])
- Use when fixed number of elements should be processed by index
-
Resizable array lists (List<T>)
- Use when elements should be added and processed by index
-
Linked lists (LinkedList<T>)
- Use when elements should be added at the both sides of the list
- Otherwise use resizable array list (List<T>)
Choosing the right data structure
-
Stacks (Stack<T>)
- Use to implement LIFO (last-in-first-out) behavior
- List<T> could also work well
-
Queues (Queue<T>)
- Use to implement FIFO (first-in-first-out) behavior
- LinkedList<T> could also work well
-
Hash table based dictionary (Dictionary<K,T>)
- Use when key-value pairs should be added fast and searched fast by key
- Elements in a hash table have no particular order
Choosing the right data structure
-
Balanced search tree based dictionary (SortedDictionary<K,T>)
- Use when key-value pairs should be added fast, searched fast by key and enumerated sorted by key
-
Hash table based set (HashSet<T>)
- Use to keep a group of unique values, to add and check belonging to the set fast
- Elements are in no particular order
-
Search tree based set (SortedSet<T>)
- Use to keep a group of ordered unique values
Summary
Summary
- Algorithm complexity is rough estimation of the number of steps performed by given computation
- Complexity can be
- \( logarithmic \)
- \( linear \)
- \( n* log n \)
- \( square \)
- \( cubic \)
- \( exponential \)
- \( etc. \)
- Complexity can be
Summary
- Allows to estimating the speed of given code before its execution
- Different data structures have different efficiency on different operations
- The fastest add / find / delete structure is the hash table - O(1) for all these operations