What is the role of C++ data structures in performance optimization?

Data structures in C are critical to performance optimization. You should consider when choosing a data structure: Access patterns Frequency of insertion and deletion operations Expected data set size Memory limitations Arrays excel at fast addressing and efficient insertion and deletion, but can suffer in performance if elements need to be inserted or deleted at intermediate locations decline. Linked lists are great at insertion and deletion, but are slower in addressing. Hash tables provide fast lookups and insertions with O(1) time complexity, but hash collisions may occur.

The role of data structures in performance optimization

In C, when choosing the right algorithm, the choice of data structure Crucial as it can have a significant impact on the overall performance of your program.

Array vs. linked list

• Array stores elements continuously in memory. The advantage is fast addressing and high insertion and deletion efficiency. . The disadvantage is that when elements are inserted or deleted, adjacent elements may move, causing performance degradation.
• The elements in the linked list are stored in the node in the form of pointers. The disadvantage is that the addressing speed is slow, but the insertion and deletion are efficient because there is no need to move adjacent elements.

Practical case:

Suppose we have an array containing 100,000 integers and need to find a specific value in it.

Use array:

int target = 50000;
for (int i = 0; i < 100000; i++) {
  if (array[i] == target) {
    return i;
  }
}

Use linked list:

ListNode* targetNode = ListNode(50000);
ListNode* currNode = head;
while (currNode != nullptr) {
  if (currNode->val == target) {
    return currNode;
  }
  currNode = currNode->next;
}

Since the elements in the array are stored continuously, use The time complexity of searching for the target element in the array is O(n), that is, all elements in the array need to be traversed.

For a linked list, it needs to traverse each node in the linked list, and the time complexity is O(n), which is more complex than using an array.

Hash table

• Hash table is a collection that uses a hash function to map keys to corresponding values. It provides quick find and insert functionality. The disadvantage is that hash collisions can occur, i.e. different keys hash to the same location.

Practical case:

Suppose we have a dictionary containing the key as user name. Need to find the value corresponding to the given username.

unordered_map<string, int> userDict;
string username = "JohnDoe";
int value = userDict[username];

When using a hash table, the time complexity of the lookup operation is O(1), which is much faster than a linear search that traverses all keys to find the target key.

Guidelines for selecting data structures

When selecting a data structure, the following factors should be considered:

• Access mode (random vs. sequential)
• Frequency of insertion and deletion operations
• Expected data set size
• Memory limit

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