Beneath the silver glow of a crescent moon, the traveler wandered through the silent fores, Cheat Sheet of Labour Law

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CS F211: DATA STRUCTURES & ALGORITHMS

ND

SEMESTER 2024-25)

BST, AND AVL TREES

Chittaranjan Hota, PhD Senior Professor, Computer Sc. BITS-Pilani Hyderabad Campus hota[AT]hyderabad.bits-pilani.ac.in

IMPLEMENTATION OF HASH MAP #include #include #include #include using namespace std; class HashMap { //Hash Table Class private: static const int TABLE_SIZE = 10; vector<list<pair<string, int>>> table; int hashFunction(const string &key) { hash hashFunc; return hashFunc(key) % TABLE_SIZE; } public: HashMap() { table.resize(TABLE_SIZE); } void insert (const string &key, int value) { int index = hashFunction(key); // Check if key already exists, update it for (auto &p : table[index]) { if (p.first == key) { p.second = value; return; } } // If key not found, insert new key-value table[index].emplace_back(key, value); } void remove (const string &key) { int index = hashFunction(key); auto &chain = table[index]; for(auto it=chain.begin(); it!=chain.end();++it){ if (it->first == key) { chain.erase(it); return; } } cout << key << " not found."; } int search (const string &key) { int index = hashFunction(key); for (auto &p : table[index]) { if (p.first == key) return p.second; } throw runtime_error("Key not found"); } void display () { for (int i = 0; i < TABLE_SIZE; i++) { cout << "Index " << i << ": "; for (auto &p : table[i]) cout << p.first << p.second; cout << endl; } } }; int main() { HashMap map; map.insert("Riddhi", 25); map.insert("Aryan", 30); map.insert("Mahadevan", 22); map.insert("Saket", 40); map.insert("Purva", 29); map.display(); map.remove("Purva"); map.display(); return 0 ; } Lab11 Next week

DNS LOOKUP USING HASH MAPS

• Each DNS server keeps track of its immediate

children servers using a hashmap.

Lab11 Next week

IMPL. OF LINEAR PROBING & PERFORMANCE

void insert (const string &key, int value) {

int index = hashFunction(key);

int originalIndex = index;

bool found = false;

while (table[index].isOccupied && !table[index].isDeleted) {

if (table[index].key == key){// Key exists, update value

table[index].value = value;

return;

index = (index + 1) % TABLE_SIZE;

if (index == originalIndex) { // Full table check

cout << "Hash table is full! Cannot insert.\n";

return;

// Insert new key-value pair

table[index].key = key;

table[index].value = value;

table[index].isOccupied = true;

table[index].isDeleted = false;

• In the worst case, searches, insertions

and removals on a hash table take?

time.

• The worst case occurs when all the

keys inserted into the map collide.

• The load factor a = n / N affects the

performance of a hash table. Default

load factor is 0. 75.

Rehashing

BINARY SEARCH TREE (BST) & ORDERED MAPS

If node with key 8 has a left child with key 3, what would be the type? To get an ascending order, what is needed?

Keys are: 20, 10, 6, 2, 8, 15, 40, 30 and 25

ORDER OF INSERTION IS IMPORTANT (a) if values are inserted in the order 37 , 24 , 42 , 7 , 2 , 40 , 42 , 32 , 120 , (b) If the order is 120 , 42 , 42 , 7 , 2 , 32 , 37 , 24 , 40 template typename SearchTree::TPos SearchTree::finder(const K& k, const TPos& v) { if (v.isExternal()) return v; // Key not found if (k < (v).key()) return finder(k, v.left()); else if ((v).key() < k) return finder(k, v.right()); else return v; } template typename SearchTree::Iterator SearchTree::find(const K& k) { TPos v = finder(k, root()); if (v.isInternal()) { return Iterator(v); // Found it } else return end(); // Didn't find it } Lab 12 : Next to next week’s lab…

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• What happens to the Balance Factors and how will you handle the imbalance?

AVL TREES

• Adelson-Velsky and Landis (Soviet mathematicians and computer scientists)
• BST with height-balance property.

BALANCING THE TREE THROUGH ROTATIONS

(LL Case)

/ \

\

\

(RR Case)

/ \

(Right rotate at 30)

(Left rotate at 10)

\

(LR Case)

/ \

\

(RL Case)

\

\

/ \

(LR 30) (RR 5 0) (RR 5 0) (LR 30)