Computer Programming

The Tower of Hanoi is a classic recursive problem in computer science. It involves moving a set of disks from one rod to another, following specific rules: only one disk can be moved at a time, and a larger disk cannot be placed on top of a smaller disk. This problem is widely used to […]

Dynamic memory allocation in C provides flexibility by allowing programs to request memory at runtime. Sometimes, the initially allocated memory may not be enough, or you may need to reduce the size of a memory block. The realloc() function allows you to resize previously allocated memory without losing the existing data. Using realloc() is essential

In C programming, memory can be allocated in two ways: statically and dynamically. Static memory allocation reserves memory at compile time, while dynamic memory allocation allows the program to request memory at runtime. Dynamic allocation is especially useful when the size of the data is not known in advance. The malloc() function is part of

In C programming, dynamic memory allocation is essential when the size of data is not known at compile time. While malloc() allocates memory without initializing it, calloc() provides a convenient way to allocate memory and initialize all bytes to zero simultaneously. Using calloc() helps avoid undefined behavior caused by uninitialized memory, especially when working with

The Bellman-Ford Algorithm is a graph-based algorithm that computes the shortest path from a single source vertex to all other vertices in a weighted graph. Unlike Dijkstra’s Algorithm, it can handle negative edge weights, making it suitable for scenarios where some connections have penalties or costs. Bellman-Ford is widely used in network routing, transportation planning,

The Floyd-Warshall Algorithm is a dynamic programming-based graph algorithm used to find the shortest paths between all pairs of vertices in a weighted graph. It can handle negative edge weights but not negative cycles. This algorithm is widely used in networking, route optimization, and transitive closure problems due to its simplicity and efficiency for dense

Graph traversal is a fundamental operation in computer science, used in networking, AI, and pathfinding. Breadth-First Search (BFS) explores neighbors level by level, making it ideal for finding the shortest path in unweighted graphs. Depth-First Search (DFS) explores as far as possible along each branch before backtracking, which is useful for connectivity, topological sorting, and

Dijkstra’s Algorithm is a graph-based algorithm used to find the shortest path from a source node to all other vertices in a weighted graph with non-negative edge weights. It is widely used in networking, route optimization, and mapping applications. Understanding Dijkstra’s Algorithm helps in solving real-world problems involving optimal paths efficiently. Think of a map

Deleting a node from a BST is one of the most important operations because it affects the tree’s structure and the ordering property. Proper handling ensures that the BST property — all left descendants are smaller and all right descendants are larger — is maintained. This operation requires careful management of pointers and consideration of

Reverse level order traversal is a variation of the traditional level order traversal. In this method, we visit nodes level by level, but instead of printing from top to bottom, we print from bottom to top. This makes the traversal useful for problems where deeper levels should be processed before higher ones, such as evaluating