String compression would be useful in a real-world scenario such as storing DNA sequences in a database. Since DNA sequences often contain repeated patterns, using compression can significantly reduce storage requirements and improve search performance.

The main disadvantage of the bubble sort algorithm is its inefficiency for large lists, as it has a worst-case time complexity of O(n^2), making it impractical for sorting large datasets.

Bubble sort compares adjacent elements in the array and swaps them if they are in the wrong order. This process continues until the entire array is sorted. The algorithm gets its name from the way smaller elements "bubble" to the top of the array during each iteration. This sorting method is simple to implement but is inefficient for large datasets, as it has a time complexity of O(n^2) in the worst case, where n is the number of elements in the array.

Radix sort sorts data by grouping digits or components of the keys. It examines individual digits or components and places the elements into buckets based on these components.

The correct option is "Greedy." While the greedy approach works for some cases, it may not always yield the optimal solution for the coin change problem. Greedy algorithms make locally optimal choices at each stage, which may not lead to the overall optimal solution.

Dynamic programming in the context of solving the Longest Common Subsequence (LCS) problem avoids repetitive computations through the memorization of previously solved subproblems. This optimization technique helps in efficiently finding the LCS by storing and reusing intermediate results.

The space complexity of Prim's algorithm is generally lesser compared to Kruskal's algorithm due to its greedy approach. Prim's algorithm maintains a priority queue of vertices, requiring space proportional to the number of vertices, while Kruskal's algorithm needs space for storing the entire set of edges.

DFS can be used to detect cycles in a graph. By keeping track of visited nodes during the traversal, the algorithm can identify back edges, indicating the presence of cycles.

In C programming, memory allocation for arrays is typically handled using malloc(), and deallocation is done using free(). This allows dynamic memory management, enabling arrays to adapt to changing requirements during runtime.

The main difference is in the order of exploration. DFS explores as far as possible along each branch before backtracking, while BFS explores all neighbor nodes before moving deeper, resulting in a level-by-level approach.