Utilizing the longest common substring involves identifying the longest sequence of words or characters shared between two documents. This helps highlight the areas where the documents are similar, aiding in document comparison.

Matrix Chain Multiplication is applied in real-life scenarios such as image processing for computer vision applications. It optimizes the order of matrix multiplications, reducing the overall computational cost and improving efficiency in tasks like convolution operations in image processing.

Yes, DFS can be used to detect cycles in both directed and undirected graphs. It does so by maintaining a visited set and checking for back edges during the traversal.

DFS is often implemented using tail recursion or an explicit stack data structure. Recursion provides a natural way to track the depth-first nature of the algorithm, while an explicit stack can be used to simulate the recursive call stack.

Linear search can be optimized for performance by employing techniques such as Transposition or Move to Front. These techniques involve rearranging the elements in the array based on their access patterns, ensuring that frequently accessed elements are positioned closer to the beginning. This optimization can improve the average-case performance of linear search.

Selection Sort is not feasible in this scenario due to its quadratic time complexity. Instead, External Sort, a class of algorithms designed for large datasets stored on external storage like disks, would be more appropriate. Merge Sort, adapted for external sorting, efficiently manages limited memory usage and minimizes disk I/O operations.

The primary objective of the Knapsack Problem is to maximize the total value of selected items while respecting the constraint of the knapsack's capacity. It involves choosing a subset of items with the highest combined value without exceeding the capacity of the knapsack.

The effectiveness of a string compression algorithm can be measured by analyzing the compression ratio (the reduction in size) and compression speed. Compression ratio indicates how well the algorithm reduces the size of the original string, while compression speed reflects the time it takes to compress the data.

In a memory-constrained scenario, Manacher's Algorithm remains the optimal choice due to its linear time complexity and minimal space requirements, making it well-suited for large text files.

In a robotics application involving complex motion planning using matrices, Matrix Chain Multiplication can enhance algorithm performance by optimizing the order of matrix operations. This optimization minimizes computational complexity and contributes to more efficient and effective motion planning.

Merge sort is inherently stable because it ensures that equal elements maintain their original order during the merging phase. This stability is particularly useful in scenarios where maintaining the relative order of equal elements is crucial, such as in sorting records with multiple attributes.

Dynamic programming techniques, such as memoization and lookup tables, are commonly employed to efficiently solve the Knapsack Problem. These techniques help avoid redundant computations and improve the overall efficiency of the solution.