Learn and practice the Bitwise Manipulation, Sliding Window, and Union Find patterns to solve coding interview problems.

Educative-99 in Python: Accelerate Your Coding Interview Prep

Each of the patterns in this module exemplifies the power of dissecting a problem in detail and figuring out the least expensive operations required to solve it. In the Bitwise Manipulation pattern, we’ll learn to leverage the power of bit-level operators to deliver more efficient solutions. With the Sliding Window pattern, we’ll gain practice in various techniques to ensure that a solution that seems to require nested loops actually executes in linear time. Using the Union Find pattern, we’ll learn to solve a diverse set of problems using the disjoint-set data structure.

Elegant by Design


# Statement
You’re given a network of $n$ nodes as an $n \times n$ adjacency matrix graph with the $i^{th}$ node directly connected to the $j^{th}$ node if `graph[i][j] == 1`.

A list of nodes, `initial`, is given, which contains nodes initially infected by malware. When two nodes are connected directly and at least one of them is infected by malware, both nodes will be infected by malware. This spread of malware will continue until every node in the connected component of nodes has been infected.

After the infection has stopped spreading, $M$ will represent the final number of nodes in the entire network that have been infected with malware.

Return a node from `initial` such that, when this node is removed from the graph, $M$ is minimized. If multiple nodes can be removed to minimize $M$, return the node with the smallest index.

> **Note:** If a node was removed from the initial list of infected nodes, it might still be infected later on due to the malware’s spread.

**Constraints:**
* `graph.length == graph[i].length`
* $2 \leq$ n $\leq 50$
* `graph[i][j]` is $0$ or $1$.
* `graph[i][j] == graph[j][i]`
* `graph[i][i] == 1`
* $1 \leq$ `initial.length` $\leq n$
* $0 \leq$ `initial[i]` $\leq n - 1$
* All the integers in the `initial` are unique.

# Examples

Try to solve the Minimize Malware Spread problem.