Question Bank

Let’s consider a manufacturing assembly line where various workers perform different tasks to assemble a product:

(1) Component suppliers who supply the necessary components for the assembly process,
(2) Assemblers that receive the components and assemble them into the final product,
(3) Inspectors, who check the quality of the finished products to ensure they meet the required standards,
(4) Packagers, who receive the inspected products and package them for shipping or distribution,
(5) Shippers that receive the packaged products and prepare them for transportation to customers or retailers.

By relating this model to processes in UNIX, what form of interprocess communication best describes this interaction?

Consider the following C code; how many child processes are created upon executing this program?

void main() { 
    fork(); 
    fork();  
    exit(); 
    fork(); 
}

The application below reads from a file containing only one string, namely "graduate". What will be the message printed on the screen if the read is successful:

#define SIZE 5 
    while((n = read(fd, buffer, SIZE)) > 0) { 
    printf("%s\n",buffer); 
}

The following code snippet should use pipes in order to communicate between the child and the parent process. Is there something wrong with the pipe mechanism from the code snippet below?

int pipe_fd[2]; 
char buffer[512]; 
pid_t pid=fork(); 
if(pid<0){ 
    perror("error"); 
    exit(1); 
} 
if(pid==0){ 
    write(pipe_fd[1],buffer,sizeof(buffer)); 
} 
else{ 
    close(pipe_fd[0]); 
    read(pipe_fd[0],buffer,sizeof(buffer)); 
    close(pipe_fd[1]); 
    printf("%s\n",buffer); 
    wait(NULL); 
}

How does the exec() family of functions differ from fork() ?

Let $f(n)$ = $n^2$, $g(n) = n$ log $n$, $h(n) = sin(n)$. Which of the following statements is true? There may be more than one correct answer.

A recursive program satisfies equation $T(n) = 9T(n/3) + Θ(n^2)$. What can we say about $T(n)$? There may be several correct answers.

In which of the following data structures does searching an item has worst-case complexity $Θ($log $n)$? There may be more than one.

Which of the following algorithms correctly computes the length of a longest increasing subsequence (LIS), problem and has complexity $O(n^2)$ ? There may be more than one right answer.

A recursive algorithm reduces solving the problem on inputs of size n to solving four subproblems on size $n/2$ and then combining the results. The combining step takes $f(n)$ steps. We want our algorithm to have complexity $O(n^2)$. Which of the following are acceptable complexities for the combining step? There may be several right answers.