11th Class Computer Chapter 2 | Exercise | Class 11th Computer New Book 2025

Added: 2026-05-11

[00:00:07]Assalam Walekum students. My name is Etesham Khan and I am your computer teacher.

[00:00:11]So son, today we are going to discuss the exercises of chapter number three. First of all we will see the MCQs and how the MCQs we have work.

[00:00:26]If I talk about MCQs first, then we have all the crackles of well defined problems, so our first answer to this is C.

[00:00:37]That is clear goal input process and output. It is a clear thing. It says that you have a good, round, good problem which is a well-defined problem. Obviously, all its conditions should be clearly specified, it should be without error, everything should be clear. After that, the complexity class recording problems solvable efficiently and deterministic problem, so which one do we have, it is a P problem, okay, the statement that applies to unsolvable problem, so we have B option, it cannot be solved by any algorithm.

[00:01:14]Son, you should have the book open and if you keep marking it, it will be easier for you.

[00:01:18]The meaning of NP in computational complexity is so the answer we have for the fourth is that it is an option non-deterministic polynomial time.

[00:01:30]After that, the fifth answer to the fifth question is we have more efficient searching algorithms for large data sets. So the answer for fifth is D quick short. Is it okay son?

[00:01:43]Because you don't have this quick sort. It is not even in the book. Because of this I cannot tell you its details. We have read the rest of the sources, you can see them by going to our topic. A scenario with dynamic programming provides more useful. So this is our option C.

[00:01:59]Problems with Overlapping Subproblems and Optimal Substructures.

[00:02:05]After that, we will get an algorithm that sorts data by stepping through the list and swiping adjacent elements if needed. If needed, we will have the option of seven, that is C option bubble sort. Yes, after that, we will get the option of eight. The time complexity of DFS graph is, so we will have the option of eighth. If you look in your book, you will find the order of vertices plus edges there. And further, we will have the answer to our 10th class MCQs. The answer to the question is eighth. Yes, we will get the ninth class. If we talk about the ninth class, then the ninth class is the best description of time complexity. So, which is the best description of time complexity? That is the B option, time taking and function input size is a function of input size. After that, the last option is the last question. We have the algorithm of MCQ which has the time complexity of order of n or log n. So, whose will this be? This will be the merged short of the 10 we have.

[00:03:12]Son, you have not read this either, hence you will not go into its details.

[00:03:17]What will you do with just this? We will go through it. Let's talk about question number two which is based on the short questions we have.

[00:03:23]So if I talk about the first question, what is the difference between well defined and ill defined? Look son, we have read this in great detail. What does well defined mean? So, the problem that you have is well defined and there should not be any kind of error in it. If the inputs are clear, the processes are clear, the goals are clear, then that is a well-defined problem and a problem in which some error or the other occurs and whose goals are not clear, is ill-defined. Is it okay son? After that, the second question we have is outline the main step involved in test and generate method. It is clear that you know about test and generate that you test. If the result is OK then it is fine. Otherwise, where would you have gone again? Used to go to generator.

[00:04:11]And you used to resolve it again.

[00:04:14]Till or till, doesn't your testing get done? It does not get corrected.

[00:04:19]You used to compare traceable and intractable problems. Well, you knew that traceable problems are solved in polynomial time and intractable problems are not solved in polynomial time. In that, the time taken is based according to that problem.

[00:04:39]ok sir. Then our Summarize the Idea Behind Greedy Algorithms. So that was the idea of ​​the Greedy Algorithm.

[00:04:47]If I talk about the fourth answer, if we have to reach here through one path, then what did he say? He used to say that we did not know that when you were coming here, how much output you had? For example, if the greedy algorithm says the distance from here is five. It's 10 from here. It's 20 from here.

[00:05:11]And the next one is 50 from here.

[00:05:14]From here it's 60 and this is five. So it is said that the greedy algorithm used to decide the shortest path. He does n't see the results in advance. He decides on the shortest path and starts walking. Is it okay son? After that we will get the advantages. What are the advantages of dynamic programming? Obviously, the first advantage of dynamic programming that we have is that it will avoid overlapping of all the problems and it will provide you optimal solutions for problems with optimal structures like Fabianchi series, Knapsack algorithms, all these are available to us in it. So if we tell you the difference between BFS and DFS, then let us talk about the six that you have.

[00:06:07]What did we have in the bread first search that you had? In BFS we used to look for the shortest path and follow it.

[00:06:13]This was BFS. This is how we used to walk. Ok? And in the DFS that we had, we used to go deep. Then he would come back.

[00:06:22]Then we would go into depth. That means, when we caught a node, we would go into its depth and come back from there. And the third seventh MCQs we have is that breaking problem down is lets you to solve test and ruse small problem. He says why do you break down any problem? So that's why you can do that problem again and again?

[00:06:43]Can be reused. And eighth we have a short question. That is a short question we had that was related to factors. So what factors come into play? So if we talk about that, we have the question Identify the factors used to evaluate the performance of algorithms. So if we look at it, factors like time complexity come into it.

[00:07:05]If I factors, what are the factors that are involved in this? So if I talk about consumption here, then we will have children and time complexity in it. Space complexity will come. These are all factors that contribute to finding out your complexity.

[00:07:24]ok sir. Good sir. Now let's talk about the long questions we have, son.

[00:07:30]Look child, we have long questions in this chapter because when I started teaching you this chapter, I had told you in the beginning of this chapter itself that all of it is long questions.

[00:07:41]So because we cannot go into the details of this long question.

[00:07:44]We are doing exercise while explaining here. So let's try.

[00:07:46]That in our exercise, we should be made to do those things which we have not studied before.

[00:07:51]So if I talk about this exercise, then in this we have long questions which we have already read earlier. There is also the first long question.

[00:08:00]Provides the explanation of halting problems is considered unsolvable and implications of computer science. I have read it.

[00:08:06]Discuss the nature of search problems and compare the efficiency of linear search algorithms. We have read this also.

[00:08:14]After that, if I talk, discuss the nature of optimization and provide examples of applications. Let me tell you what are the answers to these questions. Explain the process of time and space complexity in which you have taught bubble sort and this is a proper detailed topic that I have taught you. If you go and look at this topic, you will get an idea.

[00:08:30]Discuss the difference between time complexity and spell complexity.

[00:08:34]So I have also taught you this detailed topic with examples. Now if I tell you which long questions fit on these. So the first one is the halting problem. I had mentioned in this Halting Problem that there is no algorithm in it. Look, there are some problems which are really not possible to solve. So this was about halting problems that brother, some problems cannot be solved. So this was about halting algorithms or halting problems. The second is searching problems which include linear search and binary search. These other long questions, you can go and see the entire topic.

[00:09:08]The third is optimization problems where you have GPS, there are distra algorithms.

[00:09:14]We have these ones. Fourth you have the bubble sorts I taught in detail.

[00:09:18]You can go and see that. And I have also studied time and space complexity in detail.

[00:09:22]So you will have all these long questions, if you go to the previous videos, you will find four to five videos and there you will also get the answers to these long questions and if you write them in your board or paper as I have written in detail, then you will get full marks. Is it okay son? Thank you very much.

[00:09:42]Jazak Allah. Allah Hafiz.