officerpath@gmail.com Hyderabad, Pakistan
Login Register
Latest Jobs CSS 2025 PMS CCE Sindh FPSC PPSC MCQs Past Papers Current Affairs Scholarships Admissions Downloads Roll No. Slips Results
OfficerPath MCQs

MCQ Practice Library

Search subjects, practice latest MCQs, and open topic-wise question banks.

Subjects

Choose a subject to browse its topics and MCQs.

Accounting

Topic-wise MCQ practice for competitive exams.

1,426 MCQs1 Topics
Open Subject

Agriculture

Topic-wise MCQ practice for competitive exams.

4,931 MCQs13 Topics
Open Subject

Auditing

Topic-wise MCQ practice for competitive exams.

0 MCQs1 Topics
Open Subject

Automobile Engineering

Topic-wise MCQ practice for competitive exams.

1,378 MCQs16 Topics
Open Subject

Biology

Topic-wise MCQ practice for competitive exams.

0 MCQs14 Topics
Open Subject

Biotechnology Engineering

Topic-wise MCQ practice for competitive exams.

1,253 MCQs24 Topics
Open Subject

Chemical Engineering

Topic-wise MCQ practice for competitive exams.

5,803 MCQs21 Topics
Open Subject

Chemistry

Topic-wise MCQ practice for competitive exams.

3,062 MCQs15 Topics
Open Subject

Civil Engineering

Topic-wise MCQ practice for competitive exams.

3,051 MCQs27 Topics
Open Subject

Commerce

Topic-wise MCQ practice for competitive exams.

3,279 MCQs59 Topics
Open Subject

Computer

Computer basics, IT and software concepts.

3,061 MCQs283 Topics
Open Subject

Computer Science Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs22 Topics
Open Subject

Current Affairs

Daily and exam-focused objective questions.

0 MCQs0 Topics
Open Subject

Electrical Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs61 Topics
Open Subject

Electronics and Communication

Topic-wise MCQ practice for competitive exams.

0 MCQs21 Topics
Open Subject

Engineering Chemistry

Topic-wise MCQ practice for competitive exams.

0 MCQs8 Topics
Open Subject

Engineering Maths

Topic-wise MCQ practice for competitive exams.

0 MCQs7 Topics
Open Subject

Engineering Physics

Topic-wise MCQ practice for competitive exams.

0 MCQs9 Topics
Open Subject

English

Grammar, vocabulary, comprehension and usage practice.

9,786 MCQs27 Topics
Open Subject

Everyday Science

Science fundamentals for exam preparation.

0 MCQs1 Topics
Open Subject

Finance

Topic-wise MCQ practice for competitive exams.

0 MCQs1 Topics
Open Subject

General Knowledge

General awareness for competitive screening tests.

0 MCQs0 Topics
Open Subject

General Knowledge (GK)

Topic-wise MCQ practice for competitive exams.

0 MCQs59 Topics
Open Subject

Geological Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs15 Topics
Open Subject

Home Science

Topic-wise MCQ practice for competitive exams.

0 MCQs9 Topics
Open Subject

Investigation

Topic-wise MCQ practice for competitive exams.

0 MCQs0 Topics
Open Subject

Islamic Studies

Islamiyat objective questions and basic concepts.

0 MCQs1 Topics
Open Subject

Law

Topic-wise MCQ practice for competitive exams.

0 MCQs28 Topics
Open Subject

Management

Topic-wise MCQ practice for competitive exams.

0 MCQs17 Topics
Open Subject

Marketing

Topic-wise MCQ practice for competitive exams.

0 MCQs1 Topics
Open Subject

Mass Communication and Journalism

Topic-wise MCQ practice for competitive exams.

0 MCQs12 Topics
Open Subject

Mathematics

Core quantitative MCQs and problem-solving practice.

3,275 MCQs56 Topics
Open Subject

Mechanical Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs18 Topics
Open Subject

Medical

Topic-wise MCQ practice for competitive exams.

0 MCQs94 Topics
Open Subject

Metallurgical Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs19 Topics
Open Subject

Mining Engineering

Topic-wise MCQ practice for competitive exams.

0 MCQs21 Topics
Open Subject

Pakistan Affairs

History, polity, geography and national affairs.

2 MCQs2 Topics
Open Subject

Pakistan Studies

Topic-wise MCQ practice for competitive exams.

0 MCQs9 Topics
Open Subject

Pedagogy

Topic-wise MCQ practice for competitive exams.

0 MCQs1 Topics
Open Subject

Pharmacy

Topic-wise MCQ practice for competitive exams.

0 MCQs10 Topics
Open Subject

Philosophy

Topic-wise MCQ practice for competitive exams.

0 MCQs20 Topics
Open Subject

Physics

Topic-wise MCQ practice for competitive exams.

0 MCQs12 Topics
Open Subject

Political Science

Topic-wise MCQ practice for competitive exams.

0 MCQs16 Topics
Open Subject

Psychology

Topic-wise MCQ practice for competitive exams.

0 MCQs18 Topics
Open Subject

Reasoning

Topic-wise MCQ practice for competitive exams.

0 MCQs57 Topics
Open Subject

Screening Test

Topic-wise MCQ practice for competitive exams.

0 MCQs0 Topics
Open Subject

Sociology

Topic-wise MCQ practice for competitive exams.

0 MCQs22 Topics
Open Subject

Urdu

Topic-wise MCQ practice for competitive exams.

0 MCQs1 Topics
Open Subject

Latest MCQs

Search, sort, and practice recently published MCQs.

What is the space complexity of the following dynamic programming implementation of the balanced partition problem? #include int balanced_partition(int *arr, int len) { int sm = 0, i, j; for(i = 0;i < len; i++) sm += arr[i]; if(sm % 2 != 0) return 0; int ans[sm/2 + 1][len + 1]; for(i = 0; i <= len; i++) ans[0][i] = 1; for(i = 1; i <= sm/2; i++) ans[i][0] = 0; for(i = 1; i <= sm/2; i++) { for(j = 1;j = arr[j - 1]) ans[i][j] = ans[i][j] || ans[i - arr[j - 1]][j - 1]; } } return ans[sm/2][len]; } int main() { int arr[] = {3, 4, 5, 6, 7, 1}, len = 6; int ans = balanced_partition(arr,len); if(ans == 0) printf("false"); else printf("true"); return 0; }

  1. A. O(sum)
  2. B. O(n)
  3. C. O(sum * n)
  4. D. O(sum + n)
Report Error

The following sequence is a fibonacci sequence: 0, 1, 1, 2, 3, 5, 8, 13, 21, .... Which technique can be used to get the nth fibonacci term?

  1. A. Recursion
  2. B. Dynamic programming
  3. C. A single for loop
  4. D. Recursion, Dynamic Programming, For loops
Report Error

What is the output of the following program? #include int max_num(int a,int b) { if(a> b) return a; return b; } int maximum_subarray_sum(int *arr, int len) { int sum[len], idx; sum[0] = arr[0]; for(idx = 1; idx < len; idx++) sum[idx] = max_num(sum[idx - 1] + arr[idx], arr[idx]); int mx = sum[0]; for(idx = 0; idx mx) mx =sum[idx]; return mx; } int main() { int arr[] = {-20, 23, 10, 3, -10, 11, -5},len = 7; int ans = maximum_subarray_sum(arr, len); printf("%d",ans); return 0; }

  1. A. 27
  2. B. 37
  3. C. 36
  4. D. 26
Report Error

Consider the following code to find the nth fibonacci term using dynamic programming: 1. int fibo(int n) 2. int fibo_terms[100000] //arr to store the fibonacci numbers 3. fibo_terms[0] = 0 4. fibo_terms[1] = 1 5. 6. for i: 2 to n 7. fibo_terms[i] = fibo_terms[i - 1] + fibo_terms[i - 2] 8. 9. return fibo_terms[n] Which technique is used by line 7 of the above code?

  1. A. Greedy
  2. B. Recursion
  3. C. Memoization
  4. D. Overlapping subproblems
Report Error

If a problem can be solved by combining optimal solutions to non-overlapping problems, the strategy is called . . . . . . . .

  1. A. Dynamic programming
  2. B. Greedy
  3. C. Divide and conquer
  4. D. Recursion
Report Error

Consider the two matrices P and Q which are 10 x 20 and 20 x 30 matrices respectively. What is the number of multiplications required to multiply the two matrices?

  1. A. 10*20
  2. B. 20*30
  3. C. 10*30
  4. D. 10*20*30
Report Error

Complete the following dynamic programming implementation of the longest increasing subsequence problem: #include int longest_inc_sub(int *arr, int len) { int i, j, tmp_max; int LIS[len]; // array to store the lengths of the longest increasing subsequence LIS[0]=1; for(i = 1; i < len; i++) { tmp_max = 0; for(j = 0; j < i; j++) { if(arr[j] tmp_max) ___________; } } LIS[i] = tmp_max + 1; } int max = LIS[0]; for(i = 0; i max) max = LIS[i]; return max; } int main() { int arr[] = {10,22,9,33,21,50,41,60,80}, len = 9; int ans = longest_inc_sub(arr, len); printf("%d",ans); return 0; }

  1. A. tmp_max = LIS[j]
  2. B. LIS[i] = LIS[j]
  3. C. LIS[j] = tmp_max
  4. D. tmp_max = LIS[i]
Report Error

What is the output of the following naive method used to find the maximum sub-array sum? #include int main() { int arr[1000] = {-2, -5, 6, -2, 3, -1, 0,-5, 6}, len = 9; int cur_max, tmp_max, strt_idx, sub_arr_idx; cur_max = arr[0]; for(strt_idx = 0; strt_idx < len; strt_idx++) { tmp_max = 0; for(sub_arr_idx = strt_idx; sub_arr_idx cur_max) cur_max = tmp_max; } } printf("%d",cur_max); return 0; }

  1. A. 6
  2. B. 9
  3. C. 7
  4. D. 4
Report Error

What is the output of the following code? #include #include int count_bool_parenthesization(char *sym, char *op) { int str_len = strlen(sym); int True[str_len][str_len],False[str_len][str_len]; int row,col,length,l; for(row = 0, col = 0; row < str_len; row++,col++) { if(sym[row] == 'T') { True[row][col] = 1; False[row][col] = 0; } else { True[row][col] = 0; False[row][col] = 1; } } for(length = 1; length < str_len; length++) { for(row = 0, col = length; col < str_len; col++, row++) { True[row][col] = 0; False[row][col] = 0; for(l = 0; l < length; l++) { int pos = row + l; int t_row_pos = True[row][pos] + False[row][pos]; int t_pos_col = True[pos+1][col] + False[pos+1][col]; if(op[pos] == '|') { False[row][col] += False[row][pos] * False[pos+1][col]; True[row][col] += t_row_pos * t_pos_col - False[row][pos] * False[pos+1][col]; } if(op[pos] == '&') { True[row][col] += True[row][pos] * True[pos+1][col]; False[row][col] += t_row_pos * t_pos_col - True[row][pos] * True[pos+1][col]; } if(op[pos] == '^') { True[row][col] += True[row][pos] * False[pos+1][col] + False[row][pos] * True[pos + 1][col]; False[row][col] += True[row][pos] * True[pos+1][col] + False[row][pos] * False[pos+1][col]; } } } } return True[0][str_len-1]; } int main() { char sym[] = "TTTT"; char op[] = "|^^"; int ans = count_bool_parenthesization(sym,op); printf("%d",ans); return 0; }

  1. A. 1
  2. B. 2
  3. C. 3
  4. D. 4
Report Error

What is the value stored in max_val[5] after the following program is executed? #include #include int rod_cut(int *prices, int len) { int max_val[len + 1]; int i,j,tmp_price,tmp_idx; max_val[0] = 0; for(i = 1; i <= len; i++) { int tmp_max = INT_MIN; // minimum value an integer can hold for(j = 1; j tmp_max) tmp_max = tmp_price; } max_val[i] = tmp_max; } return max_val[len]; } int main() { int prices[]={2, 5, 6, 9, 9, 17, 17, 18, 20, 22},len_of_rod = 5; int ans = rod_cut(prices, len_of_rod); printf("%d",ans); return 0; }

  1. A. 12
  2. B. 27
  3. C. 10
  4. D. 17
Report Error

What is the space complexity of the following dynamic programming implementation of the edit distance problem where "m" and "n" are the lengths of the two strings? #include #include int get_min(int a, int b) { if(a < b) return a; return b; } int edit_distance(char *s1, char *s2) { int len1,len2,i,j,min; len1 = strlen(s1); len2 = strlen(s2); int arr[len1 + 1][len2 + 1]; for(i = 0;i <= len1; i++) arr[i][0] = i; for(i = 0; i <= len2; i++) arr[0][i] = i; for(i = 1; i <= len1; i++) { for(j = 1; j <= len2; j++) { min = get_min(arr[i-1][j],arr[i][j-1]) + 1; if(s1[i - 1] == s2[j - 1]) { if(arr[i-1][j-1] < min) min = arr[i-1][j-1]; } else { if(arr[i-1][j-1] + 1 < min) min = arr[i-1][j-1] + 1; } arr[i][j] = min; } } return arr[len1][len2]; } int main() { char s1[] = "abcd", s2[] = "defg"; int ans = edit_distance(s1, s2); printf("%d",ans); return 0; }

  1. A. O(1)
  2. B. O(m + n)
  3. C. O(mn)
  4. D. O(n)
Report Error

Given a one-dimensional array of integers, you have to find a sub-array with maximum sum. This is the maximum sub-array sum problem. Which of these methods can be used to solve the problem?

  1. A. Dynamic programming
  2. B. Two for loops (naive method)
  3. C. Divide and conquer
  4. D. Dynamic programming, naive method and Divide and conquer methods
Report Error