Analysis of Algorithms and Computational Complexity Questions and Answers
Understanding the Analysis of Algorithms and Computational Complexity questions with answers is crucial for students preparing for GATE, TCS, Infosys, and Wipro placement exams. This topic focuses on evaluating the efficiency of algorithms based on time and space complexity, which forms the foundation of advanced computer programming and system design. By solving programming questions and answers related to algorithm analysis, you can strengthen your logical thinking, optimize code performance, and make informed design decisions. In this section, we cover detailed MCQs and explanations to help you master Big O notation, asymptotic analysis, and algorithmic trade-offs. Perfect for both academic and placement preparation, this guide ensures clarity with well-explained examples.
Questions on algorithmic analysis for computer science aspirants can be complemented by data structure algorithms and software engineering MCQ
Analysis of Algorithms and Computational Complexity
131. What is the name of the computer programming language which is credited with 'no threshold and no ceiling' ?
- LOGO
- BASIC
- PASCAL
- ADA
132. The Computer language LOGO is based on another powerful list processing language for Robotics and Artificial Intelligence. Can you tell the name of that language ?
- GSP
- LISP
- PASCAL
- PROLOG
133. Which of the following is one of the widely used algol based simulation language ?
- FORTRAN
- GASPIV
- SIMSCRIPT
- GPSS
134. Which decision procedure has at least doubly-exponential time complexity ?
- LInear programming
- Travelling Salesmen Problem
- Presburger Arithmetic
- Hamiltonian Circuit Problem
135. Which sort will operate in quadratic time relative to the number of elements in the array (on the average) ?
- quick sort
- merge sort
- heap sort
- bubble sort
136. What is the weight of the minimal spanning tree for the graph in problem 234 ?
- 17
- 18
- 20
- 21
137. After constructing a "sorted" binary insertion tree, to produce a sorted array to numbers (for printing purposes), what must be done ?
- pre-order traversal
- inorder traversal
- post-order traversal
- top down traversal
138. Which of the following sorting algorithms yield approximately the same worst-case and average-case running time behaviour in O (n log n) ?
- Bubble sort and Selection sort
- Heap sort and Merge sort
- Quicksort and Radix sort
- Tree sort and Median-of-3 Quick sort
139. Super-Jarvis said "I can write a super merge sort which splits an array into 4 components (unlike regular merge sort which splits in two) and then recursively sort the 4 subarrays and thend merges them. Though similar to merge sort, it is faster and called SJ4." What is true ?
- SJ4 cannot possibly work, a four-way split and then later merge is 0 reposdterous
- SJ4 Works and SJ4 operates in O(Merge-Sort)
- SJ4 Works and SJ4 is greater than (slower than) O(Merge-Sort)
- SJ4 worksd and SJ4 is less than (faster than) O(Merge-sort)