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
71. Pascal is a
- natural language
- mahine language
- assembly language
- high level language
72. A language developed to assist children in learning geometric shapes and computing aspects is
- COBOL
- BASIC
- LOGO
- LISP
73. The preliminary evaluation of top-down design before programs are written is referred to as a (an)
- informal design review
- structured walk through
- formal design review
- scheduled reviewe
74. Which of the following is not an example of program documentation ?
- source code
- object code
- specification
- identifier names
75. Which of the following is non-essential to stepwise to stepwise refinement ? I. refining the subprograms II. decomposing the problem into subproblems III. declaring all variables IV. stating the problem simply V. inputing the data
- II
- III and IV
- IV and V
- V
76. A top-down approach to programming calls for I. working from the general to the specific II. postponing the minor decisions III. a systematic approach IV. immediate coding of the problem
- I
- I and II
- I, II and III
- I, II and IV
77. Top-down programming facilitates I. implementing a complex problem in states II. readability III. maintenance of the program IV. testing of individual modules
- I and II
- I, II and III
- II, III and IV
- I, II, III and IV
78. Repet execution of simple computation may cause compounding of
- round-off errors
- syntax errors
- run-time errors
- logic errors
79. Through testing of a program ensures that it performs as expected. A program should be tested I. for each module in the program II. with sample data III. for every path through the program
- I and III
- I and II
- II and III
- I, II and III
80. Modular programming involves I. proceeding from the particular to general II. modules that solve individual tasks III. problems decomposed into logical subproblems
- I and II
- I and III
- II and IV
- I, II and III