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1000+ Problem Solving MCQ Questions and Answers - 1

• engineering-questions

Question: 1

The maximum length of the data variable can hold is called

(A) header file

(B) length of a variable

(C) field width of a variable

(D) width of a variable

field width of a variable

Question: 2

The program created with the help of an editor is called

(A) source program or source code

(B) linking

(C) source program

(D) object program

source program or source code

Question: 3

Which of the following is easier to be transformed into a computer program?

(A) algorithm

(B) flow chart

(C) pseudo code

(D) none of these

pseudo code

Question: 4

The function printf() is used to print any combination of

(A) character

(C) string, number and character

string, number and character

Question: 5

The use of structure tags allow the structure to be

(A) separate from the constant declaration

(B) separate from the constant declaration

(C) separate from the variable declaration

(D) with the variable declaration

separate from the variable declaration

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Fundamentals of algorithms and problem-solving mcqs.

Home » Computer Science MCQs Sets » Computer Basics MCQs » Fundamentals of Algorithms and problem-solving MCQs

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1. Which graph algorithm can be used to find the longest path in a directed acyclic graph (DAG)?

• Depth-first search (DFS)
• Breadth-first search (BFS)
• Topological sort
• Dijkstra's algorithm

Topological sort can be used to find the longest path in a directed acyclic graph (DAG).

2. What does "brute force" mean in the context of problem-solving?

• Using the most complex approach to solve a problem
• Trying all possible solutions without optimization
• Solving problems without a plan
• Applying advanced mathematics to solve a problem

"Brute force" in problem-solving means trying all possible solutions without optimization.

3. What is "trial and error" as a problem-solving strategy?

• A systematic approach to problem-solving
• Randomly trying different solutions until one works
• A method used only in mathematics
• A formal proof technique

"Trial and error" as a problem-solving strategy involves randomly trying different solutions until one succeeds.

4. What is "divide and conquer" as a problem-solving technique?

• A strategy that avoids breaking problems into smaller subproblems
• A strategy that involves solving the largest subproblem first
• A strategy that breaks a problem into smaller subproblems and solves them independently
• A strategy that only works for small-scale problems

"Divide and conquer" is a problem-solving technique that breaks a problem into smaller subproblems and solves them independently.

5. In problem-solving, what is a "heuristic"?

• An optimal solution to a problem
• A rule of thumb or a practical approach to find a solution
• A random choice among multiple solutions

A heuristic is a rule of thumb or a practical approach used to find a solution in problem-solving.

6. What is "trial division" as a technique in number theory and prime factorization?

• A method to find the smallest prime number
• A method to verify if a number is prime by dividing it by smaller primes
• A method to find the largest prime number
• A method to add prime numbers

"Trial division" is a technique in number theory and prime factorization used to verify if a number is prime by dividing it by smaller primes.

7. What is the primary purpose of "backtracking" in problem-solving?

• To find the optimal solution
• To explore all possible solutions systematically
• To avoid exploring all possible solutions
• To simplify the problem

The primary purpose of "backtracking" in problem-solving is to explore all possible solutions systematically, typically in a recursive manner.

8. What is an algorithm?

• A data structure used to store information
• A sequence of steps to solve a problem
• A programming language
• A type of computer hardware

An algorithm is a sequence of steps or instructions designed to solve a specific problem or perform a task.

9. What is the primary goal of algorithm analysis?

• To design algorithms
• To implement algorithms
• To compare algorithms and evaluate their efficiency
• To debug algorithms

The primary goal of algorithm analysis is to compare algorithms and evaluate their efficiency.

10. Which of the following is NOT a characteristic of a good algorithm?

• Clarity and simplicity
• Efficiency in terms of time and space
• The use of complex data structures
• Correctness

A good algorithm is characterized by clarity, simplicity, efficiency, and correctness. Complex data structures may be used if necessary, but simplicity is preferred.

11. What is the purpose of pseudocode in algorithm development?

• To hide the algorithm's logic
• To provide a step-by-step implementation guide
• To obfuscate the algorithm
• To prevent others from understanding the algorithm

Pseudocode is used to provide a step-by-step implementation guide for an algorithm, making it easier to understand and develop.

12. Which algorithm design technique involves breaking a problem into smaller subproblems and solving each subproblem recursively?

• Divide and conquer
• Dynamic programming
• Greedy algorithm
• Backtracking

The "divide and conquer" algorithm design technique involves breaking a problem into smaller subproblems and solving each subproblem recursively.

13. What is the time complexity of an algorithm?

• The number of steps required to execute the algorithm
• The amount of memory used by the algorithm
• The analysis of the algorithm's efficiency in terms of input size
• The number of loops in the algorithm

Time complexity is the analysis of an algorithm's efficiency in terms of input size.

14. What is the "Big O notation" used for in algorithm analysis?

• To measure the algorithm's popularity
• To describe the algorithm's internal details
• To express the upper bound of an algorithm's time complexity
• To provide pseudocode for the algorithm

The Big O notation is used to express the upper bound of an algorithm's time complexity.

15. Which of the following time complexities represents the most efficient algorithm?

O(1) represents constant time complexity, which is the most efficient algorithm in terms of time.

16. What is the space complexity of an algorithm?

• The analysis of the algorithm's efficiency in terms of output size

Space complexity is the amount of memory used by the algorithm.

17. What does "optimization" refer to in the context of algorithms?

• The process of making an algorithm more complex
• The process of making an algorithm run slower
• The process of improving an algorithm's efficiency
• The process of making an algorithm more obscure

Optimization in the context of algorithms refers to the process of improving an algorithm's efficiency.

18. Which searching algorithm works by repeatedly dividing the search range in half until the target element is found?

• Linear search
• Binary search
• Quick search
• Merge search

Binary search works by repeatedly dividing the search range in half until the target element is found.

19. Which sorting algorithm has an average time complexity of O(n log n) and is often used for large datasets?

• Bubble sort
• Insertion sort
• Selection sort

Merge sort has an average time complexity of O(n log n) and is efficient for large datasets.

20. What is the primary advantage of quicksort over some other sorting algorithms like bubble sort and insertion sort?

• Quicksort always has a time complexity of O(1).
• Quicksort is a stable sorting algorithm.
• Quicksort has an average time complexity of O(n log n).
• Quicksort uses fewer comparisons.

Quicksort has an average time complexity of O(n log n), which is more efficient than the average case time complexity of bubble sort and insertion sort.

21. Which sorting algorithm repeatedly selects the smallest element from the unsorted part of the array and places it at the beginning of the sorted part?

Selection sort repeatedly selects the smallest element from the unsorted part and places it at the beginning of the sorted part.

22. What is the time complexity of the bubble sort algorithm in the worst-case scenario?

The worst-case time complexity of the bubble sort algorithm is O(n^2).

23. What data structure represents a collection of nodes connected by edges, where each edge has a direction?

• Linked list

A graph represents a collection of nodes connected by edges, where edges can have directions.

24. In a binary tree, how many children can each node have at most?

In a binary tree, each node can have at most two children: a left child and a right child.

25. What is the root node in a tree data structure?

• The node with the highest value
• The first node in the tree
• The node with the lowest value
• The topmost node from which all other nodes descend

The root node in a tree data structure is the topmost node from which all other nodes descend.

26. Which traversal method starts from the root node and explores as far as possible along each branch before backtracking?

• Inorder traversal
• Preorder traversal
• Postorder traversal
• Depth-first traversal

Preorder traversal starts from the root node and explores as far as possible along each branch before backtracking.

27. What is a common application of breadth-first search (BFS) in graph algorithms?

• Finding the shortest path between two nodes
• Sorting the nodes in a graph
• Calculating the depth of a tree
• Traversing a tree in preorder

A common application of breadth-first search (BFS) is finding the shortest path between two nodes in a graph.

28. What is dynamic programming commonly used for in algorithm design?

• Solving problems that cannot be solved by algorithms
• Solving problems by breaking them into smaller subproblems and caching their solutions
• Creating algorithms without any optimization
• Generating random solutions to problems

Dynamic programming is commonly used for solving problems by breaking them into smaller subproblems and caching their solutions to avoid redundant computation.

29. What is memoization in the context of dynamic programming?

• A technique for generating random numbers
• A method for optimizing algorithms using parallel processing
• Caching and reusing previously computed results to avoid redundant calculations
• A type of sorting algorithm

Memoization in dynamic programming involves caching and reusing previously computed results to avoid redundant calculations.

30. Which dynamic programming technique typically uses a table to store and retrieve solutions to subproblems?

• Memoization

Tabulation is a dynamic programming technique that typically uses a table to store and retrieve solutions to subproblems.

31. In dynamic programming, what does "optimal substructure" mean?

• The process of finding the best algorithm
• The property that the optimal solution to a problem can be constructed from the optimal solutions of its subproblems
• The use of greedy algorithms
• The analysis of algorithm efficiency

Optimal substructure is the property that the optimal solution to a problem can be constructed from the optimal solutions of its subproblems.

32. What is the primary advantage of dynamic programming over brute-force methods?

• Dynamic programming always produces the correct result.
• Dynamic programming is faster.
• Dynamic programming requires less memory.
• Dynamic programming optimally solves all problems.

The primary advantage of dynamic programming is that it is often faster than brute-force methods because it avoids redundant computations.

33. What is a greedy algorithm in algorithm design?

• An algorithm that always selects the largest available option
• An algorithm that makes a series of choices, each one being the best decision at the moment
• An algorithm that never backtracks
• An algorithm that solves problems by brute force

A greedy algorithm makes a series of choices, each being the best decision at the moment, with the hope of finding a globally optimal solution.

34. In the context of greedy algorithms, what is a "greedy choice property"?

• The property that a locally optimal choice leads to a globally optimal solution
• The property that a greedy algorithm is always the best choice
• The property that a greedy algorithm never makes a mistake
• The property that a greedy algorithm selects the largest option first

The greedy choice property states that a locally optimal choice in a greedy algorithm leads to a globally optimal solution.

35. Which classic greedy algorithm is used to solve the problem of finding the minimum number of coins needed to make change for a given amount of money?

• Kruskal's algorithm
• Huffman coding
• Coin change algorithm

The coin change algorithm is used to find the minimum number of coins needed to make change for a given amount of money.

36. What is the primary drawback of greedy algorithms?

• They are slow and inefficient.
• They can sometimes lead to suboptimal solutions.
• They require a lot of memory.
• They are difficult to implement.

The primary drawback of greedy algorithms is that they can sometimes lead to suboptimal solutions because they make locally optimal choices at each step.

37. What is a "cycle" in a directed graph?

• A path that visits every node exactly once
• A path that visits the same node twice or more, starting and ending at the same node
• A path that visits every node in the graph
• A path that visits all leaf nodes

In a directed graph, a cycle is a path that visits the same node twice or more, starting and ending at the same node.

38. Which algorithm is commonly used to find the shortest path between nodes in a weighted graph?

Dijkstra's algorithm is commonly used to find the shortest path between nodes in a weighted graph.

39. What is a "topological sort" of a directed acyclic graph (DAG)?

• An arrangement of nodes in ascending order based on their values
• An arrangement of nodes in descending order based on their values
• A linear ordering of nodes such that for every directed edge (u, v), node u comes before node v
• A linear ordering of nodes that connects all nodes in a graph

A topological sort of a directed acyclic graph (DAG) is a linear ordering of nodes such that for every directed edge (u, v), node u comes before node v.

40. What is a "spanning tree" of a graph?

• A tree that includes all nodes of the graph
• A tree with the fewest number of nodes
• A tree with the most number of nodes
• A tree with no nodes

A spanning tree of a graph is a tree that includes all nodes of the graph.

41. In dynamic programming, what is "bottom-up" or "tabulation" approach?

• Starting with the largest subproblems and solving them first
• Starting with the smallest subproblems and solving them first
• Starting with the middle-sized subproblems and solving them first
• Starting with the most complex subproblems and solving them first

The "bottom-up" or "tabulation" approach in dynamic programming starts with the smallest subproblems and solves them first, building up to the larger problem.

42. In dynamic programming, what is the "optimal substructure" property?

• The property that an algorithm always produces the optimal solution
• The property that an algorithm never uses subproblems
• The property that the optimal solution can be constructed from optimal solutions of subproblems
• The property that subproblems cannot be solved independently

The "optimal substructure" property in dynamic programming states that the optimal solution can be constructed from optimal solutions of subproblems.

43. What is the purpose of a "memoization table" in dynamic programming?

• To store the algorithm's pseudocode
• To store the names of subproblems
• To cache and retrieve previously computed results of subproblems
• To store debugging information

A memoization table in dynamic programming is used to cache and retrieve previously computed results of subproblems to avoid redundant calculations.

44. What is the "overlap" property in dynamic programming?

• The property that two subproblems share a common solution
• The property that subproblems do not share any common elements
• The property that all subproblems have identical solutions

The "overlap" property in dynamic programming refers to the property that two or more subproblems share a common solution, leading to the need for memoization.

45. In the context of dynamic programming, what is "pruning"?

• The process of removing nodes from a graph
• The process of reducing the complexity of an algorithm
• The process of removing unnecessary branches from a search
• The process of rearranging data structures

In dynamic programming, pruning is the process of removing unnecessary branches from a search to reduce computational effort.

46. Which dynamic programming technique uses a bottom-up approach and fills a table iteratively to solve problems?

• Greedy approach

The tabulation technique in dynamic programming uses a bottom-up approach and fills a table iteratively to solve problems.

47. What is a "weighted graph" in graph theory?

• A graph with no edges
• A graph in which each edge has a numerical weight or cost
• A graph with a large number of nodes
• A directed graph

A weighted graph is a graph in which each edge has a numerical weight or cost associated with it.

48. Which graph algorithm is used to find the minimum spanning tree of a weighted, connected graph?

• Bellman-Ford algorithm

Kruskal's algorithm is used to find the minimum spanning tree of a weighted, connected graph.

49. What is a "strongly connected component" in a directed graph?

• A component that contains only one node
• A component in which any two nodes are connected by a single edge
• A component in which there is a directed path from any node to any other node
• A component with the fewest edges

A strongly connected component in a directed graph is a component in which there is a directed path from any node to any other node within the component.

50. What is a "cycle detection" algorithm used for in graph theory?

• Detecting loops or cycles in a graph
• Finding the maximum flow in a network

A cycle detection algorithm is used to detect loops or cycles in a graph.

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Artificial Intelligence MCQ – Problem-Solving Agents

Here are 25 multiple-choice questions (MCQs) related to Artificial Intelligence, focusing specifically on Problem-Solving Agents. Each question includes four options, the correct answer, and a brief explanation. These MCQ questions cover various aspects of AI problem-solving agents, including algorithms, search strategies, optimization techniques, and problem-solving methods, providing a comprehensive overview of this area in AI.

1. What is the primary objective of a problem-solving agent in AI?

Explanation:.

A problem-solving agent is designed to find a sequence of actions that leads from the initial state to a goal state, solving a specific problem or achieving a set goal.

2. In AI, a heuristic function is used in problem-solving to:

A heuristic function is used to guide the search process by providing an educated guess about the cost to reach the goal from each node, thus helping to efficiently reduce the search space.

3. Which algorithm is commonly used for pathfinding in AI?

The A* Algorithm is widely used for pathfinding and graph traversal. It efficiently finds the shortest path between two nodes in a graph, combining the features of uniform-cost search and greedy best-first search.

4. What is "backtracking" in AI problem-solving?

Backtracking involves going back to previous states and trying different actions when the current path does not lead to a solution, allowing for exploring alternative solutions.

5. The "branch and bound" technique in AI is used to:

Branch and bound is an algorithmic technique used for solving various optimization problems. It systematically enumerates candidate solutions by branching and then uses a bounding function to eliminate suboptimal solutions.

6. Which of the following is a characteristic of a depth-first search algorithm?

Depth-first search explores as far as possible along each branch before backtracking, going deep into a search tree before exploring siblings of earlier nodes.

7. In AI, "constraint satisfaction problems" are typically solved using:

Constraint satisfaction problems, where a set of constraints must be met, are commonly solved using backtracking algorithms, which incrementally build candidates to the solutions and abandon candidates as soon as they determine that the candidate cannot possibly be completed to a valid solution.

8. The primary goal of "minimax" algorithm in AI is:

The minimax algorithm is used in decision-making and game theory to minimize the possible loss for a worst-case scenario. When dealing with gains, it seeks to maximize the minimum gain.

9. What is "state space" in AI problem-solving?

The state space in AI problem-solving refers to the set of all possible states that can be reached from the initial state by applying a sequence of actions. It is often represented as a graph.

10. In AI, "pruning" in the context of search algorithms refers to:

Pruning in search algorithms involves eliminating paths that are unlikely to lead to the goal or are less optimal, thus reducing the search space and improving efficiency.

11. The "traveling salesman problem" in AI is an example of:

The traveling salesman problem is a classic optimization problem in AI and computer science, where the goal is to find the shortest possible route that visits a set of locations and returns to the origin.

12. "Greedy best-first search" in AI prioritizes:

Greedy best-first search is a search algorithm that prioritizes nodes that seem to be leading to a solution the quickest, often using a heuristic to estimate the cost from the current node to the goal.

13. In AI, "dynamic programming" is used to:

Dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is used when the subproblems are overlapping and the problem exhibits the properties of optimal substructure.

14. The "Monte Carlo Tree Search" algorithm in AI is widely used in:

Monte Carlo Tree Search (MCTS) is an algorithm used for making decisions in some kinds of game-playing, particularly where it is impractical to search all possible moves due to the complexity of the game.

15. What does an "admissible heuristic" in AI guarantee?

An admissible heuristic is one that never overestimates the cost to reach the goal. In heuristic search algorithms, using an admissible heuristic guarantees finding an optimal solution.

16. The concept of "hill climbing" in AI problem solving is similar to:

Hill climbing in AI is a mathematical optimization technique which belongs to the family of local search. It is used to solve computational problems by continuously moving in the direction of increasing elevation or value.

17. The "no free lunch theorem" in AI implies that:

The "no free lunch" theorem states that no one algorithm works best for every problem. It implies that each problem needs to be approached uniquely and that there's no universally superior method.

18. In AI, "means-ends analysis" is a technique used in:

Means-ends analysis is a problem-solving technique used in AI that involves breaking down the difference between the current state and the goal state into smaller and smaller differences, then achieving those smaller goals.

19. The "Pigeonhole principle" in AI is used to:

In AI and mathematics, the Pigeonhole principle is used to prove that a solution exists under certain conditions. It states that if n items are put into m containers, with n > m, then at least one container must contain more than one item.

20. "Simulated annealing" in AI is inspired by:

Simulated annealing is an optimization algorithm that mimics the process of annealing in metallurgy. It involves heating and controlled cooling of a material to increase the size of its crystals and reduce their defects.

21. In AI, the "Bellman-Ford algorithm" is used for:

The Bellman-Ford algorithm is an algorithm that computes shortest paths from a single source vertex to all of the other vertices in a weighted graph. It's particularly useful for graphs where edge weights may be negative.

22. What is the primary function of "Alpha-Beta pruning" in AI?

Alpha-Beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree. It is used in game playing to prune away branches that cannot possibly influence the final decision.

23. The "Hungarian algorithm" in AI is best suited for solving:

The Hungarian algorithm, a combinatorial optimization algorithm, is used for solving assignment problems where the goal is to assign resources or tasks to agents in the most effective way.

24. In problem-solving, "depth-limited search" is used to:

Depth-limited search is a modification of depth-first search, where the search is limited to a specific depth. This prevents the algorithm from going down infinitely deep paths and helps manage the use of memory.

25. "Bidirectional search" in AI problem solving is used to:

Bidirectional search is an efficient search strategy that runs two simultaneous searches: one forward from the initial state and the other backward from the goal, stopping when the two meet. This approach can drastically reduce the amount of required exploration.

Related MCQ (Multiple Choice Questions) :

Artificial intelligence mcq – agents, artificial intelligence mcq – natural language processing, artificial intelligence mcq – partial order planning, artificial intelligence mcq – expert systems, artificial intelligence mcq – fuzzy logic, artificial intelligence mcq – neural networks, artificial intelligence mcq – robotics, artificial intelligence mcq – rule-based system, artificial intelligence mcq – semantic networks, artificial intelligence mcq – bayesian networks, artificial intelligence mcq – alpha beta pruning, artificial intelligence mcq – text mining, leave a comment cancel reply.

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Problem Solving MCQ Set 1

Question: Tom, Dick and Harry went for lunch to a restaurant. Tom had $100 with him, Dick had $60 and Harry had $409. They got a bill for $104 and decided to give a tip of $16. They further decided to share the total expenses in the ratio of the amounts of money each carried. The amount of money which Tom paid more than what Harry paid is

Correct Answer: E

Explanation:

Explanation under process. It will be available soon.

Question: A plot of land is in the shape of a trapezium whose dimensions are given in the figure below :

• None of the above

Correct Answer: C

Question: Four concentric ( having the same center ) circles with radii, x, 2x, 3x and 4x are drawn to form two rings A and B as shown in the figure.

Correct Answer: D

Question: If 3/p = 6 and 3/q = 15 then p - q = ?

Question: A father is three times as old as his son. After fifteen years the father will be twice as old as his son's age at that time. Hence the father's present age is

Explanation under process. It will be available soon.div>

Question: (1/4) 3 + (3/4) 3 + 3(1/4)(3/4)(1/4 + 3/4) =?

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What is the best type of thinking when solving a problem?

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Programming MCQ (Multiple Choice Questions)

Our Programming Questions and Answers prepares an individual for competitive exams, entrance exams, various tests and interviews. Questions have detailed problem descriptions and solutions with detailed explanations so that one can understand them easily. One should spend 1 hour daily for 5-6 months to learn and assimilate various Programming subjects comprehensively. Here’s the benefits of our completely solved Programming questions and answers:

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3. Programming Multiple Choice Questions – Quiz Questions

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Introduction to Problem Solving Class 11 MCQ

Teachers and Examiners ( CBSESkillEduction ) collaborated to create the Introduction to Problem Solving Class 11 MCQ . All the important Information are taken from the NCERT Textbook Computer Science (083) class 11 .

1. Computers cannot solve problems on their own. We must provide clear, step-by-step directions on how to solve the issue, this solving technique is known as ____________. a. Problem Solving  b. Problem Addressing c. Problem Analysis d. None of the above

2. ___________ is the process of identifying a problem, developing an algorithm for the identified problem and finally implementing the algorithm to develop a computer program. a. Problem Solving  b. Problem Addressing c. Problem Analysis d. None of the above

3. It is essential to device a solution before writing a program code for a given problem. The solution is represented in natural language and is called an ___________. a. Problem b. Algorithm  c. Problem Analysis d. None of the above

4. After finalizing the algorithm, we need to convert the algorithm into the_________. a. Format which can be understood by the computer b. High level programming language c. Both a) and b)  d. None of the above

5. What are the different type of testing. a. Component testing b. Integration testing c. System testing & Acceptance testing d. All of the above 

6. The developed programme needs to pass different parameter __________. The programme needs to fulfil the user’s requirements. It must respond in the anticipated amount of time. a. Method b. Testing  c. Error d. None of the above

7. To complete each activity in a computer, we follow a sequence of steps. This sequence of steps is known as ________. a. Problem b. Algorithm  c. Problem Analysis d. None of the above

8. ____________ is the act of locating and fixing problems in software code that could lead to unexpected behavior or crashes. These errors are sometimes referred to as “bugs.” a. Algorithm b. Problem Solving c. Debugging  d. All of the above

9. Why do we need an Algorithm? a. Accuracy b. Minimized mistakes c. Best possible solution d. All of the above 

10. Writing an algorithm is mostly considered as a ________. a. First step of programming  b. Second step of programming c. Third step of programming d. None of the above

11. Purpose of using algorithm? a. Increase the reliability b. Accuracy of the program c. Efficiency of obtaining solutions d. All of the above 

12. Characteristics of a good algorithm. a. Precision & Uniqueness b. Finiteness c. Input & Output d. All of the above 

13. Before implementing algorithm, the programmer should __________ first. a. Analyze the problem b. Identify the problem c. Both a) and b)  d. None of the above

14. A __________ is a visual representation of an algorithm. a. Flowchart  b. Pseudocode c. Algorithm d. None of the above

15. A flowchart is a diagram made up of __________. a. Boxes b. Diamonds c. Shapes d. All of the above 

16. Start/End also called _________ symbol, it indicates where the flow starts and ends. a. Terminator  b. Decision c. Input / Output d. Arrow

17. Process is also called ________, it represents a process, action, or a single step. a. Terminator b. Action Symbol  c. Decision d. Input/ Output

18. A __________ or branching point, usually a yes/no or true/ false question is asked, and based on the answer, the path gets split into two branches. a. Terminator b. Action Symbol c. Decision  d. Input/ Output

19. _________ is also called data symbol, this parallelogram shape is used to input or output data. a. Terminator b. Action Symbol c. Decision d. Input/ Output 

20. ___________ connector to show order of flow between shapes. a. Terminator b. Action Symbol c. Decision d. Arrow 

21. A ___________ is another way of representing an algorithm. It is considered as a non-formal language that helps programmers to write algorithm. a. Flowchart b. Pseudocode  c. Algorithm d. None of the above

22. The word “pseudocode” means ___________. a. Not real code  b. Real code c. Temporary code d. None of the above

23. It is necessary to run different input values through the algorithm’s phases in order to verify. This process of taking an input and running it through all of the algorithm’s steps is commonly referred to as a _______. a. Code b. Dry run  c. Method d. None of the above

24. Dry run will help us to __________. a. Identify any incorrect steps in the algorithm b. Figure out missing details or specifics in the algorithm c. Both a) and b)  d. None of the above

25. algorithms can be ___________ on the basis of the amount of processing time they need to run and the amount of memory that is needed to execute the algorithm. a. Compared b. Analyzed c. Both a) and b)  d. None of the above

26. ___________ is the set of rules or grammar that governs the formulation of the statements in the language, such as spellings, order of words, punctuation, etc. a. Analyzed b. Syntax  c. Code d. None of the above

27. Programs written using ________ are directly understood by the computer hardware, but they are difficult to deal with and comprehend by humans. a. High Level Language b. Binary Digit  c. 4GL Language d. None of the above

28. A program written in a high-level language is called ___________. a. Source code  b. Object c. Machine language d. None of the above

29. What type of problems are solved by computer. a. Easy problem b. Complex problem c. Both a) and b)  d. None of the above

30. The basic idea of solving a complex problem by decomposition is to __________. a. Decompose b. Break down c. Complex problem into smaller sub problems d. All of the above 

31. An algorithm is defined as a _________ procedure designed to perform an operation which will lead to the desired result, if followed correctly. a. Reverse procedure b. Step-by-step procedure  c. Random procedure d. None of the above

32. Algorithms have a definite ________ and a definite ________, and a finite number of steps. a. Middle & End b. Beginning & End  c. Beginning & Middle d. None of the above

33. A good algorithm, which is __________, receives input and produces an output. a. Precise b. Unique c. Finite d. All of the above 

34. In order to write effective algorithms we need to identify the__________ to be followed and the desired output. a. Input b. Process c. Both a) and b)  d. None of the above

35. A flowchart is a type of diagram that represents the algorithm graphically using boxes of various kinds, in an order connected by arrows. a. Flowchart  b. Algorithm c. Pseudocode d. None of the above

36. An _________ where all the steps are executed one after the other is said to execute in sequence. a. Flowchart b. Algorithm  c. Pseudocode d. None of the above

37. _________ making involves selection of one of the alternatives based on outcome of a condition. a. Terminator b. Action Symbol c. Decision  d. Arrow

38. An _________ may have a certain set of steps, which are repeating for a finite number of times, such an algorithm is said to be iterative. a. Flowchart b. Algorithm  c. Pseudocode d. None of the above

39. There can be __________ approach to solve a problem and hence we can have more than one algorithm for a particular problem. a. Only one b. More than one  c. No approach d. None of the above

40. The choice of __________ should be made on the basis of time and space complexity. a. Flowchart b. Algorithm  c. Pseudocode d. None of the above

Computer Science Class 11 Notes

• Unit 1 : Basic Computer Organisation
• Unit 1 : Encoding Schemes and Number System
• Unit 2 : Introduction to problem solving
• Unit 2 : Getting Started with Python
• Unit 2 : Conditional statement and Iterative statements in Python
• Unit 2 : Function in Python
• Unit 2 : String in Python
• Unit 2 : Lists in Python
• Unit 2 : Tuples in Python
• Unit 2 : Dictionary in Python
• Unit 3 : Society, Law and Ethics

Computer Science Class 11 MCQ

Computer science class 11 ncert solutions.

• Unit 2 : Tuples and Dictionary in Python

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Essential Psychology

Student resources, multiple choice questions.

1. The Tower of London problem-solving task was developed by

• Shackleton (1982)
• Shallice (1982)
• Sheriff (1982)
• Sherrington (1982)

2. The process of breaking down goals into subgoals is termed

• means–ends analysis
• initial-desired state analysis
• subgoal appropriation
• subgoal potentiation

3. According to Newell and Simon, a problem-solver

• analyzes all possible solutions before beginning
• attempts to resolve differences between problem states
• works backwards from the goal state
• prioritizes subgoals

4. What computer programme did Newell and Simon create to validate their theory?

• general purpose solution
• general problem solver
• enigma machine

5. A challenge to Newell and Simon’s problem-solving theory is that

• experts mostly use means–ends analysis
• novices mostly use means–ends analysis
• experts do not always use means–ends analysis
• novices do not always use means–ends analysis

6. Answers that appear out of the blue to solve problems are

7. Difficulty seeing the solution to a problem is

• means analysis

8. Which is NOT a type of reasoning?

• probabilistic

9. Bayes’ theorem can be used to calculate

• possibility
• probability
• information criterion
• means–ends differences

10. A heuristic is

• a rule of thumb

Java Guides

Search this blog, core java mcq - top 100 questions and answers.

Welcome to this comprehensive guide featuring 100 Multiple-Choice Questions (MCQs) on Core Java. Java remains one of the most popular, versatile, and widely-used programming languages in the world, and understanding its core concepts is essential for anyone aspiring to become proficient in it. Whether you are a beginner, an intermediate programmer, or even an expert looking for a quick refresher, this blog post is your go-to resource.

We've curated these questions to cover all the important Core Java topics such as variables, data types, operators, control statements, loops, arrays, methods, inheritance, polymorphism, interfaces, packages, exception handling, multithreading, and much more. This ensures a rounded understanding of Java’s fundamentals.

But we didn’t stop there! Each question is followed by the correct answer as well as an explanation. These explanations are designed to reinforce your knowledge and help clarify any doubts you may have.

Are you ready to level up your Java skills? Let's dive into the quiz!

1. Who developed the Java programming language?

Explanation:.

Java was developed by Sun Microsystems. Later, Oracle acquired Sun Microsystems in 2010.

2. In which year was the first version of Java released?

The first version of Java, Java 1.0, was officially released by Sun Microsystems in 1995.

3. What was the original name for Java?

Java was initially called "Oak." It was developed by Sun Microsystems' Green Team, led by James Gosling.

4. What does JVM stand for?

JVM stands for Java Virtual Machine. It is a virtualization engine that enables Java applications to run on various hardware platforms without modification.

5. Which of the following is responsible for converting bytecode into machine code?

JVM is responsible for converting bytecode (intermediate code) into machine code, ensuring Java's "Write Once, Run Anywhere" philosophy.

6. What does JDK include?

JDK (Java Development Kit) includes the Java Runtime Environment (JRE) and other tools like the Java compiler (javac).

7. Which of the following is NOT a part of the JRE?

The Java compiler (javac) is a part of the JDK (Java Development Kit) and not the JRE (Java Runtime Environment).

8. What is the primary function of JRE?

JRE (Java Runtime Environment) is responsible for providing the runtime environment where Java programs can be executed.

9. Can you run a Java program without JRE?

JRE (Java Runtime Environment) is essential for running Java programs. Without it, the Java bytecode cannot be executed.

10. Is JVM platform-independent?

While Java code (bytecode) is platform-independent, JVMs are not. Each operating system has its own JVM.

11. Which operator is used to perform bitwise "AND" operation?

The & operator is used to perform a bitwise "AND" operation.

12. What does the == operator compare in Java objects?

For objects, the == operator compares references, not the content of the objects. To compare the content, you would typically use the .equals() method.

13. Which operator is used for logical "AND" operation?

The && operator is used for the logical "AND" operation and is short-circuiting, meaning it won't evaluate the second operand if the first one is false.

14. Which of the following is a unary operator?

Unary operators are operators that act on a single operand. +, -, and ! are all unary operators in Java.

15. Which operator has the highest precedence?

Parentheses () have the highest precedence in Java and are used to explicitly specify the order of evaluation in expressions.

16. What is the output of the expression true || false?

The || operator is a logical OR. The result of true || false is true.

17. Which of the following is not a primitive data type in Java?

String is a reference data type, not a primitive data type.

18. What is the default value of the int data type?

The default value of the int data type is 0. In Java, each primitive data type has a default value.

19. Which of the following data types can store a floating-point number?

The double data type can store floating-point numbers. There's also float, but it wasn't listed among the options.

20. Which data type can store a single character?

The char data type is used to store a single character.

21. How many bits does the long data type use?

The long data type uses 64 bits to store its values.

22. What's the main difference between int and Integer in Java?

int is a primitive data type, whereas Integer is a wrapper class that provides methods to operate on the int data type.

23. Which loop construct in Java is best suited when the number of iterations is known?

The for loop in Java is best suited when the number of iterations is known.

24. What is the purpose of the continue statement in a loop?

The continue statement in Java is used to skip the current iteration of a loop and move to the next iteration.

25. Which loop construct in Java is best suited when the number of iterations is unknown?

The while loop in Java is used when the number of iterations is unknown or depends on a certain condition.

26. What is the key difference between a while loop and a do-while loop in Java?

The key difference between a while loop and a do-while loop in Java is the timing of the condition check. In a while loop, the condition is checked before the loop body is executed, whereas in a do-while loop, the condition is checked after the loop body is executed.

27. Which loop construct guarantees that the loop body is executed at least once?

The do-while loop in Java guarantees that the loop body is executed at least once, as the condition is checked after the loop body is executed.

28. What is an infinite loop?

An infinite loop in Java is a loop that never terminates naturally unless interrupted externally or using a break statement.

29. Which statement is used to exit a loop prematurely?

The break statement in Java is used to exit a loop prematurely and continue with the execution of the code outside the loop.

30. Which loop construct is best suited for iterating over an array or a collection?

The for loop in Java is best suited for iterating over an array or a collection, as it provides a convenient way to control the iteration using an index or an iterator.

31. How do you declare an array in Java?

Arrays in Java can be declared using either int[] arrayName; or int arrayName[];.

32. Which method is used to get the length of an array in Java?

The length property is used to get the number of elements in an array, e.g., arrayName.length.

33. How do you initialize an array in Java?

Arrays can be initialized using the new keyword followed by the type, and values enclosed in curly braces.

34. What happens when you try to access an array element with an index that is out of bounds?

Accessing an element outside the array's range will throw an ArrayIndexOutOfBoundsException.

35. How can you check if two arrays are equal in Java?

The Arrays.equals() method is the correct way to check if two arrays are equal. Using the == operator checks for reference equality, not the content.

36. How do you access the fourth element of an array named numbers?

Arrays use zero-based indexing, which means the fourth element is accessed using index 3.

37. Which of the following operators is used for concatenation of two strings?

In Java, the + operator is overloaded for string concatenation. When used between two strings, it concatenates them.

38. Which of the following creates a mutable string?

StringBuilder is a mutable sequence of characters, whereas String is immutable.

39. In Java, strings are:

Once a String object is created, its content cannot be modified. Hence, it's considered immutable.

40. How do you find the length of a string named 'example'?

The length() method returns the number of characters in a string.

41. What is the result of the expression "Java" + "Programming"?

The + operator concatenates two strings without adding any extra spaces.

42. Which method is used to compare two strings for equality?

The equals() method compares the content of two strings. The == operator compares the memory addresses, not the content.

43. Which class can create a string that is thread-safe?

StringBuffer is thread-safe, whereas StringBuilder is not.

44. What is the root class for all Java classes?

The Object class is the root of the Java class hierarchy. Every class has Object as a superclass.

45. What is polymorphism?

Polymorphism allows objects to be treated as instances of their parent class, leading to simplified code and a way to use objects dynamically.

46. What is encapsulation in Java?

Encapsulation is one of the four fundamental Object-Oriented Programming (OOP) concepts. The main idea behind encapsulation is to bind together the data (attributes) and the methods (functions) that operate on the data into a single unit or class. It also serves to hide the internal state of an object and requires the use of methods to access the object's data. This ensures that unwanted or unexpected modifications don't occur.

47. What is inheritance in Java?

Inheritance is a mechanism in Java that allows a class to inherit properties and behaviors from another class. It promotes code reuse by enabling the creation of subclasses that inherit the attributes and methods of a superclass. Subclasses can also add their own unique attributes and methods.

48. What is polymorphism in Java?

Polymorphism refers to the ability of an object to take on many forms or have multiple behaviors. In Java, polymorphism is achieved through method overriding and method overloading. It allows objects of different classes to be treated as objects of a common superclass, providing flexibility and extensibility.

49. What are abstract classes in Java?

Abstract classes in Java cannot be instantiated directly and are typically used as blueprints for creating objects. They can contain abstract methods (methods without implementation) and regular methods. Abstract classes provide a way to define common behavior and enforce specific methods to be implemented by subclasses.

50. What is the purpose of the "super" keyword in Java?

The "super" keyword in Java is used to refer to the superclass (or parent class) of the current object. It is commonly used to invoke the superclass constructor or methods within the subclass. The "super" keyword allows for code reuse and accessing superclass members that may be overridden in the subclass.

51. What is the purpose of the "this" keyword in Java?

The "this" keyword in Java is used to refer to the current object within an instance method or constructor. It is often used to distinguish between instance variables and method parameters or to access methods and variables of the current object.

52. What is the purpose of the "final" keyword in Java?

The "final" keyword in Java can be used to prevent the inheritance of a class, overriding of a method, or modification of a variable's value. When a class, method, or variable is declared as final, it cannot be further extended, overridden, or modified, respectively.

53. What is an interface in Java?

An interface in Java is a blueprint that can be used to implement classes. It can have methods and variables, but the methods are abstract by default.

54. Which keyword is used to implement an interface?

The implements keyword is used by classes to implement an interface.

55. Can an interface extend another interface in Java?

Interfaces can extend other interfaces in Java, allowing an interface to inherit abstract methods from another interface.

56. Can an interface have a constructor?

Interfaces cannot have constructors because they cannot be instantiated.

57. Which of the following access modifiers are implicitly applied to variables in an interface?

Variables in an interface are implicitly public, static, and final.

58. Is it possible to create an instance of an interface?

We cannot instantiate an interface directly. However, we can create reference variables of an interface type.

59. How many interfaces can a Java class implement?

A Java class can implement any number of interfaces.

60. Can an interface inherit from a class?

An interface cannot inherit from a class. It can only extend other interfaces.

61. Can an interface method be declared as final?

Methods in an interface are implicitly abstract, and abstract methods cannot be final.

62. In Java 9, which type of methods can be added to interfaces to share code between methods?

Starting from Java 9, interfaces can have private methods, which can help in sharing code between methods without exposing them to external classes.

63. An interface with no methods is known as?

An interface with no defined methods is known as a marker interface. It is used to mark classes that support certain capabilities.

64. Which keyword is used to define a default method in an interface?

The "default" keyword is used to define a default method in an interface.

65. Are all methods in an interface abstract?

Prior to Java 8, all methods in an interface were implicitly abstract. However, with Java 8 and onwards, interfaces can have default and static methods.

66. Which of these can be contained in an interface?

An interface can contain abstract methods, constants (public, static, final variables), static methods, and default methods.

67. Which Java feature helps achieve multiple inheritance?

In Java, multiple inheritance is achieved through interfaces. A class can implement multiple interfaces, thereby inheriting the abstract methods of all the interfaces.

68. What is the default access modifier of a method in an interface in Java?

Interface methods are public by default since the idea is for them to be implemented by other classes.

69. Why were default methods introduced in Java 8 interfaces?

Default methods allow developers to add new methods to interfaces with an implementation without affecting classes that already use this interface.

70. Starting from which Java version can an interface contain method implementations?

From Java 8 onwards, interfaces can have default and static method implementations.

71. What is the purpose of the instanceof operator?

The instanceof operator is used to check if an object belongs to a particular class or implements a particular interface.

72. Which keyword is used to declare a class variable?

The static keyword is used to declare a class variable which is common to all instances of a class.

73. Which keyword is used to prevent a class from being inherited?

A class declared as final cannot be subclassed or extended.

74. Which keyword is used to create an instance of a class?

The new keyword is used to instantiate an object from a class.

75. Which keyword is used to inherit the properties and methods from another class?

The extends keyword is used to inherit properties and methods from another class.

76. Which keyword is used to refer to the current instance of a class?

The this keyword is used to refer to the current instance of a class.

77. Which keyword in Java is used for importing packages into a program?

The import keyword is used to import a package or a class into a Java program.

78. What does the transient keyword indicate in a Java class?

The transient keyword indicates that the variable should not be serialized when the class instance is persisted.

79. Which of these is a checked exception?

IOException is a checked exception. Checked exceptions need to be either caught or declared in the method signature using the throws keyword.

80. Which of the following can be used to create a custom checked exception?

To create a custom-checked exception, you can extend the Exception class.

81. Which of these is an unchecked exception?

ArithmeticException, like all subclasses of RuntimeException, is an unchecked exception.

82. Which keyword is used to manually throw an exception in Java?

The throw keyword is used to explicitly throw an exception.

83. Which of these classes is the superclass of all Exception and Error classes?

The Throwable class is the superclass of all exception and error classes.

84. What does the finally block do?

The finally block is executed irrespective of whether an exception is thrown or caught.

85. Which keyword in Java is used for constant variables?

In Java, the final keyword is used to declare constant variables.

86. In Java, what is the primary purpose of the Thread class?

The Thread class in Java is primarily used for creating and executing threads.

87. Which method is used to start the execution of a thread?

The start() method is used to initiate the execution of a thread. It internally calls the run() method.

88. What does the join() method do when called on a thread object?

The join() method makes the currently executing thread wait until the thread on which it's called completes its execution.

89. Which method can be used to momentarily pause the execution of the current thread?

The sleep() method is used to pause the execution of the current thread for a specified period.

90. Which interface provides an alternative to extending the Thread class?

The Runnable interface provides an alternative way to define thread execution behavior without the need to extend the Thread class.

91. What is a daemon thread in Java?

Daemon threads are background threads that usually run continuously, performing tasks like garbage collection.

92. Which interface represents a collection of objects in which duplicate values can be stored?

The List interface in Java allow the addition of duplicate elements.

93. What will be the initial capacity of an ArrayList if it is created with the no-argument constructor?

The default initial capacity of an ArrayList (when created with the no-argument constructor) is 10.

94. What does a Set guarantee?

A Set guarantees no duplicate elements but does not guarantee any specific order of elements.

95. Which List implementation is synchronized?

Vector is synchronized, whereas ArrayList and LinkedList are not.

96. Which interface represents a key-value pair mechanism?

The Map interface represents a key-value pair mapping.

97. Which method is used to check if a Collection is empty?

The isEmpty() method is used to check if a Collection is empty.

98. What does the Collections class sort() method do?

The sort() method in the Collections class sorts the elements in ascending order.

99. What is the key difference between HashSet and TreeSet?

HashSet does not maintain any order whereas TreeSet maintains elements in a sorted order.

100. Which Collection does not allow null values?

Hashtable does not allow null keys or null values.

101. Which method is used to insert an object at a specific position in a List?

The add(index, element) method is used to insert an element at a specific position in a List.

102. Which class provides a thread-safe implementation of the List interface?

Vector is a thread-safe implementation of the List interface.

103. Which interface provides methods to traverse through a collection?

The Iterator interface provides methods to traverse through a collection.

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How to Do Well on Multiple Choice Questions

Last Updated: January 31, 2023 Fact Checked

This article was co-authored by Ted Dorsey, MA . Ted Dorsey is a Test Prep Tutor, author, and founder of Tutor Ted, an SAT and ACT tutoring service based in Southern California. Ted earned a perfect score on the SAT (1600) and PSAT (240) in high school. Since then, he has earned perfect scores on the ACT (36), SAT Subject Test in Literature (800), and SAT Subject Test in Math Level 2 (800). He has a BA in English from Princeton University and a MA in Education from the University of California, Los Angeles. There are 9 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 305,140 times.

Multiple choice exams are popular among educators, as they test a student’s critical thinking and problem solving skills. You may struggle with multiple choice exams and not know how to do well on them. To get a good grade on a multiple choice exam, start by analyzing the questions. Then, answer the questions effectively by working through them strategically. You can also prepare for the exam so you do well and get a high mark.

Analyzing the Questions

• You can also read the question more than once to ensure you understand it. Take your time and do not rush through the question.

• You should also analyze the question for any phrasing that asks for multiple answers to the question, such as “Choose more than one answer” or “Choose two of the four options.”

• Doing this can help you think of an answer before you look at the multiple choice options. Chances are, the answer you come up with is one of the options for the question.
• If you can’t come up with your own answer, don’t fret. You can use the answers provided to come up with the right answer for the question.
• Indications of time: before, after, while, always, never
• Superlatives: most, least, most common, fastest, the best, the only
• Conditionals: each time X happens, if X happens, unless X, assuming X

Answering the Questions Effectively

• Take your time and read over each possible answer. Do not skim or skip over any possible answers. This will ensure you make an informed decision about the correct answer to the question.

• Look for possible answers that have “always,” “never,” and “none of the above” in them, as they are usually incorrect.
• When you go over the answers, avoid thinking that your instructor is trying to trip you up with sneaky or confusing options. Most instructors won't give you "trick" answers like this.

• For example, you may be torn between two answers for the question. Try out both answers for the question. Read the question to yourself and place each answer at the end of the question. Pick the one that appears the most correct to you.

• If you get stuck on one question, try to work through it slowly. If you are really stumped, put a star or mark next to it so you know to come back to it at the very end of the exam.

• When in doubt on an answer to a difficult question on the exam, go with your best judgement and choose the best answer you can identify from the list of options.

Preparing For a Multiple Choice Exam

• Cramming for the exam will cause you a lot of stress and anxiety. You may not retain information well if you cram the night before the exam, leading to a poor grade.

• Use the old exams and example questions to prepare for the test. Study the structure of the questions as well as the provided answers. Take several practice tests to get better at multiple choice style exams.
• If the instructor will not give you past exams, join a study group so you can study with others. You can also get a study tutor to help you study for the exam.

• Make sure you have a good breakfast high in protein, vitamins, and nutrients, like eggs, toast, and fruit, or yogurt and granola.

• 5 Study with trusted friends, and keep out of distractions, such as parties. This can cause to fail, distract you from the test you are studying. [15] X Research source

Community Q&A

• Don't assume that there will be a logic behind the order of correct answers. For example, just because you've already answered C three times in a row, doesn't mean that the next question can't also have C as its answer. Likewise, if you notice that you haven't answered D in a while, that doesn't mean that the next questions are more like to have D for an answer. Treat every question independently of the answers to the other questions. Thanks Helpful 7 Not Helpful 1
• Give yourself enough time to transfer your final answers to the official exam sheet (like a Scantron). About 5 minutes for every 10 questions is a good rule of thumb. Thanks Helpful 5 Not Helpful 1

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• ↑ https://www.butte.edu/departments/cas/tipsheets/studystrategies/multiple_choice.html
• ↑ https://www.educationcorner.com/multiple-choice-tests.html
• ↑ https://student.unsw.edu.au/multiple-choice-exams
• ↑ https://umanitoba.ca/student/academiclearning/media/Tips_on_Taking_Multiple_Choice_Exams_NEW.pdf
• ↑ https://www.dmu.edu/wp-content/uploads/MULTIPLE-CHOICE-TEST-TAKING-STRATEGIES.pdf
• ↑ https://www.socialpsychology.org/testtips.htm
• ↑ Ted Dorsey, MA. Academic Tutor. Expert Interview. 11 December 2019.
• ↑ https://learningcenter.unc.edu/tips-and-tools/studying-101-study-smarter-not-harder/
• ↑ Ted Coopersmith, MBA. Academic Tutor. Expert Interview. 10 July 2020.

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15 Common Problem-Solving Interview Questions

In an interview for a big tech company, I was asked if I’d ever resolved a fight — and the exact way I went about handling it. I felt blindsided, and I stammered my way through an excuse of an answer.

It’s a familiar scenario to fellow technical job seekers — and one that risks leaving a sour taste in our mouths. As candidate experience becomes an increasingly critical component of the hiring process, recruiters need to ensure the problem-solving interview questions they prepare don’t dissuade talent in the first place. 

Interview questions designed to gauge a candidate’s problem-solving skills are more often than not challenging and vague. Assessing a multifaceted skill like problem solving is tricky — a good problem solver owns the full solution and result, researches well, solves creatively and takes action proactively. 

It’s hard to establish an effective way to measure such a skill. But it’s not impossible.

We recommend taking an informed and prepared approach to testing candidates’ problem-solving skills . With that in mind, here’s a list of a few common problem-solving interview questions, the science behind them — and how you can go about administering your own problem-solving questions with the unique challenges of your organization in mind.

Key Takeaways for Effective Problem-Solving Interview Questions

• Problem solving lies at the heart of programming. 
• Testing a candidate’s problem-solving skills goes beyond the IDE. Problem-solving interview questions should test both technical skills and soft skills.
• STAR, SOAR and PREP are methods a candidate can use to answer some non-technical problem-solving interview questions.
• Generic problem-solving interview questions go a long way in gauging a candidate’s fit. But you can go one step further by customizing them according to your company’s service, product, vision, and culture. 

Technical Problem-Solving Interview Question Examples

Evaluating a candidates’ problem-solving skills while using coding challenges might seem intimidating. The secret is that coding challenges test many things at the same time — like the candidate’s knowledge of data structures and algorithms, clean code practices, and proficiency in specific programming languages, to name a few examples.

Problem solving itself might at first seem like it’s taking a back seat. But technical problem solving lies at the heart of programming, and most coding questions are designed to test a candidate’s problem-solving abilities.

Here are a few examples of technical problem-solving questions:

1. Mini-Max Sum  

This well-known challenge, which asks the interviewee to find the maximum and minimum sum among an array of given numbers, is based on a basic but important programming concept called sorting, as well as integer overflow. It tests the candidate’s observational skills, and the answer should elicit a logical, ad-hoc solution.

2. Organizing Containers of Balls  

This problem tests the candidate’s knowledge of a variety of programming concepts, like 2D arrays, sorting and iteration. Organizing colored balls in containers based on various conditions is a common question asked in competitive examinations and job interviews, because it’s an effective way to test multiple facets of a candidate’s problem-solving skills.

3. Build a Palindrome

This is a tough problem to crack, and the candidate’s knowledge of concepts like strings and dynamic programming plays a significant role in solving this challenge. This problem-solving example tests the candidate’s ability to think on their feet as well as their ability to write clean, optimized code.

4. Subarray Division

Based on a technique used for searching pairs in a sorted array ( called the “two pointers” technique ), this problem can be solved in just a few lines and judges the candidate’s ability to optimize (as well as basic mathematical skills).

5. The Grid Search 

This is a problem of moderate difficulty and tests the candidate’s knowledge of strings and searching algorithms, the latter of which is regularly tested in developer interviews across all levels.

Common Non-Technical Problem-Solving Interview Questions 

Testing a candidate’s problem-solving skills goes beyond the IDE . Everyday situations can help illustrate competency, so here are a few questions that focus on past experiences and hypothetical situations to help interviewers gauge problem-solving skills.

1. Given the problem of selecting a new tool to invest in, where and how would you begin this task? 

Key Insight : This question offers insight into the candidate’s research skills. Ideally, they would begin by identifying the problem, interviewing stakeholders, gathering insights from the team, and researching what tools exist to best solve for the team’s challenges and goals. 

2. Have you ever recognized a potential problem and addressed it before it occurred? 

Key Insight: Prevention is often better than cure. The ability to recognize a problem before it occurs takes intuition and an understanding of business needs. 

3. A teammate on a time-sensitive project confesses that he’s made a mistake, and it’s putting your team at risk of missing key deadlines. How would you respond?

Key Insight: Sometimes, all the preparation in the world still won’t stop a mishap. Thinking on your feet and managing stress are skills that this question attempts to unearth. Like any other skill, they can be cultivated through practice.

4. Tell me about a time you used a unique problem-solving approach. 

Key Insight: Creativity can manifest in many ways, including original or novel ways to tackle a problem. Methods like the 10X approach and reverse brainstorming are a couple of unique approaches to problem solving. 

5. Have you ever broken rules for the “greater good?” If yes, can you walk me through the situation?

Key Insight: “Ask for forgiveness, not for permission.” It’s unconventional, but in some situations, it may be the mindset needed to drive a solution to a problem.

6. Tell me about a weakness you overcame at work, and the approach you took. 

Key Insight: According to Compass Partnership , “self-awareness allows us to understand how and why we respond in certain situations, giving us the opportunity to take charge of these responses.” It’s easy to get overwhelmed when faced with a problem. Candidates showing high levels of self-awareness are positioned to handle it well.

7. Have you ever owned up to a mistake at work? Can you tell me about it?

Key Insight: Everybody makes mistakes. But owning up to them can be tough, especially at a workplace. Not only does it take courage, but it also requires honesty and a willingness to improve, all signs of 1) a reliable employee and 2) an effective problem solver.

8. How would you approach working with an upset customer?

Key Insight: With the rise of empathy-driven development and more companies choosing to bridge the gap between users and engineers, today’s tech teams speak directly with customers more frequently than ever before. This question brings to light the candidate’s interpersonal skills in a client-facing environment.

9. Have you ever had to solve a problem on your own, but needed to ask for additional help? How did you go about it? 

Key Insight: Knowing when you need assistance to complete a task or address a situation is an important quality to have while problem solving. This questions helps the interviewer get a sense of the candidate’s ability to navigate those waters. 

10. Let’s say you disagree with your colleague on how to move forward with a project. How would you go about resolving the disagreement?

Key Insight: Conflict resolution is an extremely handy skill for any employee to have; an ideal answer to this question might contain a brief explanation of the conflict or situation, the role played by the candidate and the steps taken by them to arrive at a positive resolution or outcome. 

Strategies for Answering Problem-Solving Questions

If you’re a job seeker, chances are you’ll encounter this style of question in your various interview experiences. While problem-solving interview questions may appear simple, they can be easy to fumble — leaving the interviewer without a clear solution or outcome. 

It’s important to approach such questions in a structured manner. Here are a few tried-and-true methods to employ in your next problem-solving interview.

1. Shine in Interviews With the STAR Method

S ituation, T ask, A ction, and R esult is a great method that can be employed to answer a problem-solving or behavioral interview question. Here’s a breakdown of these steps:

• Situation : A good way to address almost any interview question is to lay out and define the situation and circumstances. 
• Task : Define the problem or goal that needs to be addressed. Coding questions are often multifaceted, so this step is particularly important when answering technical problem-solving questions.
• Action : How did you go about solving the problem? Try to be as specific as possible, and state your plan in steps if you can.
• Result : Wrap it up by stating the outcome achieved. 

2. Rise above difficult questions using the SOAR method

A very similar approach to the STAR method, SOAR stands for S ituation, O bstacle, A ction, and R esults .

• Situation: Explain the state of affairs. It’s important to steer clear of stating any personal opinions in this step; focus on the facts.
• Obstacle: State the challenge or problem you faced.
• Action: Detail carefully how you went about overcoming this obstacle.
• Result: What was the end result? Apart from overcoming the obstacle, did you achieve anything else? What did you learn in the process? 

3. Do It the PREP Way

Traditionally used as a method to make effective presentations, the P oint, R eason, E xample, P oint method can also be used to answer problem-solving interview questions.  

• Point : State the solution in plain terms. 
• Reasons: Follow up the solution by detailing your case — and include any data or insights that support your solution. 
• Example: In addition to objective data and insights, drive your answer home by contextualizing the solution in a real-world example.
• Point : Reiterate the solution to make it come full circle.

How to Customize Problem-Solving Interview Questions 

Generic problem-solving interview questions go a long way in gauging a candidate’s skill level, but recruiters can go one step further by customizing these problem-solving questions according to their company’s service, product, vision, or culture. 

Here are some tips to do so:

• Break down the job’s responsibilities into smaller tasks. Job descriptions may contain ambiguous responsibilities like “manage team projects effectively.” To formulate an effective problem-solving question, envision what this task might look like in a real-world context and develop a question around it.  
• Tailor questions to the role at hand. Apart from making for an effective problem-solving question, it gives the candidate the impression you’re an informed technical recruiter. For example, an engineer will likely have attended many scrums. So, a good question to ask is: “Suppose you notice your scrums are turning unproductive. How would you go about addressing this?” 
• Consider the tools and technologies the candidate will use on the job. For example, if Jira is the primary project management tool, a good problem-solving interview question might be: “Can you tell me about a time you simplified a complex workflow — and the tools you used to do so?”
• If you don’t know where to start, your company’s core values can often provide direction. If one of the core values is “ownership,” for example, consider asking a question like: “Can you walk us through a project you owned from start to finish?” 
• Sometimes, developing custom content can be difficult even with all these tips considered. Our platform has a vast selection of problem-solving examples that are designed to help recruiters ask the right questions to help nail their next technical interview.

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Home » 10th Class » ICSE Competency Based Questions Mathematics | Class 10 Competency Practice Questions

ICSE Competency Based Questions Mathematics | Class 10 Competency Practice Questions

ICSE Competency Based Questions Mathematics are available for download here on aglasem.com. These ICSE Competency Based Questions include MCQs, fill in the blanks, short answer questions, long answer questions, and answer key from the Mathematics curriculum and need you to apply understanding a little beyond the ICSE class 10 textbook. For CISCE students, understanding and mastering these questions is crucial for success in Mathematics exam. Here you will understand what Competency Based Questions for Mathematics are, how they differ from traditional questions, and get tips on tackling these questions. You can also download ICSE Competency Based Questions Mathematics PDF for Class 10 below.

ICSE Competency Based Questions Mathematics

Here you can access a wide array of ICSE Competency Based Questions for the Mathematics subject. The PDF includes Multiple Choice Questions, Fill in the Blanks, Short Answer Questions, and Long Answer Questions, along with the answer key for class 10 Mathematics. The ICSE Competency Based Questions for Class 10 Mathematics can be found here.

Class 10 Competency Focused Practice Questions Download Link – Click Here to Download ICSE CBQ PDF

ICSE Competency Based Questions Mathematics PDF

The complete pdf for competency focused practice questions for Mathematics is as follows.

What are Mathematics Competency Based Questions?

These are designed to evaluate a student’s understanding of concepts of Mathematics, their ability to apply knowledge in real-life situations, and their critical thinking skills. Unlike traditional questions that may focus on rote learning or memorization, Competency Focused Questions require students to demonstrate a deeper comprehension of the subject matter (Mathematics). These questions measure various competencies in the Mathematics subject, such as problem-solving, logical reasoning, creativity, and subject-specific skills.

For Class 10 Competency Based Questions of Mathematics , students are expected to think beyond the Mathematics textbook and demonstrate their skills in a way that aligns with real-world applications.

ICSE 10 Competency Based Questions

In addition to Mathematics, the Competency Focused Questions for all subjects for CISCE students in 10th standard are as follows.

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CISCE Board CBQ

Similarly the class wise CBQ practice question bank for CISCE board are as follows.

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CISCE Class 10 Mathematics Competency Questions  – An Overview

The highlights of this educational resource are as follows.

Competency Based Questions are revolutionizing the way ICSE students approach their studies. By focusing on the core competencies required by the ICSE board, students in Class 10 can develop the skills necessary to excel academically and beyond. Whether you are dealing with Class 10 Mathematics Competency Based Questions or any other subject, remember to focus on understanding, application, and critical thinking.

Start practicing today, and make these questions a core part of your study strategy. The more you engage with these questions, the more confident you’ll become in your ability to tackle any challenge that comes your way!

If you have any queries on ICSE Mathematics Specimen Paper 2025, then please ask in comments below.

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A MIP-heuristic approach for solving a bi-objective optimization model for integrated production planning of sugarcane and energy-cane

• Original Research
• Published: 02 September 2024

Cite this article

• Gilmar Tolentino 1   na1 ,
• Antônio Roberto Balbo   ORCID: orcid.org/0000-0002-4512-0140 1   na1 ,
• Sônia Cristina Poltroniere 1   na1 ,
• Angelo Aliano Filho   ORCID: orcid.org/0000-0002-5088-134X 2   na1 &
• Helenice de Oliveira Florentino   ORCID: orcid.org/0000-0003-2740-8826 3   na1  

This paper proposes a modeling and solution approach for the integrated planning of the planting and harvesting of sucrose cane and energy-cane considering multiple harvesters. An integer linear bi-objective optimization model is proposed, which seeks to find a trade-off between the maximization of the production volumes of sucrose and fiber and the minimization of the operational costs. The model considers the technical constraints of the mill, such as the milling capacity and meeting the monthly demand. A MIP-heuristic based on relax-and-fix and fix-and-optimize strategies with exact decomposition is appropriately proposed to determine approximations to Pareto optimal solutions to this problem. These approximations are used as incumbents for a branch-and-bound tree to generate potentially Pareto optimal solutions. The results reveal that the MIP-heuristic efficiently solves the problem for real and semi-random instances, generating approximate solutions with a reduced error and a reasonable computational effort. Moreover, the different solutions quantify the trade-off between cost and production volume, opening up the possibility of increasing sucrose and fiber content or decreasing the costs of solutions found. Thus, the proposed bi-objective approach, the solution technique and the different Pareto optimal solutions obtained can assist mill managers in making better decisions in sugarcane production.

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The authors thank to Brazilian foundations: CNPq n \(^{\textrm{o}}\) 306518/2022-8, CNPq n \(^{\textrm{o}}\) 304218/2022-7, FAPESP 2021/03039-1,FAPESP 2022/12652-1, PROPE/PROPG/UNESP/ FUNDUNESP grant 12/2022, for the financial support and language services provided.

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Gilmar Tolentino, Antônio Roberto Balbo, Sônia Cristina Poltroniere, Angelo Aliano Filho and Helenice de Oliveira Florentino have contributed equally to this work.

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Department of Mathematics, State University of Sao Paulo, Bauru, São Paulo, 17033-360, Brazil

Gilmar Tolentino, Antônio Roberto Balbo & Sônia Cristina Poltroniere

Department of Mathematics, Universidade Tecnológica Federal do Paraná, Apucarana, Paraná, 86812-460, Brazil

Angelo Aliano Filho

Department of Bioestatistics, State University of Sao Paulo, Botucatu, São Paulo, 18618-690, Brazil

Helenice de Oliveira Florentino

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Tolentino, G., Balbo, A.R., Poltroniere, S.C. et al. A MIP-heuristic approach for solving a bi-objective optimization model for integrated production planning of sugarcane and energy-cane. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-06229-5

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Received : 06 May 2023

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DOI : https://doi.org/10.1007/s10479-024-06229-5

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